1.5.2 time

implement the new preferences in the backend
new preferences and bug fixes
2026-07-31 01:17:29 -07:00 · 2026-07-30 16:15:33 -07:00 · 2026-07-30 14:18:26 -07:00 · 2026-07-29 17:20:23 -07:00 · 2026-07-21 00:54:51 -07:00 · 2026-07-17 23:59:42 -07:00
47 changed files with 13984 additions and 4715 deletions
@@ -174,3 +174,11 @@ cython_debug/
 # PyPI configuration file
 .pypirc

+/individual_images
+*.xlsx
+*.csv
+*.snirf
+*.json
+flares-*
+*.flare
+*.cfg
@@ -41,4 +41,4 @@ There are no conditions for Linux users at this time.

 FLARES is distributed under the GPL-3.0 license.

-Copyright (C) 2025 Tyler de Zeeuw
+Copyright (C) 2025-2026 Tyler de Zeeuw
@@ -1,3 +1,298 @@
+# Version 1.5.2
+
+- Opening both a file or a folder now contains support for reading some metadata from the BIDS structure. Both options will still function if this metadata is not present
+- Currently only the AGE metadata is grabbed and is auto populated into the participants AGE field and displayed on their bubble
+- If the participants have metadata, a popup will be displayed asking if the user wants to group the participants by their metadata
+- If the user wants to create groups, a dialog box is presented allowing them to do so. Once completed, the GROUP value will be automatically applied to all applicable participants
+- A new options menu item has been added: Regroup Files from Metadata. This will allow the dialog to be opened at a later time with a popup appearing if there is no metadata present
+- Added two new options to the Export to CSV Viewer: Export Configuration to CSV and Paragraph of Configuration
+- Export Configuration to CSV will export the parameters utilized for each file into a CSV formatted file to provide additional validation of what parameters were used
+- Paragraph of Configuration will generate a ready-to-go paragraph explaining in a more friendly and easy to follow manner of what parameters were used
+- Chunked the loading of folders to provide more feedback to the user instead of hanging the application waiting for all files to load
+- New parameters have been added to the right side of the screen! This allows for more flexibility and customizability when processing
+- A new Preference Menu option has been added: Show Advanced Parameters. This keeps some of the parameters hidden when not checked. Since this is a preference, it will be saved when reopening the application
+- Advanced parameters should only be changed if you know what you are doing, and will have a yellow warning symbol next to them to avoid potential confusion on what parameters are advanced
+- Optimized some of the calculations in Scalp Coupling Index to speed up Step 6 by ~25%
+- Removed duplicate/redundant calculations in Peak Spectral Power to speed up Step 8 by ~50%
+- Changed how the figures are generated when processing to speed up Step 28 by ~85%
+- Removed unused methods inside the processing file to slightly speed up application load time
+- Fixed an issue with the build script not properly updating the version string causing the application to falsely think that an update was always available
+- Fixed an issue where parameters that were dependent on SHORT_CHANNELS were not properly being updated
+- Fixed an issue where files that failed processing were not having their progress bar turn red at the step that failed
+- Fixed an issue where progress bars were not updating when MAX_WORKERS was set to a value higher than default
+- Fixed an issue where a high value of MAX_WORKERS was never hit the targeted value due to not being able to spawn the workers fast enough
+- Fixed an issue causing numerous 'Invalid File' popups to appear upon closing the application while files were still having their initial metadata being grabbed
+- Fixed an issue where both 'Update events in snirf file...' windows could not be open at the same time
+- Fixed an issue where externally updating a participant's metadata when they were selected would cause the application to crash
+- Fixed an issue where there was a redundant checking of dependencies when the parameters on the right side of the screen were being calculated
+- Fixed an issue in which clicking menu options too fast would cause the application to hard crash
+- Added a time elapsed message to the status bar denoting how long processing has been going on for. When processing is complete, it will change to be the time elapsed
+- Added a speedup multiplier to show how much time was saved by having MAX_WORKERS not set to 1. This multiplier is calculated using a naive approach and may not be accurate
+- Removed redundant font styling when parameters were changed from their default values
+
+
+# Version 1.5.1
+
+- Opening a folder is now minimally BIDS compatible. It will recursively go through all folders, but not load external metadata
+- Renamed options in the Viewer Launcher window to better denote what actions they can perform
+- 2 new analysis options have been added in the viewer launcher window: Inter-Group Stats and Cross-Group Stats
+- Each of these analysis options have lots of text explaining what they do when their respective windows are opened
+- The parameter input dialog in the analysis windows will now be able to scroll down when lots of parameters are required
+- When a project is saved, it automatically will populate into the Recent Projects menu. Fixes [Issue 86](https://git.research.dezeeuw.ca/tyler/flares/issues/86)
+- The description when clicking "Why are these useful?" underneath the per-file parameters is no longer placeholder text. Fixes [Issue 85](https://git.research.dezeeuw.ca/tyler/flares/issues/85)
+- Added a new parameter section "Region of Interest". It has one parameter of "JSON_LOCATION", a json file containing Region of Interest data
+- Temporarily removed the parameter REMOVE_EVENTS due to its functionality being removed because of a memory leak
+- Fixed participant metadata remaining in the background when the participant was removed. Fixes [Issue 82](https://git.research.dezeeuw.ca/tyler/flares/issues/82)
+- Fixed processing remaining active hidden in the background when the "Clear" button was pushed. Fixes [Issue 81](https://git.research.dezeeuw.ca/tyler/flares/issues/81)
+- Now when "Clear" is pushed while data is processing, a popup will appear ensuring that the user understands that pushing "Clear" will stop processing
+- Reset to Default Configuration will now properly reset all of the parameters to their default values. [Issue 90](https://git.research.dezeeuw.ca/tyler/flares/issues/90)
+- A confirmation popup will now display once the application has been reset to default in addition to the status bar message
+- Changed the improper display text of "Cross Validation" to now properly read as "Coefficient of Variation"
+- Changed the parameters "CV" and "CV_THRESHOLD" to now be "COEFF_VAR and COEFF_VAR_THRESHOLD"
+- Changed the improper display text of "Mean Absolute Deviation" to now properly read as "Median Absolute Deviation"
+- Changed the parameters "SHORT_CHANNEL", "SHORT_CHANNEL_THRESH", and "LONG_CHANNEL_THRESH" to now be "SHORT_CHANNELS", "SHORT_CHANNELS_THRESHOLD", and "LONG_CHANNELS_THRESHOLD"
+- Changed the parameter section "Channel Variance" to now be "Sensor Dropout" to better reflect the action it performs, not the method employed to calculate it
+- Changed the parameters "CHANNEL_VAR" and "CHANNEL_THRESH" to now be "SENSOR_DROPOUT" and "SENSOR_DROPOUT_VARIANCE_THRESHOLD"
+- Changed the messaged displayed when the application crashes to better reflect what occurred
+- Changed the processing stages 25-27 and updates their messages to better reflect their actions that they now perform
+- Changed stage 25 from "Generate Channel Significance" to "Generate Channel Results"
+- Changed stage 26 from "Generate Channel, Region of Interest, and Contrast Results" to "Generate Region of Interest Results"
+- Changed stage 27 from "Compute Contrast Results" to "Generate Contrast Results"
+- Changed backend code to only load required methods and not load all methods every time
+- Fixed string parameters not going blue and bold when their value was different than default
+- Fixed all parameters not going blue and bold when a save file is loaded containing values that differ from default
+- Fixed a crucial bug where short channels were not being processed and filtered the same way as long channels before being used as regressors
+- Fixed a crucial bug where short channels were being presented to the design matrix as normal long channels
+- Fixed a crucial bug where long channels could be interpolated from short channels. Short channels are still potentially interpolated from long channels. See [this link](https://git.research.dezeeuw.ca/tyler/flares/issues/80) for more information regarding this issue.
+- Decreased unnecessary processing time when fOLDing channels by an order of magnitude
+- Added a welcome message when the terminal is opened, resized the terminal, and added more commands
+
+
+# Version 1.5.0
+
+- This release introduces a new configuration file that may break existing installs. If your application does not update correctly, please download fresh from [this link.](https://git.research.dezeeuw.ca/tyler/flares/releases/)
+- This release features an almost complete rewrite of backend files. If you encounter any problems, please raise an issue at [this link.](https://git.research.dezeeuw.ca/tyler/flares/issues/new)
+- New configuration file has been added! Now your choices of preferences will be saved when the application is closed and re-opened. If the configuration file is missing, a new one will be generated
+- Recent files and recent projects are now saved and appear under the File menu for quick resuming
+- The new option "Reset to Default Configuration" under the Options menu will reset the configuration file back to its default values and remove any recent files
+- A welcome dialog will now display the changelog on first startup and after every update. This popup will only appear once but can be reopened under the Options menu through the button "Show Update Changelog"
+- Changed the hotkey for "Update optodes in snirf file..." to be F9 instead of F6
+- Revamped the fOLD channels window. Images containing the pie charts are now interactable! Click whitespace to expand the whole image and click a chart to expand it.
+- fOLD progress bar when processing now updates the percentages live. Fixes [Issue 76](https://git.research.dezeeuw.ca/tyler/flares/issues/76)
+- Overall pie charts on an individual and global basis are now generated. Fixes [Issue 78](https://git.research.dezeeuw.ca/tyler/flares/issues/78)
+- Brodmann images are now available when examining a pie chart to understand which area is being reported. Fixes [Issue 77](https://git.research.dezeeuw.ca/tyler/flares/issues/77)
+- Added a new option 'Folding Bypass' to the Preferences Menu. This skips most processing steps and the only analysis option available will be to fold. Parameters on the right will be ignored. Fixes [Issue 75](https://git.research.dezeeuw.ca/tyler/flares/issues/75)
+- Fixed an issue where the fOLD analysis progress window would go unresponsive before processing participants. Fixes [Issue 45](https://git.research.dezeeuw.ca/tyler/flares/issues/45), Fixes [Issue 34](https://git.research.dezeeuw.ca/tyler/flares/issues/34)
+- Added a feature to hover over the 28-stage progress bar and see which state the progress bar is at. Fixes [Issue 74](https://git.research.dezeeuw.ca/tyler/flares/issues/74)
+- Loading a broken snirf file no longer hangs its processing and can now be removed from the list. Fixes [Issue 73](https://git.research.dezeeuw.ca/tyler/flares/issues/73)
+
+
+# Version 1.4.3
+
+- Fixed an issue where the fOLD files could not be located
+- Added better support for updating events from external software
+
+
+# Version 1.4.2
+
+- Fixed AGE, GENDER, GROUP not visually appearing on a bubble after the metadata has been set. Fixes [Issue 42](https://git.research.dezeeuw.ca/tyler/flares/issues/42)
+- Fixed first stage of progress bar going yellow after loading from an unprocessed save
+- Fixed AGE, GENDER, GROUP not visually appearing on a bubble when loading from a save 
+- Group images involving an optode template will now be the average of all participants selected in the group and not the last processed participant. Fixes [Issue 62](https://git.research.dezeeuw.ca/tyler/flares/issues/62)
+- Group images will no longer crash if being made with participants that have a different number of channels
+- Changed CSV files to now save to the same folder rather than asking each time for each file. Fixes [Issue 39](https://git.research.dezeeuw.ca/tyler/flares/issues/39)
+
+
+# Version 1.4.1
+
+- Hotfix to fix a recursive child loop that would cause the MacOS version to not open
+
+
+# Version 1.4.0
+
+- This is potentially a save-changing release due to changes in how file paths and parameters are stored. Please update your project files to ensure compatibility
+- It is still possible to load older saves by enabling 'Incompatible Save Bypass' from the Preferences menu, but your mileage may vary
+- AGE, GENDER, GROUP, loaded files, and all the parameters on the right side of the screen can now be saved before any data has been processed
+- If processing has not been completed, the process button will be visible. If processing has completed, the analysis button will be visible
+- If the values fail to load, they will fallback to the previous logic of retrieving these values after processing has occurred. Fixes [Issue 66](https://git.research.dezeeuw.ca/tyler/flares/issues/66)
+- Added new parameters to the right side of the screen: MAX_SHIFT, T_MIN, T_MAX, MAX_BAD_CHANNELS. Fixes [Issue 69](https://git.research.dezeeuw.ca/tyler/flares/issues/69)
+- Participants that are bad on channels will no longer continue to the GLM stage. Fixes [Issue 18](https://git.research.dezeeuw.ca/tyler/flares/issues/18)
+- Added new sections to the right side of the screen to mark bad channels: Cross Validation, Median Absolute Deviation, PSD Noise, & Channel Variance
+- These sections come with the new parameters CV, CV_THRESHOLD, MAD, MAD_THRESHOLD, PSD_NOISE, TARGET_FREQ_DIV, DB_LIMIT, CHANNEL_VAR, & CHANNEL_THRESH
+- Changed number of rectangles in the progress bar to 28 to account for the new options and updated the User Guide with the new stages
+- Added feedback when clicking an analysis option that opens up a new window. Fixes [Issue 20](https://git.research.dezeeuw.ca/tyler/flares/issues/20)
+- Fixed an issue where projects can not be saved to a different drive letter on windows. Fixes [Issue 71](https://git.research.dezeeuw.ca/tyler/flares/issues/71)
+- Fixed an issue where the fOLD files were not included in the Windows version. Fixes [Issue 60](https://git.research.dezeeuw.ca/tyler/flares/issues/60)
+- Fixed an issue where the MacOS version would fail to perform some analysis options. Fixes [Issue 63](https://git.research.dezeeuw.ca/tyler/flares/issues/63)
+- Fixed an issue where processing too many participants would cause the analysis button to not appear. Fixes [Issue 61](https://git.research.dezeeuw.ca/tyler/flares/issues/61)
+- Fixed an issue where the error message when a participant fails would not appear. Fixes [Issue 68](https://git.research.dezeeuw.ca/tyler/flares/issues/68)
+- Fixed an issue where changes would not be saved if a project was originally loaded from a save. Fixes [Issue 44](https://git.research.dezeeuw.ca/tyler/flares/issues/44)
+- Fixed an issue where the significance image would be empty in the Inter-Group Viewer if only one participant was selected. Fixes [Issue 32](https://git.research.dezeeuw.ca/tyler/flares/issues/32)
+- Fixed an issue where pressing the 'Clear' button after loading a save would cause the application to crash. Fixes [Issue 67](https://git.research.dezeeuw.ca/tyler/flares/issues/67)
+- Fixed an issue where group dropdowns in the Cross-Group viewer would not be updated correctly based on the other groups selected value. Fixes [Issue 49](https://git.research.dezeeuw.ca/tyler/flares/issues/49)
+- Fixed an issue where scrollbars were still present after clearing all data. Fixes [Issue 70](https://git.research.dezeeuw.ca/tyler/flares/issues/70)
+- Fixed an issue where 'Missing Events Bypass' did not work on the Cross-Group viewer. Fixes [Issue 64](https://git.research.dezeeuw.ca/tyler/flares/issues/64)
+- Fixed an issue where bubbles loaded from a save would not resize correctly. Fixes [Issue 14](https://git.research.dezeeuw.ca/tyler/flares/issues/14)
+
+
+# Version 1.3.0
+
+- This is potentially a save-changing release due to a new parameter being saved. Please update your project files to ensure compatibility
+- It is still possible to load older saves by enabling 'Incompatible Save Bypass' from the Preferences menu, but your mileage may vary
+- Fixed workers not releasing memory when processing multiple participants. Fixes [Issue 55](https://git.research.dezeeuw.ca/tyler/flares/issues/55)
+- Fixed part of an issue where memory could increase over time despite clicking the clear button. There are still some edge cases where this can occur 
+- Fixed an issue when clearing a bubble, reloading the same file, and clicking it again would cause the app to crash. Fixes [Issue 57](https://git.research.dezeeuw.ca/tyler/flares/issues/57)
+- Picking a .txt or .xlsx file now has both in the same file selection instead of having to select which extension was desired
+- Added a new parameter to the right side of the screen: EPOCH_HANDLING. Fixes [Issue 58](https://git.research.dezeeuw.ca/tyler/flares/issues/58)
+- EPOCH_HANDLING defaults to 'shift' compared to previous versions where the default would have been equivalent to 'strict'
+- The label for ENHANCE_NEGATIVE_CORRELATION no longer gets cut off by its dropdown selection
+- Loading in files and folders have changes to immediately show their bubbles having a respective loading symbol on each bubble
+- Once the file has been completely loaded and processed, the loading symbol will change to a green checkmark and clicking will be enabled
+- The metadata in the File information widget is now saved to prevent recalculations every time the bubble is selected
+- The status bar will now say loading while the bubbles are being processed, and loaded once the processing has completed
+- This new loading method will prevent the application from hanging when loading lots of files at once. Fixes [Issue 59](https://git.research.dezeeuw.ca/tyler/flares/issues/59)
+- Fixed text alignment for the first paragraph when a bubble is selected in the 'File information' widget
+- The three main widgets are now resizable! All of them have minimum widths to ensure they do not get too squished
+- Added a new option 'Reset Window Layout' under the View menu that will resize all widgets back to their default sizes
+- Added a new terminal command 'version' that will print the applications current version
+
+
+# Version 1.2.2
+
+- Added 'Update events in snirf file (BLAZES)...' and renamed 'Update events in snirf file...' to 'Update events in snirf file (BORIS)...' under the Options menu
+- The BLAZES option will assign events that are exported directly from the software [BLAZES](https://git.research.dezeeuw.ca/tyler/blazes)
+- Moved the updating logic to a separate file for better reusability and generalization
+- Fixed 'Toggle Status Bar' having no effect on the visibility of the status bar
+- Fixed a bug when updating optode positions that would prevent .txt files from being selected. Fixes [Issue 54](https://git.research.dezeeuw.ca/tyler/flares/issues/54)
+- Fixed a missing dependency in the standalone application when attempting to use an .xlsx file to update optode positions
+
+
+# Version 1.2.1
+
+- Added a requirements.txt file to ensure compatibility
+- Added new options 'Missing Events Bypass' and 'Analysis Clearing Bypass' to the Preferences Menu
+- Missing Events Bypass allows comparing events in the Group Viewers even if not all participants in the group have the event present. Fixes [Issue 28](https://git.research.dezeeuw.ca/tyler/flares/issues/28)
+- Clicking Process after an analysis has been performed will now clear the existing analysis by default with a popup warning that the analysis will be cleared
+- Analysis Clearing Bypass will prevent the popup and will not clear the existing analysis data. Fixes [Issue 41](https://git.research.dezeeuw.ca/tyler/flares/issues/41)
+- Clicking 'Clear' should now actually properly clear all data. Hopefully fixes [Issue 9](https://git.research.dezeeuw.ca/tyler/flares/issues/9) for good
+- Setting SHORT_CHANNEL to False will now grey out SHORT_CHANNEL_REGRESSION, as it is impossible to regress what does not exist. Sets SHORT_CHANNEL_REGRESSION to False under the hood when it is greyed out regardless of what is displayed. Fixes [Issue 47](https://git.research.dezeeuw.ca/tyler/flares/issues/47)
+- Projects can now be saves if files have different parent folders. Fixes [Issue 48](https://git.research.dezeeuw.ca/tyler/flares/issues/48)
+- It is no longer possible to attempt a save before any data has been processed. A popup will now display if a save is attempted with nothing to save
+- Fixed a bug where LONG_CHANNEL_THRESH was not being applied in the processing steps
+- Added a new option in the Analysis window for Group Functional Connectivity. Implements [Issue 50](https://git.research.dezeeuw.ca/tyler/flares/issues/50)
+- Group Functional connectivity is still in development and the results should currently be taken with a grain of salt
+- A warning is displayed when entering the Group Functional Connectivity Viewer disclosing this
+- Fixed a bug when updating optode positions that would prevent .txt files from being selected. Fixes [Issue 54](https://git.research.dezeeuw.ca/tyler/flares/issues/54)
+- Fixed a bug where the secondary download server would never get contacted if the primary failed
+- Automatic downloads will now ignore prerelease versions. Fixes [Issue 52](https://git.research.dezeeuw.ca/tyler/flares/issues/52)
+
+
+# Version 1.2.0
+
+- This is a save-breaking release due to a new save file format. Please update your project files to ensure compatibility. Fixes [Issue 30](https://git.research.dezeeuw.ca/tyler/flares/issues/30)
+- Added new parameters to the right side of the screen
+- These parameters include SHOW_OPTODE_NAMES, SECONDS_TO_STRIP_HR, MAX_LOW_HR, MAX_HIGH_HR, SMOOTHING_WINDOW_HR, HEART_RATE_WINDOW, BAD_CHANNELS_HANDLING, MAX_DIST, MIN_NEIGHBORS, L_TRANS_BANDWIDTH, H_TRANS_BANDWIDTH, RESAMPLE, RESAMPLE_FREQ, STIM_DUR, HRF_MODEL, HIGH_PASS, DRIFT_ORDER, FIR_DELAYS, MIN_ONSET, OVERSAMPLING, SHORT_CHANNEL_REGRESSION, NOISE_MODEL, BINS, and VERBOSITY.
+- Certain parameters now have dependencies on other parameters and will now grey out if they are not used
+- All the new parameters have default values matching the underlying values in version 1.1.7
+- The order of the parameters has been changed to match the order that the code runs when the Process button is clicked
+- Moved TIME_WINDOW_START and TIME_WINDOW_END to the 'Other' category
+- Fixed a bug causing SCI to not work when HEART_RATE was set to False
+- Bad channels can now be dealt with by taking no action, removing them completely, or interpolating them based on their neighbours. Interpolation remains the default option
+- Fixed an underlying deprecation warning
+- Fixed an issue causing some overlay elements to not render on the brain for certain devices
+- Fixed a crash when rendering some Inter-Group images with only one participant in a group
+- Fixed a crash when attempting to fOLD channels without the fOLD dataset installed
+- Lowered the number of rectangles in the progress bar to 24 after combining some actions
+- Fixed the User Guide window to properly display information about the 24 stages and added a link to the Git wiki page
+- MAX_WORKERS should now properly respect the value set
+- Added a new CSV export option to be used by other applications
+- Added support for updating optode positions directly from an .xlsx file from a Polhemius system
+- Fixed an issue where the dropdowns in the Viewer windows would immediately open and close when using a trackpad
+- glover and spm HRF models now function as intended without crashing. Currently, group analysis is still only supported by fir. Fixes [Issue 8](https://git.research.dezeeuw.ca/tyler/flares/issues/8)
+- Clicking 'Clear' should now properly clear all data. Fixes [Issue 9](https://git.research.dezeeuw.ca/tyler/flares/issues/9)
+- Revamped the fold channels viewer to not hang the application and to better process multiple participants at once. Fixes [Issue 34](https://git.research.dezeeuw.ca/tyler/flares/issues/34), [Issue 31](https://git.research.dezeeuw.ca/tyler/flares/issues/31)
+- Added a Preferences menu to the navigation bar
+- Two preferences have been added allowing to bypass the warning of 2D data detected and save files being from previous, potentially breaking versions
+- Fixed a typo when saving a CSV that stated a SNIRF was being saved
+- Loading a save file now properly restores AGE, GENDER, and GROUP. Fixes [Issue 40](https://git.research.dezeeuw.ca/tyler/flares/issues/40)
+- Saving a project now no longer makes the main window go not responding. Fixes [Issue 43](https://git.research.dezeeuw.ca/tyler/flares/issues/43)
+- Memory usage should no longer grow when generating lots of images multiple times. Fixes [Issue 36](https://git.research.dezeeuw.ca/tyler/flares/issues/36)
+- Added a new option in the Analysis window for Functional Connectivity
+- Functional connectivity is still in development and the results should currently be taken with a grain of salt
+- A warning is displayed when entering the Functional Connectivity Viewer disclosing this
+
+
+# Version 1.1.7
+
+- Fixed a bug where having both a L_FREQ and H_FREQ would cause only the L_FREQ to be used
+- Changed the default H_FREQ from 0.7 to 0.3
+- Added a PSD graph, along with 2 heart rate images to the individual participant viewer
+- The PSD graph is used to help calculate the heart rate, whereas the other 2 are currently just for show
+- SCI is now done using a .6hz window around the calculated heart rate compared to a window around an average heart rate
+- Fixed an issue with some epochs figures not showing under the participant analysis
+- Removed SECONDS_TO_STRIP from the preprocessing options
+- Added new parameters to the right side of the screen
+- These parameters include TRIM, SECONDS_TO_KEEP, OPTODE_PLACEMENT, HEART_RATE, WAVELET, IQR, WAVELET_TYPE, WAVELET_LEVEL, ENHANCE_NEGATIVE_CORRELATION, SHORT_CHANNEL_THRESH, LONG_CHANNEL_THRESH, and DRIFT_MODEL
+- Changed number of rectangles in the progress bar to 25 to account for the new options
+
+
+# Version 1.1.6
+
+- Fixed Process button from appearing when no files are selected
+- Fixed a bug that would cause an instant child process crash on Windows
+- Added L_FREQ and H_FREQ parameters for more user control over low and high pass filtering
+
+
+# Version 1.1.5
+
+- Fixed Windows saves not being able to be opened by a Mac (hopefully the other way too!)
+- Added the option to right click loaded snirf files to reveal them in a file browser or delete them if they are no longer desired
+- Changed the way folders are opened to store the files separately rather than the folder as a whole to allow for the removal of files
+- Fixed issues with dropdowns and bubbles not populating correctly when opening a single file and temporarily removed the option to open multiple folders
+- Improved crash handling and the message that is displayed to the user if the application crashes
+- Progress bar will now colour the stage that fails as red if a file fails during processing
+- A warning message will be displayed when a file fails to process with information on what went wrong. This message does not halt the rest of the processing of the other files
+- Fixed the number of rectangles in the progress bar to 20 (was incorrect in v1.1.1)
+- Added validation to ensure loaded files do not have 2-dimensional data when clicking process to prevent inaccurate results from being generated
+- Added more metadata information to the top left information panel
+- Changed the Status Bar message when processing is complete to state how many were successful and how many were not
+- Added a clickable link below the selected file's metadata explaining the independent parameters and why they are useful
+- Updated some tooltips to provide better, more accurate information
+- Added details about the processing steps and their order into the user guide
+- Changed the default bandpass filtering parameters
+
+
+# Version 1.1.4
+
+- Fixed some display text to now display the correct information
+- A new option under Analysis has been added to export the data from a specified participant as a csv file. Fixes [Issue 19](https://git.research.dezeeuw.ca/tyler/flares/issues/19), [Issue 27](https://git.research.dezeeuw.ca/tyler/flares/issues/27)
+- Added 2 new parameters - TIME_WINDOW_START and TIME_WINDOW_END. Fixes [Issue 29](https://git.research.dezeeuw.ca/tyler/flares/issues/29)
+- These parameters affect the visualization of the significance and contrast images but do not change the total time modeled underneath
+- Fixed the duration of annotations edited from a BORIS file from 0 seconds to their proper duration
+- Added the annotation information to each participant under their "File information" window
+- Fixed Macs not being able to save snirfs attempting to be updated from BORIS files, and in general the updated files not respecting the path chosen by the user
+
+
+# Version 1.1.3
+
+- Added back the ability to use the fOLD dataset. Fixes [Issue 23](https://git.research.dezeeuw.ca/tyler/flares/issues/23)
+- 5th option has been added under Analysis to get to fOLD channels per participant
+- Added an option to cancel the running process. Fixes [Issue 15](https://git.research.dezeeuw.ca/tyler/flares/issues/15)
+- Prevented graph images from showing when participants are being processed. Fixes [Issue 24](https://git.research.dezeeuw.ca/tyler/flares/issues/24)
+- Allow the option to remove all events of a type from all loaded snirfs. Fixes [Issue 25](https://git.research.dezeeuw.ca/tyler/flares/issues/25)
+- Added new icons in the menu bar
+- Added a terminal to interact with the app in a more command-like form
+- Currently the terminal has no functionality but some features for batch operations will be coming soon!
+- Inter-Group viewer now has the option to visualize the average response on the brain of all participants in the group. Fixes [Issue 26](https://git.research.dezeeuw.ca/tyler/flares/issues/24)
+- Fixed the description under "Update events in snirf file..."
+
+
+# Version 1.1.2
+
+- Fixed incorrect colormaps being applied
+- Added functionality to utilize external event markers from a file. Fixes [Issue 6](https://git.research.dezeeuw.ca/tyler/flares/issues/6)
+
+
 # Version 1.1.1

 - Fixed the number of rectangles in the progress bar to 19
@@ -15,13 +310,13 @@
 - Added a group option when clicking on a participant's file
 - If no group is specified, the participant will be added to the "Default" group
 - Added option to update the optode positions in a snirf file from the Options menu (F6)
- Fixed [Issue 3](https://git.research.dezeeuw.ca/tyler/flares/issues/3), [Issue 4](https://git.research.dezeeuw.ca/tyler/flares/issues/4), [Issue 17](https://git.research.dezeeuw.ca/tyler/flares/issues/17), [Issue 21](https://git.research.dezeeuw.ca/tyler/flares/issues/21), [Issue 22](https://git.research.dezeeuw.ca/tyler/flares/issues/22)
+- Fixed [Issue 3](https://git.research.dezeeuw.ca/tyler/flares/issues/3), [Issue 5](https://git.research.dezeeuw.ca/tyler/flares/issues/5), [Issue 17](https://git.research.dezeeuw.ca/tyler/flares/issues/17), [Issue 21](https://git.research.dezeeuw.ca/tyler/flares/issues/21), [Issue 22](https://git.research.dezeeuw.ca/tyler/flares/issues/22)


 # Version 1.0.1

 - Two new options have been added when clicking on a participant's file.
- First new option is Age which allows the option to specify age on a per-file basis to calculate DPF by using the Scholkmann & Wolf calculation instead of having one DPF for all files. Fixes [Issue 1](https://git.research.dezeeuw.ca/tyler/flares/issues/1). This also allows for proper calculation of DPF for the two seperate wavelengths.
+- First new option is Age which allows the option to specify age on a per-file basis to calculate DPF by using the Scholkmann & Wolf calculation instead of having one DPF for all files. Fixes [Issue 1](https://git.research.dezeeuw.ca/tyler/flares/issues/1). This also allows for proper calculation of DPF for the two separate wavelengths.
 - If no age is set by the user, the code will fall back to the age of 25
 - Second new option is Gender to be used in future analysis options (currently not implemented).
 - UI elements have been shuffled to make room for the new parameters.
@@ -0,0 +1,87 @@
+# Version 1.5.2
+
+- Opening both a file or a folder now contains support for reading some metadata from the BIDS structure. Both options will still function if this metadata is not present
+- Currently only the AGE metadata is grabbed and is auto populated into the participants AGE field and displayed on their bubble
+- If the participants have metadata, a popup will be displayed asking if the user wants to group the participants by their metadata
+- If the user wants to create groups, a dialog box is presented allowing them to do so. Once completed, the GROUP value will be automatically applied to all applicable participants
+- A new options menu item has been added: Regroup Files from Metadata. This will allow the dialog to be opened at a later time with a popup appearing if there is no metadata present
+- Added two new options to the Export to CSV Viewer: Export Configuration to CSV and Paragraph of Configuration
+- Export Configuration to CSV will export the parameters utilized for each file into a CSV formatted file to provide additional validation of what parameters were used
+- Paragraph of Configuration will generate a ready-to-go paragraph explaining in a more friendly and easy to follow manner of what parameters were used
+- Chunked the loading of folders to provide more feedback to the user instead of hanging the application waiting for all files to load
+- New parameters have been added to the right side of the screen! This allows for more flexibility and customizability when processing
+- A new Preference Menu option has been added: Show Advanced Parameters. This keeps some of the parameters hidden when not checked. Since this is a preference, it will be saved when reopening the application
+- Advanced parameters should only be changed if you know what you are doing, and will have a yellow warning symbol next to them to avoid potential confusion on what parameters are advanced
+- Optimized some of the calculations in Scalp Coupling Index to speed up Step 6 by ~25%
+- Removed duplicate/redundant calculations in Peak Spectral Power to speed up Step 8 by ~50%
+- Changed how the figures are generated when processing to speed up Step 28 by ~85%
+- Removed unused methods inside the processing file to slightly speed up application load time
+- Fixed an issue with the build script not properly updating the version string causing the application to falsely think that an update was always available
+- Fixed an issue where parameters that were dependent on SHORT_CHANNELS were not properly being updated
+- Fixed an issue where files that failed processing were not having their progress bar turn red at the step that failed
+- Fixed an issue where progress bars were not updating when MAX_WORKERS was set to a value higher than default
+- Fixed an issue where a high value of MAX_WORKERS was never hit the targeted value due to not being able to spawn the workers fast enough
+- Fixed an issue causing numerous 'Invalid File' popups to appear upon closing the application while files were still having their initial metadata being grabbed
+- Fixed an issue where both 'Update events in snirf file...' windows could not be open at the same time
+- Fixed an issue where externally updating a participant's metadata when they were selected would cause the application to crash
+- Fixed an issue where there was a redundant checking of dependencies when the parameters on the right side of the screen were being calculated
+- Fixed an issue in which clicking menu options too fast would cause the application to hard crash
+- Added a time elapsed message to the status bar denoting how long processing has been going on for. When processing is complete, it will change to be the time elapsed
+- Added a speedup multiplier to show how much time was saved by having MAX_WORKERS not set to 1. This multiplier is calculated using a naive approach and may not be accurate
+- Removed redundant font styling when parameters were changed from their default values
+
+
+# Version 1.5.1
+
+- Opening a folder is now minimally BIDS compatible. It will recursively go through all folders, but not load external metadata
+- Renamed options in the Viewer Launcher window to better denote what actions they can perform
+- 2 new analysis options have been added in the viewer launcher window: Inter-Group Stats and Cross-Group Stats
+- Each of these analysis options have lots of text explaining what they do when their respective windows are opened
+- The parameter input dialog in the analysis windows will now be able to scroll down when lots of parameters are required
+- When a project is saved, it automatically will populate into the Recent Projects menu. Fixes [Issue 86](https://git.research.dezeeuw.ca/tyler/flares/issues/86)
+- The description when clicking "Why are these useful?" underneath the per-file parameters is no longer placeholder text. Fixes [Issue 85](https://git.research.dezeeuw.ca/tyler/flares/issues/85)
+- Added a new parameter section "Region of Interest". It has one parameter of "JSON_LOCATION", a json file containing Region of Interest data
+- Temporarily removed the parameter REMOVE_EVENTS due to its functionality being removed because of a memory leak
+- Fixed participant metadata remaining in the background when the participant was removed. Fixes [Issue 82](https://git.research.dezeeuw.ca/tyler/flares/issues/82)
+- Fixed processing remaining active hidden in the background when the "Clear" button was pushed. Fixes [Issue 81](https://git.research.dezeeuw.ca/tyler/flares/issues/81)
+- Now when "Clear" is pushed while data is processing, a popup will appear ensuring that the user understands that pushing "Clear" will stop processing
+- Reset to Default Configuration will now properly reset all of the parameters to their default values. [Issue 90](https://git.research.dezeeuw.ca/tyler/flares/issues/90)
+- A confirmation popup will now display once the application has been reset to default in addition to the status bar message
+- Changed the improper display text of "Cross Validation" to now properly read as "Coefficient of Variation"
+- Changed the parameters "CV" and "CV_THRESHOLD" to now be "COEFF_VAR and COEFF_VAR_THRESHOLD"
+- Changed the improper display text of "Mean Absolute Deviation" to now properly read as "Median Absolute Deviation"
+- Changed the parameters "SHORT_CHANNEL", "SHORT_CHANNEL_THRESH", and "LONG_CHANNEL_THRESH" to now be "SHORT_CHANNELS", "SHORT_CHANNELS_THRESHOLD", and "LONG_CHANNELS_THRESHOLD"
+- Changed the parameter section "Channel Variance" to now be "Sensor Dropout" to better reflect the action it performs, not the method employed to calculate it
+- Changed the parameters "CHANNEL_VAR" and "CHANNEL_THRESH" to now be "SENSOR_DROPOUT" and "SENSOR_DROPOUT_VARIANCE_THRESHOLD"
+- Changed the messaged displayed when the application crashes to better reflect what occurred
+- Changed the processing stages 25-27 and updates their messages to better reflect their actions that they now perform
+- Changed stage 25 from "Generate Channel Significance" to "Generate Channel Results"
+- Changed stage 26 from "Generate Channel, Region of Interest, and Contrast Results" to "Generate Region of Interest Results"
+- Changed stage 27 from "Compute Contrast Results" to "Generate Contrast Results"
+- Changed backend code to only load required methods and not load all methods every time
+- Fixed string parameters not going blue and bold when their value was different than default
+- Fixed all parameters not going blue and bold when a save file is loaded containing values that differ from default
+- Fixed a crucial bug where short channels were not being processed and filtered the same way as long channels before being used as regressors
+- Fixed a crucial bug where short channels were being presented to the design matrix as normal long channels
+- Fixed a crucial bug where long channels could be interpolated from short channels. Short channels are still potentially interpolated from long channels. See [this link](https://git.research.dezeeuw.ca/tyler/flares/issues/80) for more information regarding this issue.
+- Decreased unnecessary processing time when fOLDing channels by an order of magnitude
+- Added a welcome message when the terminal is opened, resized the terminal, and added more commands
+
+
+# Version 1.5.0
+
+- This release introduces a new configuration file that may break existing installs. If your application does not update correctly, please download fresh from [this link.](https://git.research.dezeeuw.ca/tyler/flares/releases/)
+- This release features an almost complete rewrite of backend files. If you encounter any problems, please raise an issue at [this link.](https://git.research.dezeeuw.ca/tyler/flares/issues/new)
+- New configuration file has been added! Now your choices of preferences will be saved when the application is closed and re-opened. If the configuration file is missing, a new one will be generated
+- Recent files and recent projects are now saved and appear under the File menu for quick resuming
+- The new option "Reset to Default Configuration" under the Options menu will reset the configuration file back to its default values and remove any recent files
+- A welcome dialog will now display the changelog on first startup and after every update. This popup will only appear once but can be reopened under the Options menu through the button "Show Update Changelog"
+- Changed the hotkey for "Update optodes in snirf file..." to be F9 instead of F6
+- Revamped the fOLD channels window. Images containing the pie charts are now interactable! Click whitespace to expand the whole image and click a chart to expand it.
+- fOLD progress bar when processing now updates the percentages live. Fixes [Issue 76](https://git.research.dezeeuw.ca/tyler/flares/issues/76)
+- Overall pie charts on an individual and global basis are now generated. Fixes [Issue 78](https://git.research.dezeeuw.ca/tyler/flares/issues/78)
+- Brodmann images are now available when examining a pie chart to understand which area is being reported. Fixes [Issue 77](https://git.research.dezeeuw.ca/tyler/flares/issues/77)
+- Added a new option 'Folding Bypass' to the Preferences Menu. This skips most processing steps and the only analysis option available will be to fold. Parameters on the right will be ignored. Fixes [Issue 75](https://git.research.dezeeuw.ca/tyler/flares/issues/75)
+- Fixed an issue where the fOLD analysis progress window would go unresponsive before processing participants. Fixes [Issue 45](https://git.research.dezeeuw.ca/tyler/flares/issues/45), Fixes [Issue 34](https://git.research.dezeeuw.ca/tyler/flares/issues/34)
+- Added a feature to hover over the 28-stage progress bar and see which state the progress bar is at. Fixes [Issue 74](https://git.research.dezeeuw.ca/tyler/flares/issues/74)
+- Loading a broken snirf file no longer hangs its processing and can now be removed from the list. Fixes [Issue 73](https://git.research.dezeeuw.ca/tyler/flares/issues/73)
@@ -18,11 +18,12 @@ import subprocess
 from datetime import datetime

 PLATFORM_NAME = platform.system().lower()
+APP_NAME = "flares"

 if PLATFORM_NAME == 'darwin':
-    LOG_FILE = os.path.join(os.path.dirname(sys.executable), "../../../flares_updater.log")
+    LOG_FILE = os.path.join(os.path.dirname(sys.executable), f"../../../{APP_NAME}_updater.log")
 else:
-    LOG_FILE = os.path.join(os.getcwd(), "flares_updater.log")
+    LOG_FILE = os.path.join(os.getcwd(), f"{APP_NAME}_updater.log")


 def log(msg):
@@ -147,7 +148,7 @@ def copy_update_files_darwin(src_folder, dest_folder, updater_name):

 def remove_quarantine(app_path):
    script = f'''
-    do shell script "xattr -d -r com.apple.quarantine {shlex.quote(app_path)}" with administrator privileges with prompt "FLARES needs privileges to finish the update. (1/2)"
+    do shell script "xattr -d -r com.apple.quarantine {shlex.quote(app_path)}" with administrator privileges with prompt "{APP_NAME} needs privileges to finish the update. (1/2)"
    '''
    try:
        subprocess.run(['osascript', '-e', script], check=True)
@@ -162,7 +163,7 @@ def main():
        log(f"[Updater] sys.argv: {sys.argv}")

        if len(sys.argv) != 3:
-            log("Invalid arguments. Usage: flares_updater <update_folder> <main_app_executable>")
+            log(f"Invalid arguments. Usage: {APP_NAME}_updater <update_folder> <main_app_executable>")
            sys.exit(1)

        update_folder = sys.argv[1]
@@ -215,7 +216,7 @@ def main():
        if PLATFORM_NAME == 'darwin':
            log(f'Attempting to delete {ppparent_dir}')
            delete_path(ppparent_dir)
-            update_folder = os.path.join(sys.argv[1], "flares-darwin")
+            update_folder = os.path.join(sys.argv[1], f"{APP_NAME}-darwin")
            copy_update_files_darwin(update_folder, pppparent_dir, updater_name)

        else:
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M400-280h160v-80H400v80Zm0-160h280v-80H400v80ZM280-600h400v-80H280v80Zm200 120ZM265-80q-79 0-134.5-55.5T75-270q0-57 29.5-102t77.5-68H80v-80h240v240h-80v-97q-37 8-61 38t-24 69q0 46 32.5 78t77.5 32v80Zm135-40v-80h360v-560H200v160h-80v-160q0-33 23.5-56.5T200-840h560q33 0 56.5 23.5T840-760v560q0 33-23.5 56.5T760-120H400Z"/></svg>
@@ -1,2 +0,0 @@
-[LocalizedFileNames]
-updater.png=@updater.png,0
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M160-160q-33 0-56.5-23.5T80-240v-480q0-33 23.5-56.5T160-800h240l80 80h320q33 0 56.5 23.5T880-640v242q-18-14-38-23t-42-19v-200H447l-80-80H160v480h120v80H160ZM640-40q-91 0-168-48T360-220q35-84 112-132t168-48q91 0 168 48t112 132q-35 84-112 132T640-40Zm0-80q57 0 107.5-26t82.5-74q-32-48-82.5-74T640-320q-57 0-107.5 26T450-220q32 48 82.5 74T640-120Zm0-40q-25 0-42.5-17.5T580-220q0-25 17.5-42.5T640-280q25 0 42.5 17.5T700-220q0 25-17.5 42.5T640-160Zm-480-80v-480 277-37 240Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M200-120q-33 0-56.5-23.5T120-200v-560q0-33 23.5-56.5T200-840h560q33 0 56.5 23.5T840-760v560q0 33-23.5 56.5T760-120H200Zm0-80h320v-560H200v560Zm560 0v-560H600v560h160Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M480-120q-138 0-240.5-91.5T122-440h82q14 104 92.5 172T480-200q117 0 198.5-81.5T760-480q0-117-81.5-198.5T480-760q-69 0-129 32t-101 88h110v80H120v-240h80v94q51-64 124.5-99T480-840q75 0 140.5 28.5t114 77q48.5 48.5 77 114T840-480q0 75-28.5 140.5t-77 114q-48.5 48.5-114 77T480-120Zm112-192L440-464v-216h80v184l128 128-56 56Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M480-80q-155 0-269-103T82-440h81q15 121 105.5 200.5T480-160q134 0 227-93t93-227q0-134-93-227t-227-93q-86 0-159.5 42.5T204-640h116v80H88q29-140 139-230t253-90q83 0 156 31.5T763-763q54 54 85.5 127T880-480q0 83-31.5 156T763-197q-54 54-127 85.5T480-80Zm112-232L440-464v-216h80v184l128 128-56 56Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M200-440v-80h560v80H200Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M520-330v-60h160v60H520Zm60 210v-50h-60v-60h60v-50h60v160h-60Zm100-50v-60h160v60H680Zm40-110v-160h60v50h60v60h-60v50h-60Zm111-280h-83q-26-88-99-144t-169-56q-117 0-198.5 81.5T200-480q0 72 32.5 132t87.5 98v-110h80v240H160v-80h94q-62-50-98-122.5T120-480q0-75 28.5-140.5t77-114q48.5-48.5 114-77T480-840q129 0 226.5 79.5T831-560Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M160-160q-33 0-56.5-23.5T80-240v-480q0-33 23.5-56.5T160-800h640q33 0 56.5 23.5T880-720v480q0 33-23.5 56.5T800-160H160Zm0-80h640v-400H160v400Zm140-40-56-56 103-104-104-104 57-56 160 160-160 160Zm180 0v-80h240v80H480Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M280-160v-80h400v80H280Zm160-160v-327L336-544l-56-56 200-200 200 200-56 56-104-103v327h-80Z"/></svg>
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" height="24px" viewBox="0 -960 960 960" width="24px" fill="#1f1f1f"><path d="M451.5-251.5Q440-263 440-280t11.5-28.5Q463-320 480-320t28.5 11.5Q520-297 520-280t-11.5 28.5Q497-240 480-240t-28.5-11.5ZM440-360v-161l80 80v81h-80Zm433 158L655-419 480-720l-47 80-58-58 105-182 393 678Zm-695 2h469L350-497 178-200ZM819-28l-92-92H40l252-435L27-820l57-57L876-85l-57 57ZM499-348Zm45-181Z"/></svg>
@@ -10,7 +10,7 @@ from pathlib import Path

 import numpy as np
 from scipy import linalg
-from scipy.special import lpmv, sph_harm
+from scipy.special import lpmv, sph_harm_y

 from .. import __version__
 from .._fiff.compensator import make_compensator
@@ -1487,7 +1487,7 @@ def _sss_basis_basic(exp, coils, mag_scale=100.0, method="standard"):
            S_in_out = list()
            grads_in_out = list()
            # Same spherical harmonic is used for both internal and external
-            sph = sph_harm(order, degree, az, pol)
+            sph = sph_harm_y(order, degree, az, pol)
            sph_norm = _sph_harm_norm(order, degree)
            # Compute complex gradient for all integration points
            # in spherical coordinates (Eq. 6). The gradient for rad, az, pol
@@ -12,7 +12,7 @@ from pathlib import Path
 import numpy as np
 from scipy import linalg
 from scipy.spatial.distance import cdist
-from scipy.special import sph_harm
+from scipy.special import sph_harm_y

 from ._fiff.constants import FIFF
 from ._fiff.open import fiff_open
@@ -1025,7 +1025,7 @@ def _handle_sensor_types(meg, eeg, fnirs):
        fnirs=dict(channels="fnirs", pairs="fnirs_pairs"),
    )
    sensor_alpha = {
-        key: dict(meg_helmet=0.25, meg=0.25).get(key, 0.8)
+        key: dict(meg_helmet=0.25, meg=0.25).get(key, 1.0)
        for ch_dict in alpha_map.values()
        for key in ch_dict.values()
    }
@@ -586,7 +586,7 @@ class _PyVistaRenderer(_AbstractRenderer):
                color = None
            else:
                scalars = None
-            tube = line.tube(radius, n_sides=self.tube_n_sides)
+            tube = line.tube(radius=radius, n_sides=self.tube_n_sides)
            actor = _add_mesh(
                plotter=self.plotter,
                mesh=tube,
@@ -0,0 +1,157 @@
+"""
+Filename: crossgroupbrainimage.py
+Description: Logic for the Cross-Group Brain & Image analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in Imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+from mne.io.base import BaseRaw
+
+import pandas as pd
+from pandas import DataFrame
+
+from flares import aggregate_fnirs_group_geometry, plot_2d_3d_contrasts_between_groups
+from src.shared.flaresbasewidget import CrossGroupUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "show_optodes",
+            "label": "Determine what is rendered above the brain. Valid values are 'sensors', 'labels', 'none', 'all'.",
+            "default": "all",
+            "type": str,
+        },
+        {
+            "key": "t_or_theta",
+            "label": "Specify if t values or theta values should be plotted. Valid values are 't', 'theta'",
+            "default": "theta",
+            "type": str,
+        },
+        {
+            "key": "show_text",
+            "label": "Display informative text on the top left corner about the contrast.",
+            "default": "True",
+            "type": bool,
+        },
+        {
+            "key": "brain_bounds",
+            "label": "Graph Upper/Lower Limit",
+            "default": "1.0",
+            "type": float,
+        },
+        {
+            "key": "is_3d",
+            "label": "Should we display the results in a 3D interactive window?",
+            "default": "True",
+            "type": bool,
+        }
+    ],
+}
+
+
+
+class CrossGroupBrainImageWidget(CrossGroupUIMixin, FlaresBaseWidget):
+    def __init__(
+        self,
+        haemo_dict: dict[str | Path, BaseRaw], 
+        df_ind_dict: dict[str, DataFrame],
+        design_matrix_dict: dict[str, DataFrame],
+        contrast_results_dict: dict[str, dict[str, Any]],
+        group_dict: dict[str, str],
+    ) -> None:
+        
+        super().__init__("CrossGroupBrainImage")
+        self.setWindowTitle(f"Cross-Group Brain & Image Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.df_ind_dict = df_ind_dict
+        self.design_matrix_dict = design_matrix_dict
+        self.contrast_results_dict = contrast_results_dict
+        self.group_dict = group_dict
+
+        self.setup_cross_group_ui(["0 (Contrast Image)"])
+
+
+    def process_request(self):
+              
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES)
+        if request is None:
+            return
+
+        (selected_event, file_paths_a, file_paths_b, all_selected_paths, selected_indexes, raw_params) = request
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        # Build group-level contrast DataFrames
+        def concat_group_contrasts(file_paths: list[str], event: str | None) -> pd.DataFrame:
+            group_df = pd.DataFrame()
+            for fp in file_paths:
+                print(f"Looking up contrast for: {fp}")
+                event_con_dict = self.contrast_results_dict.get(fp, {})
+                print("Available events for this file:", list(event_con_dict.keys()))
+                if event and event in event_con_dict:
+                    df = event_con_dict[event]
+                    print(f"Appending contrast df for event: {event}")
+                    group_df = pd.concat([group_df, df], ignore_index=True)
+                else:
+                    print(f"Event '{event}' not found for {fp}")
+            return group_df
+
+        print("Selected event:", selected_event)
+        print("File paths A:", file_paths_a)
+        print("File paths B:", file_paths_b)
+
+        contrast_df_a = concat_group_contrasts(file_paths_a, selected_event)
+        contrast_df_b = concat_group_contrasts(file_paths_b, selected_event)
+
+        print("contrast_df_a empty?", contrast_df_a.empty)
+        print("contrast_df_b empty?", contrast_df_b.empty)
+
+        all_raw_objs = [self.haemo_dict.get(fp) for fp in all_selected_paths if self.haemo_dict.get(fp)]
+        
+        if len(all_raw_objs) > 1:
+            processed_raw = aggregate_fnirs_group_geometry(all_raw_objs)
+        elif len(all_raw_objs) == 1 and all_raw_objs[0] is not None:
+            processed_raw = all_raw_objs[0].copy()
+            processed_raw.pick(picks="hbo")  # type: ignore
+        else:
+            processed_raw = None
+
+        # Visualizations
+        for idx in selected_indexes:
+            if idx == 0:
+                params = param_values.get(idx, {})
+                show_optodes = params.get("show_optodes", None)
+                t_or_theta = params.get("t_or_theta", None)
+                show_text = params.get("show_text", None)
+                brain_bounds = params.get("brain_bounds", None)
+                is_3d = params.get("is_3d", None)
+
+                if show_optodes is None or t_or_theta is None or show_text is None or brain_bounds is None or is_3d is None:
+                    print(f"Missing parameters for index {idx}, skipping.")
+                    continue
+
+                if not contrast_df_a.empty and not contrast_df_b.empty and processed_raw:
+
+                    plot_2d_3d_contrasts_between_groups(
+                        contrast_df_a,
+                        contrast_df_b,
+                        raw_haemo=processed_raw,
+                        group_a_name=self.group_a_dropdown.currentText(),
+                        group_b_name=self.group_b_dropdown.currentText(),
+                        is_3d=is_3d,
+                        t_or_theta=t_or_theta,
+                        show_optodes=show_optodes,
+                        show_text=show_text,
+                        brain_bounds=brain_bounds
+                    )
+            else:
+                print(f"No method defined for index {idx}")
@@ -0,0 +1,335 @@
+"""
+Filename: crossgroupstats.py
+Description: Cross-Group stats analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+import pandas as pd
+from pandas import DataFrame
+
+from mne.io.base import BaseRaw
+
+from flares import run_cross_group_contrast_analysis, run_cross_group_laterality_analysis, run_cross_group_second_level_analysis
+from src.shared.flaresbasewidget import CrossGroupUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "p_threshold",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "min_subjects",
+            "label": "Minimum number of participants to process",
+            "default": "3",
+            "type": int,
+        },
+        {
+            "key": "correction_method",
+            "label": "Correction method to utilize. Valid values are 'fdr_bh', 'None'",
+            "default": "fdr_bh",
+            "type": str,
+        },
+        {
+            "key": "target_chroma",
+            "label": "Which chroma to target. Valid values are 'hbo', 'hbr'",
+            "default": "hbo",
+            "type": str,
+        },
+        {
+            "key": "threshold_topo",
+            "label": "threshold_topo: TBD",
+            "default": False,
+            "type": bool,
+        }
+    ],
+    1: [
+        {
+            "key": "p_threshold",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "min_subjects",
+            "label": "Minimum number of participants to process",
+            "default": "3",
+            "type": int,
+        },
+        {
+            "key": "correction_method",
+            "label": "Correction method to utilize. Valid values are 'fdr_bh', 'None'",
+            "default": "None",
+            "type": str,
+        },
+        {
+            "key": "target_chroma",
+            "label": "Which chroma to target. Valid values are 'hbo', 'hbr'",
+            "default": "hbo",
+            "type": str,
+        },
+        {
+            "key": "roi_a",
+            "label": "ROI A (e.g. contralateral region name from regions.json)",
+            "default": [],
+            "type": list,
+        },
+        {
+            "key": "roi_b",
+            "label": "ROI B (e.g. ipsilateral region name from regions.json)",
+            "default": [],
+            "type": list,
+        }
+    ],
+    2: [
+        {
+            "key": "p_value",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "min_subjects",
+            "label": "Minimum number of participants to process",
+            "default": "3",
+            "type": int,
+        },
+        {
+            "key": "correction_method",
+            "label": "Correction method to utilize. Valid values are 'fdr_bh', 'None'",
+            "default": "fdr_bh",
+            "type": str,
+        },
+        {
+            "key": "target_chroma",
+            "label": "Which chroma to target. Valid values are 'hbo', 'hbr'",
+            "default": "hbo",
+            "type": str,
+        },
+        {
+            "key": "contrast_name",
+            "label": "Name of the contrast to use",
+            "default": [],
+            "type": list,
+        },
+    ],
+}
+        
+
+DESCRIPTION = """0. Raw ROI Comparison (run_cross_group_second_level_analysis)
+\nCompares one ROI's raw response magnitude between two independent groups (e.g. control vs. target) for a given condition, using Welch's t-test. A significant result means the two populations differ in this ROI's response magnitude for this condition. It does not tell you whether that difference is a real, localized, task-specific effect or a generic between-population difference - different overall vascular reactivity, arousal, or skull/scalp optical properties can produce the exact same statistical signature, and two independently recruited groups (especially patients vs. healthy controls) are considerably more likely to differ this way than two subsets of one study population.
+\nIf you expected a group difference and didn't find one, the most common cause is within-group heterogeneity swallowing a real between-group difference - a "target" population (e.g. a clinical group) is often more variable than a tightly-screened control group, and that added within-group variance directly weakens a between-group t-test even if the group means truly differ. Small per-group sample sizes compound this. It's also possible the true difference between your groups isn't in raw magnitude at all, but in spatial specificity or task-differentiation - which is exactly why the laterality and contrast-comparison methods exist alongside this one; a null result here doesn't rule those out.
+\n\n1. Laterality Comparison (run_cross_group_laterality_analysis)
+\nComputes each subject's own contralateral-minus-ipsilateral laterality index first, then compares those indices between the two groups with Welch's t-test. A significant result means the degree of spatial specificity/lateralization differs between the two populations - a claim about lateralization itself, harder to explain away as a generic population confound since person-level differences in overall reactivity largely cancel before the group comparison happens. It says nothing about overall response magnitude between groups (a group could have identical laterality but very different raw amplitude), and it only uses subjects who have both the contra and ipsi ROI valid, so it can lose subjects the raw-ROI comparison would have kept.
+\nNon-significance here has two likely sources, and it's worth distinguishing them. First, the same covariance issue from the within-group paired test applies across a whole group: if contra/ipsi responses aren't well-correlated within subjects, the laterality index itself is noisier than either ROI alone, and that added noise now has to clear a between-group test on top of it - a double power cost at small N. Second, and more informative if true: the groups may genuinely have similar lateralization but differ in overall magnitude instead, in which case this test correctly returns null while method 4 (raw comparison) should be the one to look at.
+\n\n2. Contrast Comparison (run_cross_group_contrast_analysis)
+\nCompares a jointly-fit task contrast (e.g. Task A minus Task B, estimated together within each subject's GLM), aggregated to ROI level, between two independent groups. A significant result means one group differentiates between the two tasks more or less than the other does, at this specific ROI - with systemic noise cancelled at the model-fitting stage, the same benefit that makes the within-group version of this method the strongest of that trio. As with the within-group version, it does not by itself say where a difference is localized unless you compare sign/pattern across multiple ROIs - opposite-signed group differences across regions point to something spatially specific, same-signed differences everywhere point to a diffuse/non-specific group difference (e.g. one group simply has stronger contrast responses across the whole head).
+\nIf this comes back non-significant despite an expected group difference, check first whether the underlying single-subject contrast estimates are noisy for either group - small per-group N means the joint contrast's precision depends on the same limited subject count as everything else, and a noisy input propagates all the way through the ROI aggregation. It's also possible for a real, localized sub-regional effect to get washed out by ROI averaging itself: if only part of an ROI's channels actually show the group difference while others don't, the inverse-variance-weighted average can dilute it toward null - in that case, a finer-grained ROI definition (splitting the region further) may recover the effect that a coarser ROI averaged away. Finally, FDR correction across every ROI tested reduces power exactly as it does everywhere else in this framework - a real but modest effect can fail to survive correction even when the raw p-value would have looked convincing on its own.
+\n\n
+\nWhy channels needed to be aggregated into ROIs: Testing every channel independently means paying a steep multiple-comparisons tax - with dozens of channels, FDR/Bonferroni correction demands very large effect sizes to call anything significant, and at small subject counts (n=5) essentially nothing survives even when a real, consistent effect exists. Collapsing channels into a handful of anatomically meaningful ROIs cuts the number of independent tests from a minimum of ~40 down to 2-8, which lets a genuinely present effect actually clear correction. It also matches the scientific question better: you have a hypothesis about regions (contralateral motor cortex, prefrontal cortex), not about individual source-detector pairs, so testing at the ROI level is testing the thing you actually believe in, using inverse-variance weighting so noisier channels contribute less to the region's combined estimate rather than diluting it equally.
+\nWhy some analyses needed contrasts instead of raw values: A single condition's GLM beta is only ever measured relative to the model's implicit intercept, and that intercept absorbs whatever's happening for the rest of the recording - including systemic physiology (blood pressure, arousal, general vascular reactivity) that rises during almost any active task, not just the one you care about. Testing a raw "vs. zero" value can't tell a real, localized neural response apart from that shared full-head noise. A contrast - either a within-subject spatial subtraction (ROI A minus ROI B) or a jointly-fit task contrast (Condition A minus Condition B, estimated together in one GLM) cancels out whatever's common to both halves of the subtraction, leaving something closer to the actual differential signal.
+\nWhy a minimum subject count is enforced: Every one of these tests is a t-test, and a t-test's ability to detect a real effect (its power) depends heavily on degrees of freedom - at n=5 (df=4), even a fairly large true effect can produce a middling p-value, and at n=2 (df=1) the test is barely meaningful at all regardless of the underlying data. The min_subjects floor exists to stop a channel or ROI from being silently tested (and potentially reported as significant or non-significant) on a sample too small for the resulting p-value to mean anything reliable - it's better to explicitly skip and flag an underpowered channel than to quietly produce a number that looks statistically legitimate but isn't backed by enough independent observations to trust."""
+
+
+class CrossGroupStatsWidget(CrossGroupUIMixin, FlaresBaseWidget):
+
+    def __init__(
+        self, 
+        haemo_dict: dict[str | Path, BaseRaw], 
+        cha_dict: dict[str, DataFrame],
+        df_ind_dict: dict[str, DataFrame],
+        design_matrix_dict: dict[str, DataFrame],
+        contrast_results_dict: dict[str, dict[str, Any]],
+        group_dict: dict[str, str],
+        json_location: str | Path
+    ) -> None:
+        
+        super().__init__("CrossGroupStats")
+        self.setWindowTitle(f"Cross-Group Stats Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.cha_dict = cha_dict
+        self.df_ind_dict = df_ind_dict
+        self.design_matrix_dict = design_matrix_dict
+        self.contrast_results_dict = contrast_results_dict
+        # self.group_dict = group_dict
+        self.json_location = json_location
+
+        self.setup_cross_group_ui(["0 (Raw ROI Comparison)", "1 (Laterality Comparison)", "2 (Contrast Comparison)",], placeholder_text=DESCRIPTION)
+        
+
+    def process_request(self):
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES, self.json_location, self.contrast_results_dict)
+        if request is None:
+            return
+
+        (selected_event, file_paths_a, file_paths_b, _, selected_indexes, raw_params) = request
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        valid_dfs = [df for df in self.df_ind_dict.values() if not df.empty]
+        if valid_dfs:
+            df_ind_combined = pd.concat(valid_dfs, ignore_index=True)
+        else:
+            df_ind_combined = pd.DataFrame()
+
+        valid_chas = [df for df in self.cha_dict.values() if not df.empty]
+        cha_combined = pd.concat(valid_chas, ignore_index=True) if valid_chas else pd.DataFrame()
+        
+        sample_path = file_paths_a[0]
+        p_haemo = self.haemo_dict.get(sample_path)
+
+        # Visualizations
+        for idx in selected_indexes:
+            if idx == 0:
+                params = param_values.get(idx, {})
+                p_threshold = params.get("p_threshold", 0.05)
+                min_subjects = params.get("min_subjects", 3)
+                correction_method = params.get("correction_method", "fdr_bh")
+                target_chroma = params.get("target_chroma", "hbo")
+                threshold_topo = params.get("threshold_topo", False)
+
+                run_cross_group_second_level_analysis(
+                    df_roi_all=df_ind_combined,  # Individual stats dataframe
+                    file_paths_a=file_paths_a,
+                    file_paths_b=file_paths_b,
+                    group_a_name=self.group_a_dropdown.currentText(),
+                    group_b_name=self.group_b_dropdown.currentText(),
+                    df_cha_all=cha_combined,
+                    raw_haemo=p_haemo,
+                    p_threshold=p_threshold,
+                    min_subjects=min_subjects,
+                    correction_method=correction_method,
+                    target_chroma=target_chroma,
+                    selected_event=selected_event,
+                    roi_config=self.json_location,
+                    threshold_topo=threshold_topo  # Shows the raw difference map (Unthresholded)
+                )
+            elif idx == 1:
+                if not selected_event:
+                    print("Laterality comparison requires a specific event/condition "
+                          "to be selected first.")
+                    continue
+ 
+                params = param_values.get(idx, {})
+                p_threshold = params.get("p_threshold", 0.05)
+                min_subjects = params.get("min_subjects", 3)
+                correction_method = params.get("correction_method", "None")
+                target_chroma = params.get("target_chroma", "hbo")
+                roi_a: str = params.get("roi_a", "").strip()
+                roi_b: str = params.get("roi_b", "").strip()
+ 
+                if not roi_a or not roi_b:
+                    print("Both a contralateral and ipsilateral ROI name must be specified.")
+                    continue
+
+                if correction_method == "None":
+                    correction_method = None
+ 
+                # Build each group's dataframe directly from the dict using
+                # the file-path lists as keys - no ID cleaning/matching needed.
+                def _build_group_df(
+                    file_paths: list[str], 
+                    dict_source: dict[str, DataFrame]
+                ) -> DataFrame:
+                    
+                    valid_dfs = [
+                        dict_source[fp] for fp in file_paths
+                        if fp in dict_source and not dict_source[fp].empty
+                    ]
+
+                    return pd.concat(valid_dfs, ignore_index=True) if valid_dfs else pd.DataFrame()
+ 
+
+                df_roi_a = _build_group_df(file_paths_a, self.df_ind_dict)
+                df_roi_b = _build_group_df(file_paths_b, self.df_ind_dict)
+ 
+                if df_roi_a.empty or df_roi_b.empty:
+                    print("No ROI data (df_ind) found for one or both groups.")
+                    continue
+ 
+                run_cross_group_laterality_analysis(
+                    df_roi_all_a=df_roi_a,
+                    df_roi_all_b=df_roi_b,
+                    roi_pairs=(roi_a, roi_b),
+                    condition=selected_event,
+                    group_a_name=self.group_a_dropdown.currentText(),
+                    group_b_name=self.group_b_dropdown.currentText(),
+                    target_chroma=target_chroma,
+                    min_subjects=min_subjects,
+                    p_threshold=p_threshold,
+                    correction_method=correction_method,
+                    roi_contra_label=roi_a,
+                    roi_ipsi_label=roi_b,
+                )
+ 
+            elif idx == 2:
+                params = param_values.get(idx, {})
+                p_threshold = params.get("p_threshold", 0.05)
+                min_subjects = params.get("min_subjects", 3)
+                correction_method = params.get("correction_method", "fdr_bh")
+                target_chroma = params.get("target_chroma", "hbo")
+                contrast_name = params.get("contrast_name", "")
+ 
+                if not contrast_name:
+                    print("A contrast name must be specified.")
+                    continue
+ 
+                # Build each group's channel-level contrast dataframe
+                # directly from contrast_results_dict, keyed by file path -
+                # same dict-key approach as the laterality patch, avoids
+                # any ID-string matching.
+                def _build_group_contrast_df(
+                    file_paths: list[str],
+                    contrast_dict: dict[str, dict[str, pd.DataFrame]],
+                    name: str,
+                ) -> pd.DataFrame:
+                    
+                    all_rows: list[DataFrame] = []
+                    for fp in file_paths:
+                        condition_dfs = contrast_dict.get(fp)
+                        if condition_dfs is None:
+                            print(f"   [MISSING] '{fp}' not found in contrast_results.")
+                            continue
+                        if name in condition_dfs:
+                            df = condition_dfs[name].copy()
+                            df["ID"] = fp
+                            df["contrast_name"] = name
+                            all_rows.append(df)
+                        else:
+                            print(f"   [MISSING CONTRAST] '{name}' not available for '{fp}'.")
+                    return pd.concat(all_rows, ignore_index=True) if all_rows else pd.DataFrame()
+ 
+                df_contrasts_a = _build_group_contrast_df(file_paths_a, self.contrast_results_dict, contrast_name)
+                df_contrasts_b = _build_group_contrast_df(file_paths_b, self.contrast_results_dict, contrast_name)
+ 
+                if df_contrasts_a.empty or df_contrasts_b.empty:
+                    print("No contrast data found for one or both groups.")
+                    continue
+ 
+                run_cross_group_contrast_analysis(
+                    df_contrasts_a=df_contrasts_a,
+                    df_contrasts_b=df_contrasts_b,
+                    contrast_name=contrast_name,
+                    roi_json_path=self.json_location,
+                    group_a_name=self.group_a_dropdown.currentText(),
+                    group_b_name=self.group_b_dropdown.currentText(),
+                    target_chroma=target_chroma,
+                    min_subjects=min_subjects,
+                    p_threshold=p_threshold,
+                    correction_method=correction_method,
+                )
+ 
+            else:
+                print("no")
@@ -0,0 +1,196 @@
+"""
+Filename: exporttocsv.py
+Description: Logic for the Export To CSV analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+import os
+from pathlib import Path
+from typing import Any
+
+# External library imports
+from pandas import DataFrame
+
+from mne.io.base import BaseRaw
+
+from PySide6.QtWidgets import QFileDialog, QMessageBox
+
+from flares import sparks_csv_export
+from src.shared.flaresbasewidget import CSVUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+class ExportToCSVWidget(CSVUIMixin, FlaresBaseWidget):
+    def __init__(
+        self, 
+        haemo_dict: dict[str | Path, BaseRaw], 
+        cha_dict: dict[str, DataFrame],
+        df_ind_dict: dict[str, DataFrame],
+        design_matrix_dict: dict[str, DataFrame],
+        contrast_results_dict: dict[str, dict[str, Any]],
+        group_dict: dict[str, str],
+        config_dict: dict[str, str],
+    ) -> None:
+        
+        super().__init__("ExportToCSV")
+        self.setWindowTitle(f"Export To CSV Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.cha_dict = cha_dict
+        # self.df_ind = df_ind_dict
+        # self.design_matrix = design_matrix_dict
+        # self.contrast_results_dict = contrast_results_dict
+        # self.group = group_dict
+        self.config_dict = config_dict
+        
+        self.setup_csv_ui(["0 (Export Data to CSV)", "1 (CSV for SPARKS)", "2 (Export Configuration to CSV)", "3 (Paragraph of Configuration)"])
+        
+    
+    def process_request(self):
+        selected_display_names = self._get_checked_items(self.participant_dropdown)
+        selected_file_paths: list[str] = []
+        for display_name in selected_display_names:
+            for fp, short_label in self.participant_map.items():
+                expected_display = f"{short_label} ({os.path.basename(fp)})"
+                if display_name == expected_display: 
+                    selected_file_paths.append(fp)
+                    break
+
+        selected_indexes = [
+            int(s.split(" ")[0]) for s in self._get_checked_items(self.image_index_dropdown)
+        ]
+
+        if not selected_file_paths or not selected_indexes:
+            QMessageBox.warning(self, "Selection Missing", "Please select at least one participant and one export type.")
+            return
+
+        output_dir = QFileDialog.getExistingDirectory(self, "Select Output Folder for CSV Exports")
+        
+        if not output_dir:
+            print("Export cancelled: No folder selected.")
+            return
+
+        success_count = 0
+
+        # Pass the necessary arguments to each method
+        for file_path in selected_file_paths:
+            base_filename = os.path.splitext(os.path.basename(file_path))[0]
+            haemo_obj = self.haemo_dict.get(file_path)
+            if haemo_obj is None:
+                continue
+
+            cha = self.cha_dict.get(file_path)
+
+            for idx in selected_indexes:
+                try:
+                    if idx == 0:
+                        save_path = os.path.join(output_dir, f"{base_filename}_exported.csv")
+                        if cha is not None:
+                            cha.to_csv(save_path)
+                            success_count += 1
+
+                    elif idx == 1:
+                        # SPARKS Export
+                        save_path = os.path.join(output_dir, f"{base_filename}_sparks.csv")
+                        sparks_csv_export(haemo_obj, save_path)
+                        success_count += 1
+
+                    elif idx == 2:
+                        formatted_data = {
+                            os.path.basename(path.replace("\\", "/")): inner_dict
+                            for path, inner_dict in self.config_dict.items()
+                        }
+                        df = DataFrame(formatted_data)
+                        df.index.name = "Parameter"
+                        save_path = os.path.join(output_dir, f"{APP_NAME}_configuration.csv")
+                        df.to_csv(save_path)
+                        success_count += 1
+
+                    elif idx == 3:
+                        first_params = next(iter(self.config_dict.values()))
+                        magic_string = self.gen_magic_str(first_params)
+                        self.placeholder_label.setText(magic_string)
+
+                    else:
+                        print(f"No method defined for index {idx}")
+                
+                except Exception as e:
+                    print(f"Failed to export {file_path} (Type {idx}): {e}")
+
+        # 4. Final Notification
+        if success_count > 0:
+            QMessageBox.information(self, "Export Complete", f"Successfully saved {success_count} CSV files to:\n{output_dir}")
+            
+            # # If SPARKS export was included, show the Event Window once at the end
+            # if 1 in selected_indexes:
+            #     win = UpdateEventsWindow(
+            #         parent=self,
+            #         mode=EventUpdateMode.WRITE_JSON,
+            #         caller="Video Alignment Tool"
+            #     )
+            #     win.show()
+
+
+    def gen_magic_str(self, all_params):
+            
+            magic_str = "To start, the data was loaded into the application. "
+            if all_params['DOWNSAMPLE']:
+                magic_str += f"The data was downsampled to {all_params['DOWNSAMPLE_FREQUENCY']}hz. "
+            else:
+                magic_str += "The data was not downsampled and was retained at its original sampling frequency. "
+    
+            if all_params['TRIM']:
+                magic_str += f"The data was then trimmed to only keep {all_params['SECONDS_TO_KEEP']} seconds before the first event, as the earlier data with no events would not be needed. "
+            else:
+                magic_str += "The data was not trimmed and was retained at its original length. "
+    
+            if all_params['OPTODE_PLACEMENT']:
+                magic_str += f"A visualization check of the optode locations in 3D space was performed to ensure that they were at the correct location. "
+    
+            if all_params['SHORT_CHANNELS']:
+                magic_str += f"A short channel(s) was specified with the maximum length of a short channel being {all_params['SHORT_CHANNELS_THRESHOLD']} metres. Channels that were over this distance but under {all_params['LONG_CHANNELS_THRESHOLD']} metres were retained. "
+            else:
+                magic_str += f"No short channel was specified. Channels between the lengths of {all_params['SHORT_CHANNELS_THRESHOLD']} and {all_params['LONG_CHANNELS_THRESHOLD']} meters were used with all other channles being discarded. "
+    
+            if all_params['HEART_RATE']:
+                magic_str += f"The heart rate of the participant was attempted to be calculated. {all_params['SECONDS_TO_STRIP_HR']} seconds were ignored from the start of the file to avoid motion artifacts. "
+                magic_str += f"The heart rate had hard limits of {all_params['MAX_LOW_HR']} to {all_params['MAX_HIGH_HR']} and was smoothed across {all_params['SMOOTHING_WINDOW_HR']} samples. "
+            else:
+                magic_str += "The heart rate of the participants was not attempted to be calculated. "
+    
+            if all_params['SCI']:
+                magic_str += f"The Scalp Coupling Index was calculated over {all_params['SCI_TIME_WINDOW']} second windows. The threshold value was {all_params['SCI_THRESHOLD']}. "
+            else:
+                magic_str += "Scalp Coupling Index was not used. "
+    
+            if all_params['SNR']:
+                magic_str += f"The Signal to Noise Ratio was calculated. The threshold value was set to {all_params['SNR_THRESHOLD']}db. "
+            else:
+                magic_str += "The Signal to Noise Ratio was not used. "
+    
+            if all_params['PSP']:
+                magic_str += f"Peak Spectral Power was calculated over {all_params['PSP_TIME_WINDOW']} second windows. The threshold value was {all_params['PSP_THRESHOLD']}. "
+            else:
+                magic_str += "Peak Spectral Power was not used. "
+    
+            if all_params['COEFF_VAR']:
+                magic_str += f"The Coefficient of Variation was calculated. The threshold value was set to {all_params['COEFF_VAR_THRESHOLD']}. "
+            else:
+                magic_str += "The Coefficient of Variation was not used. "
+    
+            if all_params['MAD']:
+                magic_str += f"Median Absolute Deviation was calculated. The threshold value was set to {all_params['MAD_THRESHOLD']}. "
+            else:
+                magic_str += "Median Absolute Deviation was not used. "
+    
+            if all_params['PSD_NOISE']:
+                magic_str += f"Power Spectral Density Noise was calculated with a target frequency divisor of {all_params['TARGET_FREQ_DIV']} and a decibal limit of {all_params['DB_LIMIT']}. "
+            else:
+                magic_str += f"Power Spectral Density Noise was not used. "
+    
+            magic_str += "More coming soon."
+
+            return magic_str
@@ -0,0 +1,221 @@
+"""
+Filename: intergroupbrainimage.py
+Description: Logic for the Inter-Group Brain & Image analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in Imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+import pandas as pd
+from pandas import DataFrame
+
+from mne import Annotations
+from mne.io.base import BaseRaw
+
+from flares import aggregate_fnirs_group_geometry, plot_fir_model_results, brain_3d_visualization
+from src.shared.flaresbasewidget import InterGroupUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+from mne.io import BaseRaw
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "lower_bound",
+            "label": "Lower bound + <description>",
+            "default": "-0.3",
+            "type": float,  # specify int here
+        },
+        {
+            "key": "upper_bound",
+            "label": "Upper bound + <description>",
+            "default": "0.8",
+            "type": float,  # specify int here
+        }
+    ],
+    1: [
+        {
+            "key": "p_value",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "graph_bounds",
+            "label": "Graph Upper/Lower Limit",
+            "default": "3.0",
+            "type": float,
+        }
+    ],
+    2: [
+        {
+            "key": "show_optodes",
+            "label": "Determine what is rendered above the brain. Valid values are 'sensors', 'labels', 'none', 'all'.",
+            "default": "all",
+            "type": str,
+        },
+        {
+            "key": "t_or_theta",
+            "label": "Specify if t values or theta values should be plotted. Valid values are 't', 'theta'",
+            "default": "theta",
+            "type": str,
+        },
+        {
+            "key": "show_text",
+            "label": "Display informative text on the top left corner. THIS DOES NOT WORK AND SHOULD BE LEFT AT FALSE",
+            "default": "False",
+            "type": bool,
+        },
+        {
+            "key": "brain_bounds",
+            "label": "Graph Upper/Lower Limit",
+            "default": "1.0",
+            "type": float,
+        }
+    ],
+}
+
+
+
+class InterGroupBrainImageWidget(InterGroupUIMixin, FlaresBaseWidget):
+    def __init__(
+        self,
+        haemo_dict: dict[str | Path, BaseRaw], 
+        cha_dict: dict[str, DataFrame],
+        df_ind_dict: dict[str, DataFrame],
+        design_matrix_dict: dict[str, DataFrame],
+        contrast_results_dict: dict[str, dict[str, Any]],
+        group_dict: dict[str, str]
+    ) -> None:
+
+        super().__init__("InterGroupBrainImage")
+        self.setWindowTitle(f"Inter-Group Brain & Image Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.cha_dict = cha_dict
+        self.df_ind_dict = df_ind_dict
+        self.design_matrix_dict = design_matrix_dict
+        self.contrast_results_dict = contrast_results_dict
+        # self.group_dict = group_dict
+               
+        self.setup_inter_group_ui(["0 (GLM Results)", "1 (Significance)", "2 (Brain Activity Visualization)",])
+
+
+    def process_request(self):
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES)
+        if request is None:
+            return
+
+        (selected_event, selected_file_paths, selected_indexes, raw_params) = request
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        all_cha = pd.DataFrame()
+        for file_path in selected_file_paths:
+            haemo_obj = self.haemo_dict.get(file_path)
+
+            if haemo_obj is None:
+                continue
+
+            if selected_event:
+                raw_annotations = getattr(haemo_obj, "annotations", None)
+                
+                if raw_annotations is not None:
+                    annotations = cast(Annotations, raw_annotations)
+                    descriptions = cast(list[str], list(annotations.description))
+                    participant_events: set[str] = set(descriptions)
+                else:
+                    participant_events: set[str] = set()
+                    
+                if selected_event not in participant_events:
+                    print(f"Skipping {self.participant_map[file_path]}: Event '{selected_event}' not found.")
+                    continue
+            
+            cha_df = self.cha_dict.get(file_path)
+            if cha_df is not None:
+                all_cha = pd.concat([all_cha, cha_df], ignore_index=True)
+
+        # Pass the necessary arguments to each method
+        file_path = selected_file_paths[0]
+        p_haemo = self.haemo_dict.get(file_path)
+        p_design_matrix = self.design_matrix_dict.get(file_path)
+
+        df_group = pd.DataFrame()
+
+        if selected_file_paths:
+            for file_path in selected_file_paths:
+                df = self.df_ind_dict.get(file_path)
+                if df is not None:
+                    df_group = pd.concat([df_group, df], ignore_index=True)
+                
+
+        for idx in selected_indexes:
+            if idx == 0:
+                params = param_values.get(idx, {})
+                lower_bound = params.get("lower_bound", None)
+                upper_bound = params.get("upper_bound", None)
+
+                if lower_bound is None or upper_bound is None:
+                    print(f"Missing parameters for index {idx}, skipping.")
+                    continue
+
+
+                plot_fir_model_results(df_group, p_haemo, p_design_matrix, selected_event, lower_bound, upper_bound)
+
+            elif idx == 1:
+                params = param_values.get(idx, {})
+                p_val = params.get("p_value", None)
+                graph_bounds = params.get("graph_bounds", None)
+
+                if p_val is None or graph_bounds is None:
+                    print(f"Missing parameters for index {idx}, skipping.")
+                    continue
+
+                all_contrasts: list[DataFrame] = []
+                for fp in selected_file_paths:
+                    condition_dfs = self.contrast_results_dict.get(fp, {})
+                    if selected_event in condition_dfs:
+                        df = condition_dfs[selected_event].copy()
+                        df["ID"] = fp
+                        all_contrasts.append(df)
+
+                if not all_contrasts:
+                    print("No contrast data found for selected participants and event.")
+                    return
+
+                # TODO: look at intergroupstats and figure out what to do 
+                _ = pd.concat(all_contrasts, ignore_index=True)
+                #flares.run_second_level_analysis(df_contrasts, p_haemo, p_val, graph_bounds)
+
+            elif idx == 2:
+                params = param_values.get(idx, {})
+                show_optodes = params.get("show_optodes", None)
+                t_or_theta = params.get("t_or_theta", None)
+                show_text = params.get("show_text", None)
+                brain_bounds = params.get("brain_bounds", None)
+
+                if show_optodes is None or t_or_theta is None or show_text is None or brain_bounds is None:
+                    print(f"Missing parameters for index {idx}, skipping.")
+                    continue
+
+                all_raw_objs = [self.haemo_dict.get(fp) for fp in selected_file_paths if self.haemo_dict.get(fp)]
+                
+                if len(all_raw_objs) > 1:
+                    processed_raw = aggregate_fnirs_group_geometry(all_raw_objs)
+                elif len(all_raw_objs) == 1 and all_raw_objs[0] is not None:
+                    processed_raw = all_raw_objs[0].copy()
+                    processed_raw.pick(picks="hbo")  # type: ignore
+                else:
+                    processed_raw = None
+
+                brain_3d_visualization(processed_raw, all_cha, selected_event, t_or_theta=t_or_theta, show_optodes=show_optodes, show_text=show_text, brain_bounds=brain_bounds)
+                    
+            elif idx == 3:
+                pass
+
+            else:
+                print(f"No method defined for index {idx}")
@@ -0,0 +1,84 @@
+"""
+Filename: intergroupfunctionalconnectivity.py
+Description: Logic for the Inter-Group Functional Connectivity analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+from PySide6.QtWidgets import QMessageBox
+
+from mne.io.base import BaseRaw
+
+from flares import run_group_functional_connectivity
+from src.shared.flaresbasewidget import InterGroupUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "n_lines",
+            "label": "<Description>",
+            "default": "20",
+            "type": int,
+        },
+        {
+            "key": "vmin",
+            "label": "<Description>",
+            "default": "0.9",
+            "type": float,
+        },
+    ],
+}
+
+
+
+class InterGroupFunctionalConnectivityWidget(InterGroupUIMixin, FlaresBaseWidget):
+    def __init__(
+        self,
+        haemo_dict: dict[str | Path, BaseRaw],
+        group_dict: dict[str, str],
+        config_dict: dict[str, str]
+    ) -> None:
+        
+        super().__init__("InterGroupFunctionalConnectivity")
+        self.setWindowTitle(f"Inter-Group Functional Connectivity Viewer [BETA] - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        #self.group_dict = group_dict
+        self.config_dict = config_dict
+
+        QMessageBox.warning(self, f"Warning - {APP_NAME.upper()}", f"Functional Connectivity is still in development and the results should currently be taken with a grain of salt. "
+                    "By clicking OK, you accept that the images generated may not be factual.")
+
+        self.setup_inter_group_ui(["0 (Betas)",])
+
+
+    def process_request(self):
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES)
+        if request is None:
+            return
+
+        (selected_event, selected_file_paths, selected_indexes, raw_params) = request   
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+            
+        for idx in selected_indexes:
+            if idx == 0:
+                params = param_values.get(idx, {})
+                n_lines = params.get("n_lines", None)
+                vmin = params.get("vmin", None)
+
+                if n_lines is None or vmin is None:
+                    print(f"Missing parameters for index {idx}, skipping.")
+                    continue
+                run_group_functional_connectivity(self.haemo_dict, self.config_dict, selected_file_paths, selected_event, 50, 0.5)            
+
+            else:
+                print(f"No method defined for index {idx}")
@@ -0,0 +1,396 @@
+"""
+Filename: intergroupstats.py
+Description: Logic for the Inter-Group Stats analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+import pandas as pd
+from pandas import DataFrame
+
+from mne import Annotations
+from mne.io.base import BaseRaw
+
+from flares import run_roi_paired_contrast_analysis, run_roi_second_level_analysis, aggregate_channel_contrasts_to_roi
+from src.shared.flaresbasewidget import InterGroupUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "p_threshold",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "min_subjects",
+            "label": "Minimum number of participants to process",
+            "default": "5",
+            "type": int,
+        },
+        {
+            "key": "correction_method",
+            "label": "Correction method to utilize. Valid values are 'fdr_bh', 'None'",
+            "default": "fdr_bh",
+            "type": str,
+        },
+        {
+            "key": "target_chroma",
+            "label": "Which chroma to target. Valid values are 'hbo', 'hbr'",
+            "default": "hbo",
+            "type": str,
+        },
+        {
+            "key": "graph_bounds",
+            "label": "Graph Upper/Lower Limit",
+            "default": "0.0",
+            "type": float,
+        }
+    ],
+    1: [
+        {
+            "key": "p_threshold",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "min_subjects",
+            "label": "Minimum number of participants to process",
+            "default": "5",
+            "type": int,
+        },
+        {
+            "key": "correction_method",
+            "label": "Correction method to utilize. Valid values are 'fdr_bh', 'None'",
+            "default": "None",
+            "type": str,
+        },
+        {
+            "key": "target_chroma",
+            "label": "Which chroma to target. Valid values are 'hbo', 'hbr'",
+            "default": "hbo",
+            "type": str,
+        },
+        {
+            "key": "roi_a",
+            "label": "ROI A (e.g. contralateral region name from regions.json)",
+            "default": [],
+            "type": list,
+        },
+        {
+            "key": "roi_b",
+            "label": "ROI B (e.g. ipsilateral region name from regions.json)",
+            "default": [],
+            "type": list,
+        }
+    ],
+    2: [
+        {
+            "key": "p_value",
+            "label": "Significance threshold P-value (e.g. 0.05)",
+            "default": "0.05",
+            "type": float,
+        },
+        {
+            "key": "min_subjects",
+            "label": "Minimum number of participants to process",
+            "default": "5",
+            "type": int,
+        },
+        {
+            "key": "correction_method",
+            "label": "Correction method to utilize. Valid values are 'fdr_bh', 'None'",
+            "default": "fdr_bh",
+            "type": str,
+        },
+        {
+            "key": "target_chroma",
+            "label": "Which chroma to target. Valid values are 'hbo', 'hbr'",
+            "default": "hbo",
+            "type": str,
+        },
+        {
+            "key": "contrast_name",
+            "label": "Name of the contrast to use",
+            "default": [],
+            "type": list,
+        },
+        {
+            "key": "weighted",
+            "label": "Use inverse-variance weighting to minimize noisy channels",
+            "default": True,
+            "type": bool,
+        },
+        {
+            "key": "graph_bounds",
+            "label": "Graph Upper/Lower Limit",
+            "default": "0.0",
+            "type": float,
+        },
+    ],
+}
+
+
+DESCRIPTION = """0. ROI vs. Zero (run_roi_second_level_analysis)
+\nTests whether one ROI's response during one condition reliably differs from zero across subjects - a one-sample t-test on each subject's ROI-averaged theta. A significant result means the region's signal during this condition is consistently non-zero across your sample, not just noise. It does not tell you whether the response is localized/specific to this region, or whether it reflects real neural activity versus systemic physiology (blood pressure, arousal) shared across the whole head during any active task - a single-condition "vs. zero" test can't distinguish those two explanations on its own.
+\nIf you expected significance here and didn't get it, likely causes include: the sample size is simply small relative to between-subject variability in true response magnitude or HRF shape (individual differences in timing/amplitude inflate the variance a t-test divides by); the ROI's channel composition differs slightly across subjects (missing channels get down-weighted or excluded from the inverse-variance average, diluting a real signal); FDR correction across many ROIs is suppressing a modest true effect that would clear an uncorrected threshold; or the condition itself may not reliably engage this region the way you assumed (worth checking the single-subject/individual-level results for this ROI before concluding the group effect isn't there).
+\n\n1. Paired ROI Contrast (run_roi_paired_contrast_analysis)
+\nFor one condition, subtracts each subject's ROI_A response from their ROI_B response, then tests whether that per-subject difference is reliably non-zero. A significant result is a genuine spatial contrast - the two regions respond differently from each other during this specific condition, with shared systemic noise partially cancelling in the subtraction. It says nothing about whether the condition produced meaningful activity at all (only a relative difference between two places), and its power depends entirely on ROI_A and ROI_B varying together across subjects - an assumption that isn't guaranteed.
+\nIf this test underperforms a plain ROI-vs-zero result, which can occur, the most likely explanation is that ROI_A and ROI_B's noise isn't well-correlated across your subjects. The math is variance(A - B) = variance(A) + variance(B) - 2·covariance(A,B): subtraction only helps when the shared/systemic component is large relative to independent noise in each region. If the two regions are picking up largely independent noise sources (motion artifact affecting one side more, different channel quality, etc.), subtracting adds variance rather than removing it, and can turn a detectable single-ROI effect into an underpowered paired one. Small sample size makes this worse, since the covariance itself is poorly estimated with few subjects.
+\n\n2. Joint Contrast, ROI-Aggregated (aggregate_channel_contrasts_to_roi + one-sample test)
+\nUses a contrast fit jointly within each subject's GLM (Condition A minus Condition B, estimated together), then aggregates that per-channel contrast to ROI level using inverse-variance weighting, and tests it against zero across subjects. A significant result means the two conditions produce reliably different responses at this ROI, with systemic noise largely cancelled at the model-fitting stage itself - the most statistically efficient of the three within-group methods, since the correlation between conditions is handled natively rather than inferred afterward. It does not tell you where the difference is localized on its own - for that, compare the sign/pattern across multiple ROIs: opposite signs across regions indicates a real, spatially-specific effect, while the same sign everywhere suggests diffuse/systemic noise rather than localized activity (as seen when comparing a real task-vs-task contrast against a task-vs-inert-marker contrast).
+\nIf this comes back non-significant despite expecting an effect, first check whether the two conditions are actually similar enough in their neural engagement of this ROI that a small or genuinely near-zero contrast is the correct answer - not every ROI should differentiate every pair of tasks, and a null result here can be the right result. Beyond that: FDR correction across every ROI in your regions file can suppress a real but modest contrast; the inverse-variance weighting can be destabilized if a few channels within the ROI have very noisy or near-zero t-statistics (their standard error estimate becomes huge or unstable); and - as always - small subject counts limit the achievable degrees of freedom regardless of how clean the underlying per-channel estimates are.
+\n\n
+\nWhy channels needed to be aggregated into ROIs: Testing every channel independently means paying a steep multiple-comparisons tax - with dozens of channels, FDR/Bonferroni correction demands very large effect sizes to call anything significant, and at small subject counts (n=5) essentially nothing survives even when a real, consistent effect exists. Collapsing channels into a handful of anatomically meaningful ROIs cuts the number of independent tests from a minimum of ~40 down to 2-8, which lets a genuinely present effect actually clear correction. It also matches the scientific question better: you have a hypothesis about regions (contralateral motor cortex, prefrontal cortex), not about individual source-detector pairs, so testing at the ROI level is testing the thing you actually believe in, using inverse-variance weighting so noisier channels contribute less to the region's combined estimate rather than diluting it equally.
+\nWhy some analyses needed contrasts instead of raw values: A single condition's GLM beta is only ever measured relative to the model's implicit intercept, and that intercept absorbs whatever's happening for the rest of the recording - including systemic physiology (blood pressure, arousal, general vascular reactivity) that rises during almost any active task, not just the one you care about. Testing a raw "vs. zero" value can't tell a real, localized neural response apart from that shared full-head noise. A contrast - either a within-subject spatial subtraction (ROI A minus ROI B) or a jointly-fit task contrast (Condition A minus Condition B, estimated together in one GLM) cancels out whatever's common to both halves of the subtraction, leaving something closer to the actual differential signal.
+\nWhy a minimum subject count is enforced: Every one of these tests is a t-test, and a t-test's ability to detect a real effect (its power) depends heavily on degrees of freedom - at n=5 (df=4), even a fairly large true effect can produce a middling p-value, and at n=2 (df=1) the test is barely meaningful at all regardless of the underlying data. The min_subjects floor exists to stop a channel or ROI from being silently tested (and potentially reported as significant or non-significant) on a sample too small for the resulting p-value to mean anything reliable - it's better to explicitly skip and flag an underpowered channel than to quietly produce a number that looks statistically legitimate but isn't backed by enough independent observations to trust."""
+
+
+class InterGroupStatsWidget(InterGroupUIMixin, FlaresBaseWidget):
+    
+    def __init__(
+        self, 
+        haemo_dict: dict[str | Path, BaseRaw], 
+        cha_dict: dict[str, DataFrame],
+        df_ind_dict: dict[str, DataFrame],
+        design_matrix_dict: dict[str, DataFrame],
+        contrast_results_dict: dict[str, dict[str, Any]],
+        group_dict: dict[str, str],
+        json_location: str | Path
+    ) -> None:
+        
+        super().__init__("InterGroupStats")
+        self.setWindowTitle(f"Inter-Group Stats Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.cha_dict = cha_dict
+        self.df_ind_dict = df_ind_dict
+        self.design_matrix_dict = design_matrix_dict
+        self.contrast_results_dict = contrast_results_dict
+        self.group_dict = group_dict
+        self.json_location = json_location
+
+        self.setup_inter_group_ui(["0 (ROI vs. Zero)", "1 (Paired ROI Contrast)", "2 (Joint Contrast, ROI-Aggregated)"], placeholder_text=DESCRIPTION)
+
+
+    def process_request(self):
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES, self.json_location, self.contrast_results_dict)
+        if request is None:
+            return
+
+        (selected_event, selected_file_paths, selected_indexes, raw_params) = request     
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        all_cha = DataFrame()
+        for file_path in selected_file_paths:
+            haemo_obj = self.haemo_dict.get(file_path)
+
+            if haemo_obj is None:
+                continue
+
+            if selected_event:
+                raw_annotations = getattr(haemo_obj, "annotations", None)
+                
+                if raw_annotations is not None:
+                    annotations = cast(Annotations, raw_annotations)
+                    descriptions = cast(list[str], list(annotations.description))
+                    participant_events: set[str] = set(descriptions)
+                else:
+                    participant_events: set[str] = set()
+                    
+                if selected_event not in participant_events:
+                    print(f"Skipping {self.participant_map[file_path]}: Event '{selected_event}' not found.")
+                    continue
+
+
+            
+            cha_df = self.cha_dict.get(file_path)
+            if cha_df is not None:
+                all_cha = pd.concat([all_cha, cha_df], ignore_index=True)
+
+        file_path = selected_file_paths[0]
+        p_haemo = self.haemo_dict.get(file_path)
+
+        # Concatenate individual ROI stats (df_ind) for all chosen subjects
+        df_group = DataFrame()
+        if selected_file_paths:
+            for file_path in selected_file_paths:
+                df = self.df_ind_dict.get(file_path)
+                if df is not None:
+                    df_group = pd.concat([df_group, df], ignore_index=True)
+
+        for idx in selected_indexes:
+            if idx == 0:
+                params = param_values.get(idx, {})
+                p_threshold = params.get("p_threshold", 0.05)
+                min_subjects = params.get("min_subjects", 5)
+                correction_method = params.get("correction_method", "fdr_bh")
+                target_chroma = params.get("target_chroma", "hbo")
+                graph_bounds = params.get("graph_bounds", 0.0)
+
+                if correction_method == "None":
+                    correction_method = None
+
+                if df_group.empty:
+                    print("No ROI data (df_ind) found for selected participants.")
+                    continue
+
+                # Filter down to the selected experimental event/condition
+                if selected_event:
+                    if 'Condition' in df_group.columns:
+                        df_filtered = df_group[df_group['Condition'] == selected_event]
+                    else:
+                        print("Warning: 'Condition' column not found in ROI data.")
+                        df_filtered = df_group
+                else:
+                    df_filtered = df_group
+
+                if df_filtered.empty:
+                    print(f"No ROI data matches the condition '{selected_event}'.")
+                    continue
+
+                all_cha_filtered = DataFrame()
+                if not all_cha.empty:
+                    if selected_event and 'Condition' in all_cha.columns:
+                        all_cha_filtered = all_cha[all_cha['Condition'] == selected_event]
+                    else:
+                        all_cha_filtered = all_cha
+
+
+                run_roi_second_level_analysis(
+                    df_roi_all=df_filtered,
+                    df_cha_all=all_cha_filtered,
+                    raw_haemo=p_haemo,
+                    p_threshold=p_threshold,
+                    min_subjects=min_subjects,
+                    correction_method=correction_method,
+                    target_chroma=target_chroma,
+                    graph_bounds=graph_bounds if graph_bounds > 0.0 else None,
+                    roi_config=self.json_location
+                )
+
+            elif idx == 1:
+                params = param_values.get(idx, {})
+                p_threshold = params.get("p_threshold", 0.05)
+                min_subjects = params.get("min_subjects", 5)
+                correction_method = params.get("correction_method", "None")
+                target_chroma = params.get("target_chroma", "hbo")
+                roi_a = params.get("roi_a", "").strip()
+                roi_b = params.get("roi_b", "").strip()
+            
+                if not selected_event:
+                    print("Paired ROI contrast requires a specific event/condition "
+                          "to be selected - pick one from the Event dropdown first.")
+                    continue
+ 
+                if df_group.empty:
+                    print("No ROI data (df_ind) found for selected participants.")
+                    continue
+ 
+                if correction_method == "None":
+                    correction_method = None
+ 
+                if not roi_a or not roi_b:
+                    print("Both ROI A and ROI B must be specified.")
+                    continue
+                
+                print(min_subjects)
+                run_roi_paired_contrast_analysis(
+                    df_roi_all=df_group,
+                    roi_pairs=(roi_a, roi_b),
+                    condition=selected_event,
+                    target_chroma=target_chroma,
+                    min_subjects=min_subjects,
+                    p_threshold=p_threshold,
+                    correction_method=correction_method,
+                    roi_a_label=roi_a,
+                    roi_b_label=roi_b,
+                )
+
+            elif idx == 2:
+                params = param_values.get(idx, {})
+                p_threshold = params.get("p_threshold", 0.05)
+                min_subjects = params.get("min_subjects", 5)
+                correction_method = params.get("correction_method", "fdr_bh")
+                target_chroma = params.get("target_chroma", "hbo")
+                contrast_name = params.get("contrast_name", "")
+                weighted = params.get("weighted", True)
+                graph_bounds = params.get("graph_bounds", 0.0)
+
+                if not selected_event:
+                    print("Joint contrast ROI analysis requires a specific contrast "
+                          "to be selected from the Event dropdown first.")
+                    continue
+
+                if not contrast_name:
+                    print("Contrast name must be specified.")
+                    continue
+
+
+                all_contrasts: list[DataFrame] = []
+                for fp in selected_file_paths:
+                    condition_dfs = self.contrast_results_dict.get(fp)
+                    if condition_dfs is None:
+                        print(f"   [MISSING] '{fp}' not found in contrast_results.")
+                        continue
+                    if contrast_name in condition_dfs:
+                        df = condition_dfs[contrast_name].copy()
+                        df["ID"] = fp
+                        df["contrast_name"] = contrast_name
+                        all_contrasts.append(df)
+                    else:
+                        print(f"   [MISSING CONTRAST] '{contrast_name}' not "
+                              f"available for {self.participant_map.get(fp, fp)}.")
+ 
+                if not all_contrasts:
+                    print(f"No contrast data found for '{contrast_name}' "
+                          f"across selected participants.")
+                    continue
+ 
+                df_contrasts = pd.concat(all_contrasts, ignore_index=True)
+ 
+                try:
+                    roi_theta = aggregate_channel_contrasts_to_roi(
+                        df_contrasts,
+                        roi_json_path=self.json_location,
+                        weighted=weighted,
+                    )
+
+                except Exception as e:
+                    print(f"Failed to aggregate contrasts to ROI: {e}")
+                    continue
+ 
+                if roi_theta.empty:
+                    print("No ROI-level contrast values could be computed "
+                          "(check regions.json channel names against this montage).")
+                    continue
+ 
+                # TODO: Come back to this
+                # df_cha_all intentionally omitted (None): the topography
+                # section of run_roi_second_level_analysis expects
+                # single-condition Condition values in df_cha_all, which
+                # doesn't semantically match a contrast name - skip it here
+                # rather than pass mismatched data.
+                run_roi_second_level_analysis(
+                    df_roi_all=roi_theta,
+                    df_cha_all=None,
+                    raw_haemo=p_haemo,
+                    p_threshold=p_threshold,
+                    min_subjects=min_subjects,
+                    correction_method=correction_method,
+                    target_chroma=target_chroma,
+                    graph_bounds=graph_bounds if graph_bounds > 0.0 else None,
+                )
+ 
+            else:
+                print(f"No method defined for index {idx}")
@@ -0,0 +1,144 @@
+"""
+Filename: participantbrain.py
+Description: Logic for the Participant Brain analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+from mne import Annotations
+from pandas import DataFrame
+
+from mne.io.base import BaseRaw
+
+from flares import brain_3d_visualization, brain_landmarks_3d
+from src.shared.flaresbasewidget import ParticipantUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "show_optodes",
+            "label": "Determine what is rendered above the brain. Valid values are 'sensors', 'labels', 'none', 'all'.",
+            "default": "all",
+            "type": str,
+        },
+        {
+            "key": "show_brodmann",
+            "label": "Show common brodmann areas on the brain.",
+            "default": "True",
+            "type": bool,
+        }
+    ],
+    1: [
+        {
+            "key": "show_optodes",
+            "label": "Determine what is rendered above the brain. Valid values are 'sensors', 'labels', 'none', 'all'.",
+            "default": "all",
+            "type": str,
+        },
+        {
+            "key": "t_or_theta",
+            "label": "Specify if t values or theta values should be plotted. Valid values are 't', 'theta'",
+            "default": "theta",
+            "type": str,
+        },
+        {
+            "key": "show_text",
+            "label": "Display informative text on the top left corner. THIS DOES NOT WORK AND SHOULD BE LEFT AT FALSE",
+            "default": "False",
+            "type": bool,
+        },
+        {
+            "key": "brain_bounds",
+            "label": "Graph Upper/Lower Limit",
+            "default": "1.0",
+            "type": float,
+        }
+    ],
+}
+
+
+class ParticipantBrainViewerWidget(ParticipantUIMixin, FlaresBaseWidget):
+    def __init__(
+        self, 
+        haemo_dict: dict[str | Path, BaseRaw], 
+        cha_dict: dict[str, DataFrame],
+    ) -> None:
+        
+        super().__init__("ParticipantBrain")
+        self.setWindowTitle(f"Participant Brain Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.cha_dict = cha_dict
+
+        self.setup_participant_ui(["0 (Brain Landmarks)", "1 (Brain Activity Visualization)",])
+
+
+    def process_request(self):
+
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES)
+        if request is None:
+            return
+
+        (selected_event, selected_file_paths, selected_indexes, raw_params) = request  
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        # Pass the necessary arguments to each method
+        for file_path in selected_file_paths:
+            haemo_obj = self.haemo_dict.get(file_path)
+
+            if haemo_obj is None:
+                continue
+
+            if selected_event:
+                raw_annotations = getattr(haemo_obj, "annotations", None)
+                
+                if raw_annotations is not None:
+                    annotations = cast(Annotations, raw_annotations)
+                    descriptions = cast(list[str], list(annotations.description))
+                    participant_events: set[str] = set(descriptions)
+                else:
+                    participant_events: set[str] = set()
+                    
+                if selected_event not in participant_events:
+                    print(f"Skipping {self.participant_map[file_path]}: Event '{selected_event}' not found.")
+                    continue
+
+            cha = self.cha_dict.get(file_path)
+
+            for idx in selected_indexes:
+                if idx == 0:
+
+                    params = param_values.get(idx, {})
+                    show_optodes = params.get("show_optodes", None)
+                    show_brodmann = params.get("show_brodmann", None)
+
+                    if show_optodes is None or show_brodmann is None:
+                        print(f"Missing parameters for index {idx}, skipping.")
+                        continue
+
+                    brain_landmarks_3d(haemo_obj, show_optodes, show_brodmann)
+
+                elif idx == 1:
+                    params = param_values.get(idx, {})
+                    show_optodes = params.get("show_optodes", None)
+                    t_or_theta = params.get("t_or_theta", None)
+                    show_text = params.get("show_text", None)
+                    brain_bounds = params.get("brain_bounds", None)
+
+                    if show_optodes is None or t_or_theta is None or show_text is None or brain_bounds is None:
+                        print(f"Missing parameters for index {idx}, skipping.")
+                        continue
+
+                    brain_3d_visualization(haemo_obj, cha, selected_event, t_or_theta=t_or_theta, show_optodes=show_optodes, show_text=show_text, brain_bounds=brain_bounds)
+
+                else:
+                    print(f"No method defined for index {idx}")
@@ -0,0 +1,185 @@
+"""
+Filename: participantfunctionalconnectivity.py
+Description: Logic for the Participant Functional Connectivity analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in Imports
+from pathlib import Path
+from typing import Any, cast
+
+# External library imports
+from PySide6.QtWidgets import QMessageBox
+
+from pandas import DataFrame
+
+from mne import Annotations
+from mne.io.base import BaseRaw
+
+from flares import functional_connectivity_betas, functional_connectivity_envelope, functional_connectivity_spectral_epochs, functional_connectivity_spectral_time
+from src.shared.flaresbasewidget import ParticipantUIMixin, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+PARAMETERIZED_INDEXES: dict[int, list[dict[str, Any]]] = {
+    0: [
+        {
+            "key": "n_lines",
+            "label": "<Description>",
+            "default": "20",
+            "type": int,
+        },
+        {
+            "key": "vmin",
+            "label": "<Description>",
+            "default": "0.9",
+            "type": float,
+        },
+    ],
+    1: [
+        {
+            "key": "n_lines",
+            "label": "<Description>",
+            "default": "20",
+            "type": int,
+        },
+        {
+            "key": "vmin",
+            "label": "<Description>",
+            "default": "0.9",
+            "type": float,
+        },
+        
+    ],
+    2: [
+        {
+            "key": "n_lines",
+            "label": "<Description>",
+            "default": "20",
+            "type": int,
+        },
+        {
+            "key": "vmin",
+            "label": "<Description>",
+            "default": "0.9",
+            "type": float,
+        },
+        
+    ],
+    3: [
+        {
+            "key": "n_lines",
+            "label": "<Description>",
+            "default": "20",
+            "type": int,
+        },
+        {
+            "key": "vmin",
+            "label": "<Description>",
+            "default": "0.9",
+            "type": float,
+        },
+        
+    ],
+}
+
+
+
+class ParticipantFunctionalConnectivityWidget(ParticipantUIMixin, FlaresBaseWidget):
+    def __init__(
+        self,
+        haemo_dict: dict[str | Path, BaseRaw],
+        epochs_dict: dict[str, DataFrame],
+    ) -> None:
+        
+        super().__init__("ParticipantFunctionalConnectivity")
+        self.setWindowTitle(f"Participant Functional Connectivity Viewer [BETA] - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.epochs_dict = epochs_dict
+
+        QMessageBox.warning(self, f"Warning - {APP_NAME.upper()}", f"Functional Connectivity is still in development and the results should currently be taken with a grain of salt. "
+                            "By clicking OK, you accept that the images generated may not be factual.")
+
+        self.setup_participant_ui(["0 (Spectral Connectivity Epochs)", "1 (Envelope Correlation)", "2 (Betas)", "3 (Spectral Connectivity Epochs)",])
+
+
+
+    def process_request(self):
+        request = self.get_common_request_data(PARAMETERIZED_INDEXES)
+        if request is None:
+            return
+
+        (selected_event, selected_file_paths, selected_indexes, raw_params) = request  
+
+        param_values = cast(dict[int | str, dict[str, Any]], raw_params)
+
+        # Pass the necessary arguments to each method
+        for file_path in selected_file_paths:
+            haemo_obj = self.haemo_dict.get(file_path)
+            epochs_obj = self.epochs_dict.get(file_path)
+
+            if haemo_obj is None:
+                continue
+
+            if selected_event:
+                raw_annotations = getattr(haemo_obj, "annotations", None)
+                
+                if raw_annotations is not None:
+                    annotations = cast(Annotations, raw_annotations)
+                    descriptions = cast(list[str], list(annotations.description))
+                    participant_events: set[str] = set(descriptions)
+                else:
+                    participant_events: set[str] = set()
+                    
+                if selected_event not in participant_events:
+                    print(f"Skipping {self.participant_map[file_path]}: Event '{selected_event}' not found.")
+                    continue
+
+
+            for idx in selected_indexes:
+                if idx == 0:
+
+                    params = param_values.get(idx, {})
+                    n_lines = params.get("n_lines", None)
+                    vmin = params.get("vmin", None)
+
+                    if n_lines is None or vmin is None:
+                        print(f"Missing parameters for index {idx}, skipping.")
+                        continue
+                    functional_connectivity_spectral_epochs(epochs_obj, n_lines, vmin)
+
+                elif idx == 1:
+                    params = param_values.get(idx, {})
+                    n_lines = params.get("n_lines", None)
+                    vmin = params.get("vmin", None)
+
+                    if n_lines is None or vmin is None:
+                        print(f"Missing parameters for index {idx}, skipping.")
+                        continue
+                    functional_connectivity_envelope(epochs_obj, n_lines, vmin)
+                    
+                elif idx == 2:
+                    params = param_values.get(idx, {})
+                    n_lines = params.get("n_lines", None)
+                    vmin = params.get("vmin", None)
+
+                    if n_lines is None or vmin is None:
+                        print(f"Missing parameters for index {idx}, skipping.")
+                        continue
+                    functional_connectivity_betas(haemo_obj, n_lines, vmin, selected_event)
+
+                elif idx == 3:
+                    params = param_values.get(idx, {})
+                    n_lines = params.get("n_lines", None)
+                    vmin = params.get("vmin", None)
+
+                    if n_lines is None or vmin is None:
+                        print(f"Missing parameters for index {idx}, skipping.")
+                        continue
+                    functional_connectivity_spectral_time(epochs_obj, n_lines, vmin)
+
+                else:
+                    print(f"No method defined for index {idx}")
@@ -0,0 +1,176 @@
+"""
+Filename: participantimage.py
+Description: Logic for the Participant Image analysis window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in Imports
+import os.path as op
+from pathlib import Path
+from datetime import datetime
+
+# External library imports
+from mne.io.base import BaseRaw
+
+from PySide6.QtWidgets import QGridLayout, QHBoxLayout, QMessageBox, QPushButton, QScrollArea, QWidget, QVBoxLayout, QLabel
+from PySide6.QtCore import Qt, QSize
+from PySide6.QtGui import QPixmap
+
+from src.shared.flaresbasewidget import ClickableLabel, FlaresBaseWidget
+from src.shared.shareddata import APP_NAME
+
+
+class ParticipantImageViewerWidget(FlaresBaseWidget):
+  
+    def __init__(
+        self, 
+        haemo_dict: dict[str, BaseRaw], 
+        fig_bytes_dict: dict[str, dict[str, bytes]]
+    ) -> None:
+        
+        super().__init__("ParticipantImage")
+        self.setAttribute(Qt.WidgetAttribute.WA_DeleteOnClose)
+        self.setWindowTitle(f"Participant Image Viewer - {APP_NAME.upper()}")
+        self.haemo_dict = haemo_dict
+        self.fig_bytes_dict = fig_bytes_dict
+
+        # Create mappings: file_path -> participant label and dropdown display text
+        self.participant_map: dict[str, str] = {}
+        self.participant_dropdown_items: list[str] = []
+
+        for i, file_path in enumerate(self.haemo_dict.keys(), start=1):
+            short_label = f"Participant {i}"
+            display_label = f"{short_label} ({op.basename(file_path)})"
+            self.participant_map[file_path] = short_label
+            self.participant_dropdown_items.append(display_label)
+
+        self.main_layout = QVBoxLayout(self)
+        self.top_bar = QHBoxLayout()
+        self.main_layout.addLayout(self.top_bar)
+
+        self.participant_dropdown = self._create_multiselect_dropdown(self.participant_dropdown_items)
+        self.participant_dropdown.currentIndexChanged.connect(self.update_participant_dropdown_label)
+                
+        first_fig_dict = next(iter(self.fig_bytes_dict.values()))
+        image_label_items = list(first_fig_dict.keys())
+
+        self.image_index_dropdown = self._create_multiselect_dropdown(image_label_items)
+        self.image_index_dropdown.currentIndexChanged.connect(self.update_image_index_dropdown_label)
+
+        self.submit_button = QPushButton("Submit")
+        self.submit_button.clicked.connect(self.show_selected_images)
+
+        self.top_bar.addWidget(QLabel("Participants:"))
+        self.top_bar.addWidget(self.participant_dropdown)
+        self.top_bar.addWidget(QLabel("Image Indexes:"))
+        self.top_bar.addWidget(self.image_index_dropdown)
+        self.top_bar.addWidget(self.submit_button)
+
+        self.scroll_area = QScrollArea()
+        self.scroll_area.setWidgetResizable(True)
+        self.scroll_content = QWidget()
+        self.grid_layout = QGridLayout(self.scroll_content)
+        self.scroll_area.setWidget(self.scroll_content)
+        self.main_layout.addWidget(self.scroll_area)
+
+        self.thumb_size = QSize(280, 180)
+
+        self.save_button = QPushButton("Save Displayed Images")
+        self.save_button.clicked.connect(self.save_displayed_images)
+        self.top_bar.addWidget(self.save_button)
+
+        self.showMaximized()
+
+
+
+    def show_selected_images(self):
+        # Clear previous images
+        while self.grid_layout.count():
+            item = self.grid_layout.takeAt(0)
+            widget = item.widget()
+            if widget:
+                widget.deleteLater()
+
+        selected_display_names = self._get_checked_items(self.participant_dropdown)
+        # Map from display names back to file paths
+        selected_file_paths: list[str] = []
+        for display_name in selected_display_names:
+            # Find file_path by matching display name
+            for fp, short_label in self.participant_map.items():
+                expected_display = f"{short_label} ({Path(fp).name})"
+                if display_name == expected_display:
+                    selected_file_paths.append(str(fp))
+                    break
+
+        selected_labels = self._get_checked_items(self.image_index_dropdown)
+
+        row, col = 0, 0
+        for file_path in selected_file_paths:
+            fig_map: dict[str, bytes] = self.fig_bytes_dict.get(file_path, {})
+            participant_label: str = self.participant_map.get(file_path, "Unknown")
+
+            for label in selected_labels:
+                fig_bytes: bytes | None = fig_map.get(label)
+                if not fig_bytes:
+                    continue
+
+                full_pixmap = QPixmap()
+                full_pixmap.loadFromData(fig_bytes)
+
+                thumbnail_pixmap = full_pixmap.scaled(
+                    self.thumb_size,
+                    Qt.AspectRatioMode.KeepAspectRatio,
+                    Qt.TransformationMode.SmoothTransformation
+                )
+
+                container = QWidget()
+                hlayout = QHBoxLayout(container)
+                hlayout.setContentsMargins(0, 0, 0, 0)
+                hlayout.setSpacing(0)
+                hlayout.setAlignment(Qt.AlignmentFlag.AlignCenter)
+
+                image_label = ClickableLabel(full_pixmap, thumbnail_pixmap)
+                image_label.setToolTip(f"{participant_label}\n{label}")
+                hlayout.addWidget(image_label)
+
+                self.grid_layout.addWidget(container, row, col)
+
+                col += 1
+                if col >= 6:
+                    col = 0
+                    row += 1
+
+        # Update dropdown labels after display
+        self.update_participant_dropdown_label()
+        self.update_image_index_dropdown_label()
+
+
+    def save_displayed_images(self):
+        # Ensure the folder exists
+        save_dir = Path("individual_images")
+        save_dir.mkdir(exist_ok=True)
+
+        selected_display_names = self._get_checked_items(self.participant_dropdown)
+        selected_image_labels = self._get_checked_items(self.image_index_dropdown)
+
+        for display_name in selected_display_names:
+            # Match display name to file path
+            for file_path, short_label in self.participant_map.items():
+                expected_display = f"{short_label} ({op.basename(file_path)})"
+                if display_name == expected_display:
+                    fig_dict = self.fig_bytes_dict.get(file_path, {})
+                    for label in selected_image_labels:
+                        if label not in fig_dict:
+                            continue
+                        fig_bytes = fig_dict[label]
+                        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+                        filename = f"{op.basename(file_path)}_{label}_{timestamp}.png"
+                        output_path = save_dir / filename
+                        with open(output_path, "wb") as f:
+                            f.write(fig_bytes)
+                    break  # file_path matched; stop loop
+
+        QMessageBox.information(self, "Save Complete", f"Images saved to {save_dir.resolve()}")
@@ -0,0 +1,64 @@
+"""
+Filename: shareddata.py
+Description: Shared constants and methods other files depend on
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+import os
+import sys
+import platform
+
+
+CURRENT_VERSION = "1.5.2"
+APP_NAME = "flares"
+APP_NAME_EXPANDED = "fNIRS Lightweight Analysis, Research, & Evaluation Suite"
+API_URL = f"https://git.research.dezeeuw.ca/api/v1/repos/tyler/{APP_NAME}/releases"
+API_URL_SECONDARY = f"https://git.research2.dezeeuw.ca/api/v1/repos/tyler/{APP_NAME}/releases"
+PLATFORM_NAME = platform.system().lower()
+CHANGELOG_URL = f"https://git.research.dezeeuw.ca/tyler/{APP_NAME}/raw/branch/main/changelog_major.md"
+WIKI_URL = f"https://git.research.dezeeuw.ca/tyler/{APP_NAME}/wiki"
+
+
+PIPELINE_STAGES = [
+    "Preprocessing",
+    "Trimming",
+    "Verify Optode Placement",
+    "Short/Long Channels",
+    "Heart Rate",
+    "Scalp Coupling Index",
+    "Signal to Noise Ratio",
+    "Peak Spectral Power",
+    "Cross Validation",
+    "Median Absolute Deviation",
+    "Power Spectral Density Noise",
+    "Channel Variance",
+    "Bad Channels Handling",
+    "Optical Density",
+    "Temporal Derivative Distribution Repair Filtering",
+    "Wavelet Filtering",
+    "Haemoglobin Concentration",
+    "Enhance Negative Correlation",
+    "Filter",
+    "Extracting Events",
+    "Epoch Calculations",
+    "Design Matrix",
+    "General Linear Model",
+    "Generate GLM Results",
+    "Generate Channel Results",
+    "Generate Region of Interest Results",
+    "Generate Contrast Results",
+    "Finishing Up"
+]
+
+
+def resource_path(relative_path: str) -> str:
+    """
+    Get absolute path to resource regardless of running directly or packaged using PyInstaller
+    """
+
+    base_path = getattr(sys, "_MEIPASS", os.path.abspath("."))
+    return os.path.join(base_path, relative_path)
@@ -0,0 +1,39 @@
+"""
+Filename: about.py
+Description: About window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+from PySide6.QtWidgets import QWidget, QVBoxLayout, QLabel
+from PySide6.QtCore import Qt
+
+from src.shared.shareddata import APP_NAME, APP_NAME_EXPANDED, CURRENT_VERSION
+
+class AboutWindow(QWidget):
+    """
+    Simple About window displaying basic application information.
+
+    Args:
+        parent (QWidget, optional): Parent widget of this window. Defaults to None.
+    """
+
+    def __init__(self, parent: QWidget | None = None) -> None:
+        super().__init__(parent, Qt.WindowType.Window)
+        self.setWindowTitle(f"About {APP_NAME.upper()}")
+        self.resize(250, 100)
+
+        layout = QVBoxLayout()
+        label = QLabel(f"About {APP_NAME.upper()}", self)
+        label2 = QLabel(f"{APP_NAME_EXPANDED}", self)
+        label3 = QLabel(f"{APP_NAME.upper()} is licensed under the GPL-3.0 licence. For more information, visit https://www.gnu.org/licenses/gpl-3.0.en.html", self)
+        label4 = QLabel(f"Version v{CURRENT_VERSION}")
+                        
+        layout.addWidget(label)
+        layout.addWidget(label2)
+        layout.addWidget(label3)
+        layout.addWidget(label4)
+
+        self.setLayout(layout)
@@ -0,0 +1,104 @@
+"""
+Filename: terminal.py
+Description: Terminal window
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+from typing import Any, Callable
+
+from PySide6.QtWidgets import QWidget, QVBoxLayout, QTextEdit, QLineEdit
+from PySide6.QtCore import Qt
+
+from src.shared.shareddata import API_URL, API_URL_SECONDARY, APP_NAME, CURRENT_VERSION, PLATFORM_NAME
+from src.window.about import AboutWindow
+from updater import UpdateManager
+
+
+class TerminalWindow(QWidget):
+    def __init__(self, parent: QWidget | None = None) -> None:
+        super().__init__(parent, Qt.WindowType.Window)
+        self.setWindowTitle(f"Terminal - {APP_NAME.upper()}")
+        self.resize(320, 180)
+        self.output_area = QTextEdit()
+        self.output_area.setReadOnly(True)
+
+        self.input_line = QLineEdit()
+        self.input_line.returnPressed.connect(self.handle_command)
+
+        layout = QVBoxLayout()
+        layout.addWidget(self.output_area)
+        layout.addWidget(self.input_line)
+        self.setLayout(layout)
+
+        self.commands: dict[str, Callable[..., Any]] = {
+            "hello": self.cmd_hello,
+            "help": self.cmd_help,
+            "version": self.cmd_version,
+            "about": self.cmd_about,
+            "update": self.cmd_update,
+        }
+
+        self.output_area.append(f"Welcome to {APP_NAME.upper()}. You are running version {CURRENT_VERSION}.")
+        self.output_area.append("Type 'help' for a list of available commands.\n")
+
+        self.input_line.setFocus()
+
+
+    def handle_command(self):
+        command_text = self.input_line.text()
+        self.input_line.clear()
+
+        self.output_area.append(f"> {command_text}")
+        parts = command_text.strip().split()
+        if not parts:
+            return
+
+        command_name = parts[0]
+        args = parts[1:]
+
+        func = self.commands.get(command_name)
+        if func:
+            try:
+                result = func(*args)
+                if result:
+                    self.output_area.append(str(result))
+            except Exception as e:
+                self.output_area.append(f"[Error] {e}")
+        else:
+            self.output_area.append(f"[Unknown command] '{command_name}'")
+
+
+    def cmd_hello(self, *args: Any) -> str:
+        return "Hello from the terminal!"
+
+    def cmd_help(self, *args: Any) -> str:
+        return f"Available commands: {', '.join(self.commands.keys())}"
+    
+    def cmd_version(self, *args: Any) -> str:
+        return f"{APP_NAME.upper()} is running version {CURRENT_VERSION}."
+    
+    def cmd_about(self, *args: Any) -> None:
+        self.about = AboutWindow(self)
+        self.about.show()
+
+    def cmd_update(self, *args: Any) -> str:
+        main_win = self.parent()
+        if not isinstance(main_win, QWidget):
+            return "[Error] Main window context not found."
+        
+        self.updater = UpdateManager(
+            main_window=main_win,
+            api_url=API_URL,
+            api_url_sec=API_URL_SECONDARY,
+            current_version=CURRENT_VERSION,
+            platform_name=PLATFORM_NAME,
+            platform_suffix="-" + PLATFORM_NAME,
+            app_name=APP_NAME
+        )
+        self.output_area.append("Checking for updates...")
+        
+        self.updater.manual_check_for_updates()
+        return "See status bar for update information."
@@ -0,0 +1,855 @@
+"""
+Filename: updateevents.py
+Description: Methods to update snirf events for FLARES
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+import os
+import json
+from enum import Enum, auto
+from datetime import datetime
+
+import numpy as np
+
+from PySide6.QtWidgets import QWidget, QVBoxLayout, QLabel, QLineEdit, QPushButton, QComboBox, QHBoxLayout, QMessageBox, QFileDialog
+from PySide6.QtCore import Qt
+
+from mne import Annotations
+from mne.io import read_raw_snirf
+from mne_nirs.io import write_raw_snirf
+
+from src.shared.shareddata import APP_NAME
+
+
+class EventUpdateMode(Enum):
+    WRITE_SNIRF = auto()   # destructive
+    WRITE_JSON = auto()    # non-destructive
+
+
+class UpdateEventsWindow(QWidget):
+    def __init__(self, parent=None, mode=EventUpdateMode.WRITE_SNIRF, caller=None):
+        super().__init__(parent, Qt.WindowType.Window)
+
+        self.mode = mode
+        self.caller = caller or self.__class__.__name__
+        self.setWindowTitle(f"Update event markers - {APP_NAME.upper()}")
+        self.resize(760, 200)
+
+        print("INIT MODE:", mode)
+
+        self.label_file_a = QLabel("SNIRF file:")
+        self.line_edit_file_a = QLineEdit()
+        self.line_edit_file_a.setReadOnly(True)
+        self.btn_browse_a = QPushButton("Browse .snirf")
+        self.btn_browse_a.clicked.connect(self.browse_file_a)
+
+        self.label_file_b = QLabel("BORIS file:")
+        self.line_edit_file_b = QLineEdit()
+        self.line_edit_file_b.setReadOnly(True)
+        self.btn_browse_b = QPushButton("Browse .boris")
+        self.btn_browse_b.clicked.connect(self.browse_file_b)
+
+        self.label_suffix = QLabel("Filename in BORIS project file:")
+        self.combo_suffix = QComboBox()
+        self.combo_suffix.setEditable(False)
+        self.combo_suffix.currentIndexChanged.connect(self.on_observation_selected)
+
+        self.label_events = QLabel("Events in selected observation:")
+        self.combo_events = QComboBox()
+        self.combo_events.setEnabled(False)
+        
+        self.label_snirf_events = QLabel("Events in SNIRF file:")
+        self.combo_snirf_events = QComboBox()
+        self.combo_snirf_events.setEnabled(False)
+
+        self.btn_clear = QPushButton("Clear")
+        self.btn_go = QPushButton("Go")
+        self.btn_clear.clicked.connect(self.clear_files)
+        self.btn_go.clicked.connect(self.go_action)
+
+        # --- 
+        layout = QVBoxLayout()
+        self.description = QLabel()
+        self.description.setTextFormat(Qt.TextFormat.RichText)
+        self.description.setTextInteractionFlags(Qt.TextInteractionFlag.TextBrowserInteraction)
+        self.description.setOpenExternalLinks(True)
+            
+        self.description.setText("The events that are present in a snirf file may not be the events that are to be studied and examined.<br>"
+        "Utilizing different software and video recordings, it is easy enough to see when an action actually occured in a file.<br>"
+        "The software <a href='https://www.boris.unito.it/'>BORIS</a> is used to add these events to video files, and these events can be applied to the snirf file <br>"
+        "selected below by selecting the correct BORIS observation and time syncing it to an event that it shares with the snirf file.")
+
+        layout.addWidget(self.description)
+
+        help_text_a = "Select the SNIRF (.snirf) file to update with new event markers."
+
+        file_a_layout = QHBoxLayout()
+
+        # Help button on the left
+        help_btn_a = QPushButton("?")
+        help_btn_a.setFixedWidth(25)
+        help_btn_a.setToolTip(help_text_a)
+        help_btn_a.clicked.connect(lambda _, text=help_text_a: self.show_help_popup(text))
+        file_a_layout.addWidget(help_btn_a)
+
+        # Container for label + line_edit + browse button with tooltip
+        file_a_container = QWidget()
+        file_a_container_layout = QHBoxLayout()
+        file_a_container_layout.setContentsMargins(0, 0, 0, 0)
+        file_a_container_layout.addWidget(self.label_file_a)
+        file_a_container_layout.addWidget(self.line_edit_file_a)
+        file_a_container_layout.addWidget(self.btn_browse_a)
+        file_a_container.setLayout(file_a_container_layout)
+        file_a_container.setToolTip(help_text_a)
+
+        file_a_layout.addWidget(file_a_container)
+        layout.addLayout(file_a_layout)
+
+        help_text_b = "Provide a .boris project file that contains events for this participant."
+
+        file_b_layout = QHBoxLayout()
+
+        help_btn_b = QPushButton("?")
+        help_btn_b.setFixedWidth(25)
+        help_btn_b.setToolTip(help_text_b)
+        help_btn_b.clicked.connect(lambda _, text=help_text_b: self.show_help_popup(text))
+        file_b_layout.addWidget(help_btn_b)
+
+        file_b_container = QWidget()
+        file_b_container_layout = QHBoxLayout()
+        file_b_container_layout.setContentsMargins(0, 0, 0, 0)
+        file_b_container_layout.addWidget(self.label_file_b)
+        file_b_container_layout.addWidget(self.line_edit_file_b)
+        file_b_container_layout.addWidget(self.btn_browse_b)
+        file_b_container.setLayout(file_b_container_layout)
+        file_b_container.setToolTip(help_text_b)
+
+        file_b_layout.addWidget(file_b_container)
+        layout.addLayout(file_b_layout)
+
+        help_text_suffix = "This participant from the .boris project file matches the .snirf file."
+
+        suffix_layout = QHBoxLayout()
+
+        help_btn_suffix = QPushButton("?")
+        help_btn_suffix.setFixedWidth(25)
+        help_btn_suffix.setToolTip(help_text_suffix)
+        help_btn_suffix.clicked.connect(lambda _, text=help_text_suffix: self.show_help_popup(text))
+        suffix_layout.addWidget(help_btn_suffix)
+
+        suffix_container = QWidget()
+        suffix_container_layout = QHBoxLayout()
+        suffix_container_layout.setContentsMargins(0, 0, 0, 0)
+        suffix_container_layout.addWidget(self.label_suffix)
+        suffix_container_layout.addWidget(self.combo_suffix)
+        suffix_container.setLayout(suffix_container_layout)
+        suffix_container.setToolTip(help_text_suffix)
+
+        suffix_layout.addWidget(suffix_container)
+        layout.addLayout(suffix_layout)
+
+        help_text_suffix = "The events extracted from the BORIS project file for the selected observation."
+
+        suffix2_layout = QHBoxLayout()
+
+        help_btn_suffix = QPushButton("?")
+        help_btn_suffix.setFixedWidth(25)
+        help_btn_suffix.setToolTip(help_text_suffix)
+        help_btn_suffix.clicked.connect(lambda _, text=help_text_suffix: self.show_help_popup(text))
+        suffix2_layout.addWidget(help_btn_suffix)
+        
+        suffix2_container = QWidget()
+        suffix2_container_layout = QHBoxLayout()
+        suffix2_container_layout.setContentsMargins(0, 0, 0, 0)
+        suffix2_container_layout.addWidget(self.label_events)
+        suffix2_container_layout.addWidget(self.combo_events)
+        suffix2_container.setLayout(suffix2_container_layout)
+        suffix2_container.setToolTip(help_text_suffix)
+
+        suffix2_layout.addWidget(suffix2_container)
+        layout.addLayout(suffix2_layout)
+        
+        snirf_events_layout = QHBoxLayout()
+
+        help_text_snirf_events = "The event markers extracted from the SNIRF file."
+        help_btn_snirf_events = QPushButton("?")
+        help_btn_snirf_events.setFixedWidth(25)
+        help_btn_snirf_events.setToolTip(help_text_snirf_events)
+        help_btn_snirf_events.clicked.connect(lambda _, text=help_text_snirf_events: self.show_help_popup(text))
+        snirf_events_layout.addWidget(help_btn_snirf_events)
+
+        snirf_events_container = QWidget()
+        snirf_events_container_layout = QHBoxLayout()
+        snirf_events_container_layout.setContentsMargins(0, 0, 0, 0)
+        snirf_events_container_layout.addWidget(self.label_snirf_events)
+        snirf_events_container_layout.addWidget(self.combo_snirf_events)
+        snirf_events_container.setLayout(snirf_events_container_layout)
+        snirf_events_container.setToolTip(help_text_snirf_events)
+
+        snirf_events_layout.addWidget(snirf_events_container)
+        layout.addLayout(snirf_events_layout)
+
+        buttons_layout = QHBoxLayout()
+        buttons_layout.addStretch()
+        buttons_layout.addWidget(self.btn_clear)
+        buttons_layout.addWidget(self.btn_go)
+        layout.addLayout(buttons_layout)
+
+        self.setLayout(layout)
+
+    def show_help_popup(self, text):
+        msg = QMessageBox(self)
+        msg.setWindowTitle(f"Parameter Info - {APP_NAME.upper()}")
+        msg.setText(text)
+        msg.exec()
+
+    def browse_file_a(self):
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select SNIRF File", "", "SNIRF Files (*.snirf)")
+        if file_path:
+            self.line_edit_file_a.setText(file_path)
+            try:
+                # TODO: Bad! read_raw_snirf doesnt release memory properly! Should be spawned in a seperate process and killed once completed
+                raw = read_raw_snirf(file_path, preload=False)
+                annotations = raw.annotations
+
+                # Build individual event entries
+                event_entries = []
+                for onset, description in zip(annotations.onset, annotations.description):
+                    event_str = f"{description} @ {onset:.3f}s"
+                    event_entries.append(event_str)
+
+                if not event_entries:
+                    QMessageBox.information(self, "No Events", "No events found in SNIRF file.")
+                    self.combo_snirf_events.clear()
+                    self.combo_snirf_events.setEnabled(False)
+                    return
+
+                self.combo_snirf_events.clear()
+                self.combo_snirf_events.addItems(event_entries)
+                self.combo_snirf_events.setEnabled(True)
+
+            except Exception as e:
+                QMessageBox.warning(self, "Error", f"Could not read SNIRF file with MNE:\n{str(e)}")
+                self.combo_snirf_events.clear()
+                self.combo_snirf_events.setEnabled(False)
+
+    def browse_file_b(self):
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select BORIS File", "", "BORIS project Files (*.boris)")
+        if file_path:
+            self.line_edit_file_b.setText(file_path)
+            
+            try:
+                with open(file_path, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                self.boris_data = data
+
+                observation_keys = self.extract_boris_observation_keys(data)
+                self.combo_suffix.clear()
+                self.combo_suffix.addItems(observation_keys)
+
+            except (json.JSONDecodeError, FileNotFoundError, KeyError) as e:
+                QMessageBox.warning(self, "Error", f"Failed to parse BORIS file:\n{e}")
+                
+    def extract_boris_observation_keys(self, data):
+        if "observations" not in data:
+            raise KeyError("Missing 'observations' key in BORIS file.")
+
+        observations = data["observations"]
+        if not isinstance(observations, dict):
+            raise TypeError("'observations' must be a dictionary.")
+
+        return list(observations.keys())
+    
+    def on_observation_selected(self):
+        selected_obs = self.combo_suffix.currentText()
+        if not selected_obs or not hasattr(self, 'boris_data'):
+            self.combo_events.clear()
+            self.combo_events.setEnabled(False)
+            return
+
+        try:
+            events = self.boris_data["observations"][selected_obs]["events"]
+        except (KeyError, TypeError):
+            self.combo_events.clear()
+            self.combo_events.setEnabled(False)
+            return
+
+        event_entries = []
+        for event in events:
+            if isinstance(event, list) and len(event) >= 3:
+                timestamp = event[0]
+                label = event[2]
+                display = f"{label} @ {timestamp:.3f}"
+                event_entries.append(display)
+
+        self.combo_events.clear()
+        self.combo_events.addItems(event_entries)
+        self.combo_events.setEnabled(bool(event_entries))
+
+    def clear_files(self):
+        self.line_edit_file_a.clear()
+        self.line_edit_file_b.clear()
+    
+    def go_action(self):
+        
+        file_a = self.line_edit_file_a.text()
+        suffix = "flare" 
+    
+        if not hasattr(self, "boris_data") or self.combo_events.count() == 0 or self.combo_snirf_events.count() == 0:
+            QMessageBox.warning(self, "Missing data", "Please make sure a BORIS and SNIRF event are selected.")
+            return
+
+        # Extract BORIS anchor
+        try:
+            boris_label, boris_time_str = self.combo_events.currentText().split(" @ ")
+            boris_anchor_time = float(boris_time_str.replace("s", "").strip())
+        except Exception as e:
+            QMessageBox.critical(self, "BORIS Event Error", f"Could not parse BORIS anchor event:\n{e}")
+            return
+
+        # Extract SNIRF anchor
+        try:
+            snirf_label, snirf_time_str = self.combo_snirf_events.currentText().split(" @ ")
+            snirf_anchor_time = float(snirf_time_str.replace("s", "").strip())
+        except Exception as e:
+            QMessageBox.critical(self, "SNIRF Event Error", f"Could not parse SNIRF anchor event:\n{e}")
+            return
+
+        time_shift = snirf_anchor_time - boris_anchor_time
+
+        selected_obs = self.combo_suffix.currentText()
+        if not selected_obs or selected_obs not in self.boris_data["observations"]:
+            QMessageBox.warning(self, "Invalid selection", "Selected observation not found in BORIS file.")
+            return
+
+        boris_events = self.boris_data["observations"][selected_obs].get("events", [])
+        if not boris_events:
+            QMessageBox.warning(self, "No BORIS events", "No events found in selected BORIS observation.")
+            return
+
+        snirf_path = self.line_edit_file_a.text()
+        if not snirf_path:
+            QMessageBox.warning(self, "No SNIRF file", "Please select a SNIRF file.")
+            return
+
+        boris_obs = self.boris_data["observations"][selected_obs]
+
+        # --- Extract videos + delays ---
+        files = boris_obs.get("file", {})
+        offsets = boris_obs.get("media_info", {}).get("offset", {})
+
+        videos = {}
+        for key, path in files.items():
+            if path:  # only include videos that exist
+                delay = offsets.get(key, 0.0)  # default 0 if missing
+                videos[key] = {"file": path, "delay": delay}
+
+        base_name = os.path.splitext(os.path.basename(file_a))[0]
+
+        if self.mode == EventUpdateMode.WRITE_SNIRF:
+            # Open save dialog for SNIRF
+            base_name = os.path.splitext(os.path.basename(file_a))[0]
+            suggested_name = f"{base_name}_{suffix}.snirf"
+            save_path, _ = QFileDialog.getSaveFileName(
+                self,
+                "Save SNIRF File As",
+                suggested_name,
+                "SNIRF Files (*.snirf)"
+            )
+            if not save_path:
+                print("SNIRF save cancelled.")
+                return
+            if not save_path.lower().endswith(".snirf"):
+                save_path += ".snirf"
+
+            try:
+                raw = read_raw_snirf(file_a, preload=True)
+
+                # --- Align BORIS events to SNIRF ---
+                boris_events = boris_obs.get("events", [])
+                onsets, durations, descriptions = [], [], []
+                open_events = {}  # label -> list of start times
+                label_counts = {}
+                used_times = set()
+                sfreq = raw.info['sfreq']
+                min_shift = 1.0 / sfreq
+                max_attempts = 10
+
+                for event in boris_events:
+                    if not isinstance(event, list) or len(event) < 3:
+                        continue
+                    event_time = event[0]
+                    label = event[2]
+                    count = label_counts.get(label, 0) + 1
+                    label_counts[label] = count
+
+                    if label not in open_events:
+                        open_events[label] = []
+
+                    if count % 2 == 1:
+                        open_events[label].append(event_time)
+                    else:
+                        if open_events[label]:
+                            start_time = open_events[label].pop(0)
+                            duration = event_time - start_time
+                            if duration <= 0:
+                                continue
+
+                            adjusted_time = start_time + time_shift
+                            attempts = 0
+                            while round(adjusted_time, 6) in used_times and attempts < max_attempts:
+                                adjusted_time += min_shift
+                                attempts += 1
+                            if attempts == max_attempts:
+                                continue
+
+                            adjusted_time = round(adjusted_time, 6)
+                            used_times.add(adjusted_time)
+                            onsets.append(adjusted_time)
+                            durations.append(duration)
+                            descriptions.append(label)
+                # Handle unmatched starts
+                for label, starts in open_events.items():
+                    for start_time in starts:
+                        adjusted_time = start_time + time_shift
+                        attempts = 0
+                        while round(adjusted_time, 6) in used_times and attempts < max_attempts:
+                            adjusted_time += min_shift
+                            attempts += 1
+                        if attempts == max_attempts:
+                            continue
+                        adjusted_time = round(adjusted_time, 6)
+                        used_times.add(adjusted_time)
+                        onsets.append(adjusted_time)
+                        durations.append(0.0)
+                        descriptions.append(label)
+
+                new_annotations = Annotations(onset=onsets, duration=durations, description=descriptions)
+                raw.set_annotations(new_annotations)
+                write_raw_snirf(raw, save_path)
+                QMessageBox.information(self, "Success", "SNIRF file updated with aligned BORIS events.")
+
+            except Exception as e:
+                QMessageBox.critical(self, "Error", f"Failed to update SNIRF file:\n{e}")
+
+        elif self.mode == EventUpdateMode.WRITE_JSON:
+            # Open save dialog for JSON
+            base_name = os.path.splitext(os.path.basename(file_a))[0]
+            suggested_name = f"{base_name}_{suffix}_alignment.json"
+            save_path, _ = QFileDialog.getSaveFileName(
+                self,
+                "Save Event Alignment JSON As",
+                suggested_name,
+                "JSON Files (*.json)"
+            )
+            if not save_path:
+                print("JSON save cancelled.")
+                return
+            if not save_path.lower().endswith(".json"):
+                save_path += ".json"
+
+            # Build JSON dict
+            json_data = {
+                "observation": selected_obs,
+                "snirf_anchor": {"label": snirf_label, "time": snirf_anchor_time},
+                "boris_anchor": {"label": boris_label, "time": boris_anchor_time},
+                "time_shift": time_shift,
+                "videos": videos
+            }
+
+            # Write JSON
+            try:
+                with open(save_path, "w", encoding="utf-8") as f:
+                    json.dump(json_data, f, indent=4)
+                QMessageBox.information(self, "Success", f"Event alignment saved to:\n{save_path}")
+            except Exception as e:
+                QMessageBox.critical(self, "Error", f"Failed to write JSON:\n{e}")
+
+
+    def update_optode_positions(self, file_a, file_b, save_path):
+                
+        fiducials = {}
+        ch_positions = {}
+
+        # Read the lines from the optode file
+        with open(file_b, 'r') as f:
+            for line in f:
+                if line.strip():
+                    # Split by the semicolon and convert to meters
+                    ch_name, coords_str = line.split(":")
+                    coords = np.array(list(map(float, coords_str.strip().split()))) * 0.001
+
+                    # The key we have is a fiducial
+                    if ch_name.lower() in ['lpa', 'nz', 'rpa']:
+                        fiducials[ch_name.lower()] = coords
+
+                    # The key we have is a source or detector
+                    else:
+                        ch_positions[ch_name.upper()] = coords
+
+        # Create montage with updated coords in head space
+        initial_montage = make_dig_montage(ch_pos=ch_positions, nasion=fiducials.get('nz'), lpa=fiducials.get('lpa'), rpa=fiducials.get('rpa'), coord_frame='head') # type: ignore
+
+        # Read the SNIRF file, set the montage, and write it back
+        # TODO: Bad! read_raw_snirf doesnt release memory properly! Should be spawned in a seperate process and killed once completed
+        raw = read_raw_snirf(file_a, preload=True)
+        raw.set_montage(initial_montage)
+        write_raw_snirf(raw, save_path)
+
+
+    def _apply_events_to_snirf(self, raw, new_annotations, save_path):
+        raw.set_annotations(new_annotations)
+        write_raw_snirf(raw, save_path)
+        
+    def _write_event_mapping_json(
+        self,
+        file_a,
+        file_b,
+        selected_obs,
+        snirf_anchor,
+        boris_anchor,
+        time_shift,
+        mapped_events,
+        save_path
+    ):
+
+        payload = {
+            "source": {
+                "called_from": self.caller,
+                "snirf_file": os.path.basename(file_a),
+                "boris_file": os.path.basename(file_b),
+                "observation": selected_obs
+            },
+            "alignment": {
+                "snirf_anchor": snirf_anchor,
+                "boris_anchor": boris_anchor,
+                "time_shift_seconds": time_shift
+            },
+            "events": mapped_events,
+            "created_at": datetime.utcnow().isoformat() + "Z"
+        }
+
+        with open(save_path, "w", encoding="utf-8") as f:
+            json.dump(payload, f, indent=2)
+
+        return save_path
+
+
+
+class UpdateEventsBlazesWindow(QWidget):
+
+    def __init__(self, parent=None, mode=EventUpdateMode.WRITE_SNIRF, caller=None):
+        super().__init__(parent, Qt.WindowType.Window)
+
+        self.mode = mode
+        self.caller = caller or self.__class__.__name__
+        self.setWindowTitle("Update event markers (BLAZES)")
+        self.resize(760, 200)
+
+        self.label_file_a = QLabel("SNIRF file:")
+        self.line_edit_file_a = QLineEdit()
+        self.line_edit_file_a.setReadOnly(True)
+        self.btn_browse_a = QPushButton("Browse .snirf")
+        self.btn_browse_a.clicked.connect(self.browse_file_a)
+
+        self.label_file_b = QLabel("BLAZES file:")
+        self.line_edit_file_b = QLineEdit()
+        self.line_edit_file_b.setReadOnly(True)
+        self.btn_browse_b = QPushButton("Browse .blaze")
+        self.btn_browse_b.clicked.connect(self.browse_file_b)
+
+        self.label_events = QLabel("Events in selected blazes file:")
+        self.combo_events = QComboBox()
+        self.combo_events.setEnabled(False)
+        
+        self.label_snirf_events = QLabel("Events in SNIRF file:")
+        self.combo_snirf_events = QComboBox()
+        self.combo_snirf_events.setEnabled(False)
+
+        self.btn_clear = QPushButton("Clear")
+        self.btn_go = QPushButton("Go")
+        self.btn_clear.clicked.connect(self.clear_files)
+        self.btn_go.clicked.connect(self.go_action)
+
+        # --- 
+        layout = QVBoxLayout()
+        self.description = QLabel()
+        self.description.setTextFormat(Qt.TextFormat.RichText)
+        self.description.setTextInteractionFlags(Qt.TextInteractionFlag.TextBrowserInteraction)
+        self.description.setOpenExternalLinks(True)
+            
+        self.description.setText("The events that are present in a snirf file may not be the events that are to be studied and examined.<br>"
+        "Utilizing different software and video recordings, it is easy enough to see when an action actually occured in a file.<br>"
+        "The software <a href='https://git.research.dezeeuw.ca/tyler/blazes/'>BLAZES</a> is used to create these events in video files, and these events can be applied to the snirf file <br>"
+        "selected below by time syncing it to an event that it shares with the snirf file.")
+
+        layout.addWidget(self.description)
+
+        help_text_a = "Select the SNIRF (.snirf) file to update with new event markers."
+
+        file_a_layout = QHBoxLayout()
+
+        # Help button on the left
+        help_btn_a = QPushButton("?")
+        help_btn_a.setFixedWidth(25)
+        help_btn_a.setToolTip(help_text_a)
+        help_btn_a.clicked.connect(lambda _, text=help_text_a: self.show_help_popup(text))
+        file_a_layout.addWidget(help_btn_a)
+
+        # Container for label + line_edit + browse button with tooltip
+        file_a_container = QWidget()
+        file_a_container_layout = QHBoxLayout()
+        file_a_container_layout.setContentsMargins(0, 0, 0, 0)
+        file_a_container_layout.addWidget(self.label_file_a)
+        file_a_container_layout.addWidget(self.line_edit_file_a)
+        file_a_container_layout.addWidget(self.btn_browse_a)
+        file_a_container.setLayout(file_a_container_layout)
+        file_a_container.setToolTip(help_text_a)
+
+        file_a_layout.addWidget(file_a_container)
+        layout.addLayout(file_a_layout)
+
+        help_text_b = "Provide a .blaze output file that contains events for this participant."
+
+        file_b_layout = QHBoxLayout()
+
+        help_btn_b = QPushButton("?")
+        help_btn_b.setFixedWidth(25)
+        help_btn_b.setToolTip(help_text_b)
+        help_btn_b.clicked.connect(lambda _, text=help_text_b: self.show_help_popup(text))
+        file_b_layout.addWidget(help_btn_b)
+
+        file_b_container = QWidget()
+        file_b_container_layout = QHBoxLayout()
+        file_b_container_layout.setContentsMargins(0, 0, 0, 0)
+        file_b_container_layout.addWidget(self.label_file_b)
+        file_b_container_layout.addWidget(self.line_edit_file_b)
+        file_b_container_layout.addWidget(self.btn_browse_b)
+        file_b_container.setLayout(file_b_container_layout)
+        file_b_container.setToolTip(help_text_b)
+
+        file_b_layout.addWidget(file_b_container)
+        layout.addLayout(file_b_layout)
+
+        help_text_suffix = "The events extracted from the blaze file."
+
+        suffix2_layout = QHBoxLayout()
+
+        help_btn_suffix = QPushButton("?")
+        help_btn_suffix.setFixedWidth(25)
+        help_btn_suffix.setToolTip(help_text_suffix)
+        help_btn_suffix.clicked.connect(lambda _, text=help_text_suffix: self.show_help_popup(text))
+        suffix2_layout.addWidget(help_btn_suffix)
+        
+        suffix2_container = QWidget()
+        suffix2_container_layout = QHBoxLayout()
+        suffix2_container_layout.setContentsMargins(0, 0, 0, 0)
+        suffix2_container_layout.addWidget(self.label_events)
+        suffix2_container_layout.addWidget(self.combo_events)
+        suffix2_container.setLayout(suffix2_container_layout)
+        suffix2_container.setToolTip(help_text_suffix)
+
+        suffix2_layout.addWidget(suffix2_container)
+        layout.addLayout(suffix2_layout)
+        
+        snirf_events_layout = QHBoxLayout()
+
+        help_text_snirf_events = "The event markers extracted from the SNIRF file."
+        help_btn_snirf_events = QPushButton("?")
+        help_btn_snirf_events.setFixedWidth(25)
+        help_btn_snirf_events.setToolTip(help_text_snirf_events)
+        help_btn_snirf_events.clicked.connect(lambda _, text=help_text_snirf_events: self.show_help_popup(text))
+        snirf_events_layout.addWidget(help_btn_snirf_events)
+
+        snirf_events_container = QWidget()
+        snirf_events_container_layout = QHBoxLayout()
+        snirf_events_container_layout.setContentsMargins(0, 0, 0, 0)
+        snirf_events_container_layout.addWidget(self.label_snirf_events)
+        snirf_events_container_layout.addWidget(self.combo_snirf_events)
+        snirf_events_container.setLayout(snirf_events_container_layout)
+        snirf_events_container.setToolTip(help_text_snirf_events)
+
+        snirf_events_layout.addWidget(snirf_events_container)
+        layout.addLayout(snirf_events_layout)
+
+        buttons_layout = QHBoxLayout()
+        buttons_layout.addStretch()
+        buttons_layout.addWidget(self.btn_clear)
+        buttons_layout.addWidget(self.btn_go)
+        layout.addLayout(buttons_layout)
+
+        self.setLayout(layout)
+
+
+    def show_help_popup(self, text):
+        msg = QMessageBox(self)
+        msg.setWindowTitle(f"Parameter Info - {APP_NAME.upper()}")
+        msg.setText(text)
+        msg.exec()
+
+    def browse_file_a(self):
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select SNIRF File", "", "SNIRF Files (*.snirf)")
+        if file_path:
+            self.line_edit_file_a.setText(file_path)
+            try:
+                # TODO: Bad! read_raw_snirf doesnt release memory properly! Should be spawned in a seperate process and killed once completed
+                raw = read_raw_snirf(file_path, preload=False)
+                annotations = raw.annotations
+
+                # Build individual event entries
+                event_entries = []
+                for onset, description in zip(annotations.onset, annotations.description):
+                    event_str = f"{description} @ {onset:.3f}s"
+                    event_entries.append(event_str)
+
+                if not event_entries:
+                    QMessageBox.information(self, "No Events", "No events found in SNIRF file.")
+                    self.combo_snirf_events.clear()
+                    self.combo_snirf_events.setEnabled(False)
+                    return
+
+                self.combo_snirf_events.clear()
+                self.combo_snirf_events.addItems(event_entries)
+                self.combo_snirf_events.setEnabled(True)
+
+            except Exception as e:
+                QMessageBox.warning(self, "Error", f"Could not read SNIRF file with MNE:\n{str(e)}")
+                self.combo_snirf_events.clear()
+                self.combo_snirf_events.setEnabled(False)
+
+    def browse_file_b(self):
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select JSON Timeline File", "", "JSON Files (*.json)")
+        if file_path:
+            self.line_edit_file_b.setText(file_path)
+            
+            try:
+                with open(file_path, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                self.json_data = data
+
+                obs_keys = self.extract_json_observation_strings(data)
+                self.combo_events.clear()
+                if obs_keys:
+                    self.combo_events.addItems(obs_keys)
+                    self.combo_events.setEnabled(True)
+                else:
+                    QMessageBox.information(self, "No Events", "No events found in JSON file.")
+                    self.combo_events.setEnabled(False)
+
+            except (json.JSONDecodeError, FileNotFoundError, KeyError, TypeError) as e:
+                QMessageBox.warning(self, "Error", f"Failed to parse JSON file:\n{e}")
+                self.combo_events.clear()
+                self.combo_events.setEnabled(False)
+                
+
+    def extract_json_observation_strings(self, data):
+        if "events" not in data:
+            raise KeyError("Missing 'events' key in JSON file.")
+
+        event_strings = []
+
+        # The new format is a flat list chronologically ordered
+        for event in data["events"]:
+            track_name = event.get("track_name", "Unknown")
+            onset = event.get("start_sec", 0.0)
+            
+            # Formatting to match your SNIRF style: "Event Name @ 0.000s"
+            display_str = f"{track_name} @ {onset:.3f}s"
+            event_strings.append(display_str)
+
+        return event_strings
+    
+
+    def clear_files(self):
+        self.line_edit_file_a.clear()
+        self.line_edit_file_b.clear()
+    
+    
+    def go_action(self):
+        file_a = self.line_edit_file_a.text()
+        file_b = self.line_edit_file_b.text()
+        suffix = APP_NAME
+    
+        if not hasattr(self, "json_data") or self.combo_events.count() == 0 or self.combo_snirf_events.count() == 0:
+            QMessageBox.warning(self, "Missing data", "Please make sure a JSON and SNIRF event are selected.")
+            return
+
+        try:
+            json_text = self.combo_events.currentText()
+            _, json_time_str = json_text.split(" @ ")
+            json_anchor_time = float(json_time_str.replace("s", "").strip())
+        except Exception as e:
+            QMessageBox.critical(self, "JSON Event Error", f"Could not parse JSON anchor:\n{e}")
+            return
+
+        try:
+            snirf_text = self.combo_snirf_events.currentText()
+            _, snirf_time_str = snirf_text.split(" @ ")
+            snirf_anchor_time = float(snirf_time_str.replace("s", "").strip())
+        except Exception as e:
+            QMessageBox.critical(self, "SNIRF Event Error", f"Could not parse SNIRF anchor:\n{e}")
+            return
+
+        time_shift = snirf_anchor_time - json_anchor_time
+
+        onsets, durations, descriptions = [], [], []
+        skipped_count = 0
+        
+        try:
+            events_list = self.json_data.get("events", [])
+            
+            for event in events_list:
+                track_name = event.get("track_name", "Unknown")
+                clean_name = track_name.replace("AI: ", "").strip()
+                
+                original_start = event.get("start_sec", 0.0)
+                original_end = event.get("end_sec", original_start)
+                duration = original_end - original_start
+
+                # FILTER: Minimum 0.1s duration
+                if duration < 0.1:
+                    skipped_count += 1
+                    continue
+
+                # Apply shift
+                adjusted_onset = original_start + time_shift
+
+                onsets.append(round(adjusted_onset, 6))
+                durations.append(round(duration, 6))
+                descriptions.append(clean_name) 
+
+        except Exception as e:
+            QMessageBox.critical(self, "Track Error", f"Failed to process tracks: {e}")
+            return
+
+        if not onsets:
+            QMessageBox.warning(self, "No Data", f"No events met the 0.1s threshold. (Skipped {skipped_count})")
+            return
+
+        if self.mode == EventUpdateMode.WRITE_SNIRF:
+            suggested_name = f"{os.path.splitext(os.path.basename(file_a))[0]}_{suffix}.snirf"
+            save_path, _ = QFileDialog.getSaveFileName(self, "Save SNIRF", suggested_name, "SNIRF Files (*.snirf)")
+            
+            if not save_path: return
+            if not save_path.lower().endswith(".snirf"): save_path += ".snirf"
+
+            try:
+                raw = read_raw_snirf(file_a, preload=True)
+                
+                # Create annotations
+                new_annotations = Annotations(
+                    onset=onsets, 
+                    duration=durations, 
+                    description=descriptions
+                )
+                
+                # Replace existing annotations with the new aligned JSON tracks
+                raw.set_annotations(new_annotations)
+                
+                write_raw_snirf(raw, save_path)
+                QMessageBox.information(self, "Success", 
+                    f"Aligned {len(onsets)} events.\n(Filtered out {skipped_count} short events)")
+            except Exception as e:
+                QMessageBox.critical(self, "Error", f"Failed to update SNIRF file:\n{e}")
@@ -0,0 +1,296 @@
+"""
+Filename: updateoptodes.py
+Description: Methods to update optode locations for FLARES
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+import os
+from pathlib import Path
+
+import pandas as pd
+import numpy as np
+
+from PySide6.QtWidgets import QWidget, QVBoxLayout, QLabel, QHBoxLayout, QMessageBox, QLineEdit, QPushButton, QFileDialog
+from PySide6.QtCore import Qt
+
+from mne.io import read_raw_snirf  #type: ignore
+from mne_nirs.io import write_raw_snirf  #type: ignore
+from mne.channels import make_dig_montage  #type: ignore
+
+from src.shared.shareddata import APP_NAME
+
+
+class UpdateOptodesWindow(QWidget):
+
+    def __init__(self, parent=None):
+        super().__init__(parent, Qt.WindowType.Window)
+        self.setWindowTitle(f"Update optode positions - {APP_NAME.upper()}")
+        self.resize(760, 200)
+
+        self.label_file_a = QLabel("SNIRF file:")
+        self.line_edit_file_a = QLineEdit()
+        self.line_edit_file_a.setReadOnly(True)
+        self.btn_browse_a = QPushButton("Browse .snirf")
+        self.btn_browse_a.clicked.connect(self.browse_file_a)
+
+        self.label_file_b = QLabel("Text file:")
+        self.line_edit_file_b = QLineEdit()
+        self.line_edit_file_b.setReadOnly(True)
+        self.btn_browse_b = QPushButton("Browse .txt/.xlsx")
+        self.btn_browse_b.clicked.connect(self.browse_file_b)
+
+        self.label_suffix = QLabel("Suffix to append to filename:")
+        self.line_edit_suffix = QLineEdit()
+        self.line_edit_suffix.setText("flare")
+
+        self.btn_clear = QPushButton("Clear")
+        self.btn_go = QPushButton("Go")
+        self.btn_clear.clicked.connect(self.clear_files)
+        self.btn_go.clicked.connect(self.go_action)
+
+        # --- 
+        layout = QVBoxLayout()
+        self.description = QLabel()
+        self.description.setTextFormat(Qt.TextFormat.RichText)
+        self.description.setTextInteractionFlags(Qt.TextInteractionFlag.TextBrowserInteraction)
+        self.description.setOpenExternalLinks(False) # Handle the click internally
+            
+        self.description.setText("Some software when creating snirf files will insert a template of optode positions as the correct position of the optodes for the participant.<br>"
+        "This is rarely correct as each head differs slightly in shape or size, and a lot of calculations require the optodes to be in the correct location.<br>"
+        "Using a .txt or .xlsx file, we can update the positions in the snirf file to match those of a digitization system such as one from Polhemus or elsewhere.<br>"
+        "The .txt file should have the fiducials, detectors, and sources clearly labeled, followed by the x, y, and z coordinates seperated by a space.<br>"
+        "An example format of what a digitization text file should look like can be found <a href='custom_link'>by clicking here</a>. Currently only .xlsx files directly exported from a<br>"
+        "Polhemus system are supported.")
+
+        self.description.linkActivated.connect(self.handle_link_click)
+        layout.addWidget(self.description)
+
+        help_text_a = "Select the SNIRF (.snirf) file to update with new optode positions."
+
+        file_a_layout = QHBoxLayout()
+
+        # Help button on the left
+        help_btn_a = QPushButton("?")
+        help_btn_a.setFixedWidth(25)
+        help_btn_a.setToolTip(help_text_a)
+        help_btn_a.clicked.connect(lambda _, text=help_text_a: self.show_help_popup(text))
+        file_a_layout.addWidget(help_btn_a)
+
+        # Container for label + line_edit + browse button with tooltip
+        file_a_container = QWidget()
+        file_a_container_layout = QHBoxLayout()
+        file_a_container_layout.setContentsMargins(0, 0, 0, 0)
+        file_a_container_layout.addWidget(self.label_file_a)
+        file_a_container_layout.addWidget(self.line_edit_file_a)
+        file_a_container_layout.addWidget(self.btn_browse_a)
+        file_a_container.setLayout(file_a_container_layout)
+        file_a_container.setToolTip(help_text_a)
+
+        file_a_layout.addWidget(file_a_container)
+        layout.addLayout(file_a_layout)
+
+        help_text_b = "Provide a .txt file with labeled optodes (e.g., nz, rpa, lpa, d1, s1) and their x, y, z coordinates, or a .xlsx file from a Polhemius system."
+
+        file_b_layout = QHBoxLayout()
+
+        help_btn_b = QPushButton("?")
+        help_btn_b.setFixedWidth(25)
+        help_btn_b.setToolTip(help_text_b)
+        help_btn_b.clicked.connect(lambda _, text=help_text_b: self.show_help_popup(text))
+        file_b_layout.addWidget(help_btn_b)
+
+        file_b_container = QWidget()
+        file_b_container_layout = QHBoxLayout()
+        file_b_container_layout.setContentsMargins(0, 0, 0, 0)
+        file_b_container_layout.addWidget(self.label_file_b)
+        file_b_container_layout.addWidget(self.line_edit_file_b)
+        file_b_container_layout.addWidget(self.btn_browse_b)
+        file_b_container.setLayout(file_b_container_layout)
+        file_b_container.setToolTip(help_text_b)
+
+        file_b_layout.addWidget(file_b_container)
+        layout.addLayout(file_b_layout)
+
+
+        help_text_suffix = "This text will be appended to the original filename when saving. Default is 'flare'."
+
+        suffix_layout = QHBoxLayout()
+
+        help_btn_suffix = QPushButton("?")
+        help_btn_suffix.setFixedWidth(25)
+        help_btn_suffix.setToolTip(help_text_suffix)
+        help_btn_suffix.clicked.connect(lambda _, text=help_text_suffix: self.show_help_popup(text))
+        suffix_layout.addWidget(help_btn_suffix)
+
+        suffix_container = QWidget()
+        suffix_container_layout = QHBoxLayout()
+        suffix_container_layout.setContentsMargins(0, 0, 0, 0)
+        suffix_container_layout.addWidget(self.label_suffix)
+        suffix_container_layout.addWidget(self.line_edit_suffix)
+        suffix_container.setLayout(suffix_container_layout)
+        suffix_container.setToolTip(help_text_suffix)
+
+        suffix_layout.addWidget(suffix_container)
+        layout.addLayout(suffix_layout)
+
+        buttons_layout = QHBoxLayout()
+        buttons_layout.addStretch()
+        buttons_layout.addWidget(self.btn_clear)
+        buttons_layout.addWidget(self.btn_go)
+        layout.addLayout(buttons_layout)
+
+        self.setLayout(layout)
+
+    def show_help_popup(self, text):
+        msg = QMessageBox(self)
+        msg.setWindowTitle(f"Parameter Info - {APP_NAME.upper()}")
+        msg.setText(text)
+        msg.exec()
+
+    def handle_link_click(self, link):
+        if link == "custom_link":
+            msg = QMessageBox(self)
+            msg.setWindowTitle("Example Digitization File")
+
+            text = "nz: -1.91 85.175 -31.1525\n" \
+                "rpa: 80.3825 -17.1925 -57.2775\n" \
+                "lpa: -81.815 -17.1925 -57.965\n" \
+                "d1: 0.01 -97.5175 62.5875\n" \
+                "d2: 25.125 -103.415 45.045\n" \
+                "d3: 49.095 -97.9025 30.2075\n" \
+                "s1: 0.01 -112.43 32.595\n" \
+                "s2: 30.325 -84.3125 71.8975\n" \
+                "s3: 0.01 -70.6875 89.0925\n"
+            msg.setText(text)
+            msg.exec()
+
+    def browse_file_a(self):
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select SNIRF File", "", "SNIRF Files (*.snirf)")
+        if file_path:
+            self.line_edit_file_a.setText(file_path)
+
+    def browse_file_b(self):
+        file_path, _ = QFileDialog.getOpenFileName(self, "Select File", "", "Supported Files (*.txt *.xlsx)")
+        if file_path:
+            self.line_edit_file_b.setText(file_path)
+
+    def clear_files(self):
+        self.line_edit_file_a.clear()
+        self.line_edit_file_b.clear()
+
+    def go_action(self):
+        file_a = self.line_edit_file_a.text()
+        file_b = self.line_edit_file_b.text()
+        suffix = self.line_edit_suffix.text().strip() or "flare"
+
+        if not file_a:
+            QMessageBox.critical(self, "Missing File", "Please select a SNIRF file.")
+            return
+        if not file_b:
+            QMessageBox.critical(self, "Missing File", "Please select a TXT file.")
+            return
+
+        # Get original filename without extension
+        base_name = os.path.splitext(os.path.basename(file_a))[0]
+        suggested_name = f"{base_name}_{suffix}.snirf"
+
+        # Open save dialog with default name
+        save_path, _ = QFileDialog.getSaveFileName(
+            self,
+            "Save SNIRF File As",
+            suggested_name,
+            "SNIRF Files (*.snirf)"
+        )
+
+        if not save_path:
+            print("Save cancelled.")
+            return
+
+        # Ensure .snirf extension
+        if not save_path.lower().endswith(".snirf"):
+            save_path += ".snirf"
+
+        try:
+            self.update_optode_positions(file_a=file_a, file_b=file_b, save_path=save_path)
+        except Exception as e:
+            QMessageBox.critical(self, "Error", f"Failed to write file:\n{e}")
+            return
+        
+        QMessageBox.information(self, "File Saved", f"File was saved to:\n{save_path}")
+
+    def update_optode_positions(self, file_a, file_b, save_path):
+                
+        fiducials = {}
+        ch_positions = {}
+
+        extension = Path(file_b).suffix
+
+        # Read the lines from the optode file
+        if extension == '.txt':
+            with open(file_b, 'r') as f:
+                for line in f:
+                    if line.strip():
+                        # Split by the semicolon and convert to meters
+                        ch_name, coords_str = line.split(":")
+                        coords = np.array(list(map(float, coords_str.strip().split()))) * 0.001
+
+                        # The key we have is a fiducial
+                        if ch_name.lower() in ['lpa', 'nz', 'rpa']:
+                            fiducials[ch_name.lower()] = coords
+
+                        # The key we have is a source or detector
+                        else:
+                            ch_positions[ch_name.upper()] = coords
+
+        elif extension == '.xlsx':
+
+            # TODO: Bad! Why assume sheet1 has the contents?
+            df = pd.read_excel(file_b, sheet_name='Sheet1')
+
+            def _get_block_data(df, block_id, row_mapping, scale=0.001):
+                """Isolates a block, cleans numeric data, and returns a scaled dictionary."""
+                # 1. Isolate and clean
+                block = df[df['block_id'] == block_id].iloc[:, [1, 2, 3]].copy()
+                block = block.apply(pd.to_numeric, errors='coerce')
+                
+                # 2. Extract into dictionary based on mapping
+                result = {}
+                
+                # If row_mapping is a dict (like {0: 'nz'}), use it directly
+                if isinstance(row_mapping, dict):
+                    for row_idx, key in row_mapping.items():
+                        if row_idx < len(block):
+                            result[key] = block.iloc[row_idx].to_numpy(dtype=float) * scale
+                
+                # If row_mapping is a string prefix (like 'D' or 'S'), auto-generate keys
+                elif isinstance(row_mapping, str):
+                    for i in range(len(block)):
+                        result[f"{row_mapping}{i+1}"] = block.iloc[i].to_numpy(dtype=float) * scale
+                        
+                return result
+                    
+            # Identify blocks
+            is_empty = df.isnull().all(axis=1)
+            df['block_id'] = is_empty.cumsum()
+            clean_df = df[~is_empty].copy()
+
+            # Process Block 2: Landmarks
+            fiducials = _get_block_data(clean_df, 2, {0: 'nz', 2: 'rpa', 3: 'lpa'})
+
+            # Process Block 3: D-Points
+            d_points = _get_block_data(clean_df, 3, 'D')
+
+            # Process Block 4: S-Points
+            s_points = _get_block_data(clean_df, 4, 'S')
+
+            ch_positions = {**d_points, **s_points}
+
+        # Create montage with updated coords in head space
+        initial_montage = make_dig_montage(ch_pos=ch_positions, nasion=fiducials.get('nz'), lpa=fiducials.get('lpa'), rpa=fiducials.get('rpa'), coord_frame='head') # type: ignore
+
+        # Read the SNIRF file, set the montage, and write it back
+        raw = read_raw_snirf(file_a, preload=True)
+        raw.set_montage(initial_montage)
+        write_raw_snirf(raw, save_path)
@@ -0,0 +1,41 @@
+"""
+Filename: userguide.py
+Description: User guide for FLARES
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+from PySide6.QtWidgets import QWidget, QVBoxLayout, QLabel
+from PySide6.QtCore import Qt
+
+from src.shared.shareddata import APP_NAME, PIPELINE_STAGES, WIKI_URL
+
+
+class UserGuideWindow(QWidget):
+    """
+    Simple User Guide window displaying basic information on how to use the software.
+
+    Args:
+        parent (QWidget, optional): Parent widget of this window. Defaults to None.
+    """
+
+    def __init__(self, parent: QWidget | None = None) -> None:
+        super().__init__(parent, Qt.WindowType.Window)
+        self.setWindowTitle(f"User Guide - {APP_NAME.upper()}")
+        self.resize(250, 100)
+
+        layout = QVBoxLayout()
+        label = QLabel("Progress Bar Stages:", self)
+        label2_text = "\n".join(f"Stage {idx + 1}: {name}" for idx, name in enumerate(PIPELINE_STAGES)) + "\n"
+        label2 = QLabel(label2_text, self)
+
+        label3 = QLabel(f"For more information, visit the Git wiki page <a href='{WIKI_URL}'>here</a>.", self)
+        label3.setTextFormat(Qt.TextFormat.RichText)
+        label3.setTextInteractionFlags(Qt.TextInteractionFlag.TextBrowserInteraction)
+        label3.setOpenExternalLinks(True)
+        layout.addWidget(label)
+        layout.addWidget(label2)
+        layout.addWidget(label3)
+
+        self.setLayout(layout)
@@ -0,0 +1,75 @@
+"""
+Filename: viewerlauncher.py
+Description: Viewer launcher window
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# External library imports
+from PySide6.QtWidgets import  QPushButton, QWidget, QVBoxLayout
+from PySide6.QtCore import QTimer
+
+from src.analysis.exporttocsv import ExportToCSVWidget
+from src.analysis.intergroupbrainimage import InterGroupBrainImageWidget
+from src.analysis.crossgroupbrainimage import CrossGroupBrainImageWidget
+from src.analysis.intergroupfunctionalconnectivity import InterGroupFunctionalConnectivityWidget
+from src.analysis.intergroupstats import InterGroupStatsWidget
+from src.analysis.crossgroupstats import CrossGroupStatsWidget
+from src.analysis.participantimage import ParticipantImageViewerWidget
+from src.analysis.participantbrain import ParticipantBrainViewerWidget
+from src.analysis.participantfoldchannels import ParticipantFoldChannelsWidget
+from src.analysis.participantfunctionalconnectivity import ParticipantFunctionalConnectivityWidget
+from src.shared.shareddata import APP_NAME
+
+
+class ViewerLauncherWidget(QWidget):
+    def __init__(self, haemo_dict, epochs_dict, cha_dict, df_ind_dict, design_matrix_dict, config_dict, fig_bytes_dict, contrast_results_dict, folding_bypass, json_location):
+        super().__init__()
+        self.setWindowTitle(f"Viewer Launcher - {APP_NAME.upper()}")
+
+        group_dict = {f: c.get("GROUP", "Unknown") for f, c in config_dict.items()}
+        
+        btn_data = [
+            ("Participant Image Viewer", ParticipantImageViewerWidget, [haemo_dict, fig_bytes_dict], True),
+            ("Participant Brain Viewer", ParticipantBrainViewerWidget, [haemo_dict, cha_dict], True),
+            ("Participant Fold Channels Viewer", ParticipantFoldChannelsWidget, [haemo_dict, cha_dict], False),
+            ("Participant Functional Connectivity Viewer [BETA]", ParticipantFunctionalConnectivityWidget, [haemo_dict, epochs_dict], True),
+            ("Inter-Group Functional Connectivity Viewer [BETA]", InterGroupFunctionalConnectivityWidget, [haemo_dict, group_dict, config_dict], True),
+            ("Inter-Group Stats Viewer", InterGroupStatsWidget, [haemo_dict, cha_dict, df_ind_dict, design_matrix_dict, contrast_results_dict, group_dict, json_location], True),
+            ("Cross-Group Stats Viewer", CrossGroupStatsWidget, [haemo_dict, cha_dict, df_ind_dict, design_matrix_dict, contrast_results_dict, group_dict, json_location], True),
+            ("Inter-Group Brain and Image Viewer", InterGroupBrainImageWidget, [haemo_dict, cha_dict, df_ind_dict, design_matrix_dict, contrast_results_dict, group_dict], True),
+            ("Cross-Group Brain and Image Viewer", CrossGroupBrainImageWidget, [haemo_dict, df_ind_dict, design_matrix_dict, contrast_results_dict, group_dict], True),
+            ("Export To CSV Viewer", ExportToCSVWidget, [haemo_dict, cha_dict, df_ind_dict, design_matrix_dict, contrast_results_dict, group_dict, config_dict], True)
+        ]
+
+        layout = QVBoxLayout(self)
+        for label, widget_class, args, requires_bypass in btn_data:
+            btn = QPushButton(f"Open {label}")
+            # Connect directly to the generic opener
+            btn.clicked.connect(lambda _, c=widget_class, b=btn, a=args: self._open_viewer(c, b, *a))
+            btn.setEnabled(not (requires_bypass and folding_bypass))
+            layout.addWidget(btn)
+
+    def _open_viewer(self, widget_class, btn, *args):
+        # Instantiate and show dynamically
+        self.active_viewer = widget_class(*args)
+        self.active_viewer.show()
+        self._trigger_success(btn)
+
+    def _launch(self, func, btn, *args):
+        func(*args)
+        self._trigger_success(btn)
+
+    def _trigger_success(self, button):
+        """Temporarily adds a green checkmark to the button text."""
+        original_text = button.text()
+        button.setText(f"{original_text}  ✔")
+        button.setStyleSheet("color: green; font-weight: bold;")
+        
+        # Revert after 1 second
+        QTimer.singleShot(1000, lambda: self._revert_button(button, original_text))
+
+    def _revert_button(self, button, original_text):
+        button.setText(original_text)
+        button.setStyleSheet("")
@@ -0,0 +1,80 @@
+"""
+Filename: welcome.py
+Description: Welcome dialog for FLARES
+Note: Compliant with pylance strict type checking
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+from PySide6.QtWidgets import QTextBrowser, QVBoxLayout, QLabel, QDialog, QHBoxLayout, QPushButton
+from PySide6.QtGui import QDesktopServices, QIcon
+from PySide6.QtCore import QUrl
+from PySide6.QtNetwork import QNetworkAccessManager, QNetworkRequest, QNetworkReply
+
+from src.shared.shareddata import APP_NAME, CURRENT_VERSION, CHANGELOG_URL, resource_path
+
+
+class WelcomeDialog(QDialog):
+    def __init__(self, parent: QDialog | None = None, direct: bool = True, first: bool = False):
+        super().__init__(parent)
+        self.setWindowTitle(f"What's New - {APP_NAME.upper()}")
+        self.setMinimumSize(550, 450)
+        self.resize(800, 500)
+        
+        layout = QVBoxLayout(self)
+        
+        header_layout = QHBoxLayout()
+        logo_label = QLabel(self)
+
+        # NOTE: might not work on mac and need the icns file
+        logo_label.setPixmap(QIcon(resource_path("icons/main.ico")).pixmap(48, 48))
+        if first:
+            title_label = QLabel(f"<h2>Welcome to {APP_NAME.upper()}!</h2>", self)
+        elif direct:
+            title_label = QLabel(f"<h2>{APP_NAME.upper()} has been sucessfully updated to version {CURRENT_VERSION}!</h2>", self)
+        else:
+            title_label = QLabel(f"<h2>{APP_NAME.upper()} is currently running version {CURRENT_VERSION}.</h2>", self)
+
+        header_layout.addWidget(logo_label)
+        header_layout.addWidget(title_label)
+        header_layout.addStretch()
+        layout.addLayout(header_layout)
+        
+        self.text_browser = QTextBrowser(self)
+        self.text_browser.setHtml("<p style='color: gray;'>Loading latest updates from server...</p>")
+
+        # Ensure links open in the default web browser and not in this window
+        self.text_browser.setOpenLinks(False)
+        self.text_browser.anchorClicked.connect(QDesktopServices.openUrl)
+        layout.addWidget(self.text_browser)
+        
+        footer_layout = QHBoxLayout()
+        
+        ok_button = QPushButton("OK", self)
+        ok_button.setDefault(True)
+        ok_button.clicked.connect(self.accept)
+        
+        footer_layout.addStretch()
+        footer_layout.addWidget(ok_button)
+        layout.addLayout(footer_layout)
+        
+        # Fetch markdown from the web asynchronously
+        self.network_manager = QNetworkAccessManager(self)
+        self.network_manager.finished.connect(self._on_download_complete)
+        self.network_manager.get(QNetworkRequest(QUrl(CHANGELOG_URL)))
+
+
+    def _on_download_complete(self, reply: QNetworkReply) -> None:
+        """Processes the downloaded markdown and drops it into the view frame."""
+        if reply.error() == reply.NetworkError.NoError:
+            raw_bytes = reply.readAll().data()
+
+            # Convert raw bytes to standard text string
+            markdown_text = str(raw_bytes, encoding='utf-8')
+            self.text_browser.setMarkdown(markdown_text)
+        else:
+            self.text_browser.setHtml(
+                f"<p style='color: red;'><b>Failed to load content.</b><br>Error: {reply.errorString()}</p>"
+            )
+        reply.deleteLater()
@@ -0,0 +1 @@
+update
@@ -0,0 +1,550 @@
+"""
+Filename: updater.py
+Description: Generic updater file
+
+Author: Tyler de Zeeuw
+License: GPL-3.0
+"""
+
+# Built-in imports
+import os
+import re
+import sys
+import time
+import shlex
+import shutil
+import zipfile
+import traceback
+import subprocess
+import configparser
+
+# External library imports
+import psutil
+import requests
+
+from PySide6.QtWidgets import QMessageBox
+from PySide6.QtCore import QThread, Signal, QObject
+
+
+class UpdateDownloadThread(QThread):
+    """
+    Thread that downloads and extracts an update package and emits a signal on completion or error.
+
+    Args:
+        download_url (str): URL of the update zip file to download.
+        latest_version (str): Version string of the latest update.
+    """
+        
+    update_ready = Signal(str, str)
+    error_occurred = Signal(str)
+
+    def __init__(self, download_url, latest_version, platform_name, app_name):
+        super().__init__()
+        self.download_url = download_url
+        self.latest_version = latest_version
+        self.platform_name = platform_name
+        self.app_name = app_name
+
+    def run(self):
+        try:
+            local_filename = os.path.basename(self.download_url)
+
+            if self.platform_name == 'darwin':
+                tmp_dir = f'/tmp/{self.app_name}tempupdate'
+                os.makedirs(tmp_dir, exist_ok=True)
+                local_path = os.path.join(tmp_dir, local_filename)
+            else:
+                local_path = os.path.join(os.getcwd(), local_filename)
+
+            # Download the file
+            with requests.get(self.download_url, stream=True, timeout=15) as r:
+                r.raise_for_status()
+                with open(local_path, 'wb') as f:
+                    for chunk in r.iter_content(chunk_size=8192):
+                        if chunk:
+                            f.write(chunk)
+
+            # Extract folder name (remove .zip)
+            if self.platform_name == 'darwin':
+                extract_folder = os.path.splitext(local_filename)[0]
+                extract_path = os.path.join(tmp_dir, extract_folder)
+
+            else:
+                extract_folder = os.path.splitext(local_filename)[0]
+                extract_path = os.path.join(os.getcwd(), extract_folder)
+
+            # Create the folder if not exists
+            os.makedirs(extract_path, exist_ok=True)
+
+            # Extract the zip file contents
+            if self.platform_name == 'darwin':
+                subprocess.run(['ditto', '-xk', local_path, extract_path], check=True)
+            else:
+                with zipfile.ZipFile(local_path, 'r') as zip_ref:
+                    zip_ref.extractall(extract_path)
+
+            # Remove the zip once extracted and emit a signal
+            os.remove(local_path)
+            self.update_ready.emit(self.latest_version, extract_path)
+
+        except Exception as e:
+            # Emit a signal signifying failure
+            self.error_occurred.emit(str(e))
+
+
+
+class UpdateCheckThread(QThread):
+    """
+    Thread that checks for updates by querying the API and emits a signal based on the result.
+
+    Signals:
+        download_requested(str, str): Emitted with (download_url, latest_version) when an update is available.
+        no_update_available(): Emitted when no update is found or current version is up to date.
+        error_occurred(str): Emitted with an error message if the update check fails.
+    """
+
+    download_requested = Signal(str, str)
+    no_update_available = Signal()
+    error_occurred = Signal(str)
+
+    def __init__(self, api_url, api_url_sec, current_version, platform_name, app_name):
+        super().__init__()
+        self.api_url = api_url
+        self.api_url_sec = api_url_sec
+        self.current_version = current_version
+        self.platform_name = platform_name
+        self.app_name = app_name
+
+    def run(self):
+        # if not getattr(sys, 'frozen', False):
+        #     self.error_occurred.emit("Application is not frozen (Development mode).")
+        #     return
+        try:
+            latest_version, download_url = self.get_latest_release_for_platform()
+            if not latest_version:
+                self.no_update_available.emit()
+                return
+
+            if not download_url:
+                self.error_occurred.emit(f"No download available for platform '{self.platform_name}'")
+                return
+
+            if self.version_compare(latest_version, self.current_version) > 0:
+                self.download_requested.emit(download_url, latest_version)
+            else:
+                self.no_update_available.emit()
+
+        except Exception as e:
+            self.error_occurred.emit(f"Update check failed: {e}")
+
+    def version_compare(self, v1, v2):
+        def normalize(v): return [int(x) for x in v.split(".")]
+        return (normalize(v1) > normalize(v2)) - (normalize(v1) < normalize(v2))
+
+    def get_latest_release_for_platform(self):
+        urls = [self.api_url, self.api_url_sec]
+        for url in urls:
+            try:
+                    
+                response = requests.get(url, timeout=5)
+                response.raise_for_status()
+                releases = response.json()
+
+                if not releases:
+                    continue
+
+                latest = next((r for r in releases if not r.get("prerelease") and not r.get("draft")), None)
+
+                if not latest:
+                    continue
+                
+                tag = latest["tag_name"].lstrip("v")
+
+                for asset in latest.get("assets", []):
+                    if self.platform_name in asset["name"].lower():
+                        return tag, asset["browser_download_url"]
+
+                return tag, None
+            except (requests.RequestException, ValueError) as e:
+                continue
+        return None, None
+
+
+class LocalPendingUpdateCheckThread(QThread):
+    """
+    Thread that checks for locally pending updates by scanning the download directory and emits a signal accordingly.
+
+    Args:
+        current_version (str): Current application version.
+        platform_suffix (str): Platform-specific suffix to identify update folders.
+    """
+
+    pending_update_found = Signal(str, str)
+    no_pending_update = Signal()
+
+    def __init__(self, current_version, platform_suffix, platform_name, app_name):
+        super().__init__()
+        self.current_version = current_version
+        self.platform_suffix = platform_suffix
+        self.platform_name = platform_name
+        self.app_name = app_name
+
+    def version_compare(self, v1, v2):
+        def normalize(v): return [int(x) for x in v.split(".")]
+        return (normalize(v1) > normalize(v2)) - (normalize(v1) < normalize(v2))
+
+    def run(self):
+        if self.platform_name == 'darwin':
+            cwd = f'/tmp/{self.app_name}tempupdate'
+        else:
+            cwd = os.getcwd()
+
+        pattern = re.compile(r".*-(\d+\.\d+\.\d+)" + re.escape(self.platform_suffix) + r"$")
+        found = False
+
+        try:
+            for item in os.listdir(cwd):
+                folder_path = os.path.join(cwd, item)
+                if os.path.isdir(folder_path) and item.endswith(self.platform_suffix):
+                    match = pattern.match(item)
+                    if match:
+                        folder_version = match.group(1)
+                        if self.version_compare(folder_version, self.current_version) > 0:
+                            self.pending_update_found.emit(folder_version, folder_path)
+                            found = True
+                            break
+        except:
+            pass
+        
+        if not found:
+            self.no_pending_update.emit()
+
+
+
+
+
+class UpdateManager(QObject):
+    """
+    Orchestrates the update process. 
+    Main apps should instantiate this and call check_for_updates().
+    """
+    
+    def __init__(self, main_window, api_url, api_url_sec, current_version, platform_name, platform_suffix, app_name):
+        super().__init__()
+        self.parent = main_window
+        self.api_url = api_url
+        self.api_url_sec = api_url_sec
+        self.current_version = current_version
+        self.platform_name = platform_name
+        self.platform_suffix = platform_suffix
+        self.app_name = app_name
+        
+        self.pending_update_version = None
+        self.pending_update_path = None
+
+
+    def manual_check_for_updates(self):
+        self.local_check_thread = LocalPendingUpdateCheckThread(self.current_version, self.platform_suffix, self.platform_name, self.app_name)
+        self.local_check_thread.pending_update_found.connect(self.on_pending_update_found)
+        self.local_check_thread.no_pending_update.connect(self.on_no_pending_update)
+        self.local_check_thread.start()
+
+    def on_pending_update_found(self, version, folder_path):
+        self.parent.statusBar().showMessage(f"Pending update found: version {version}")
+        self.pending_update_version = version
+        self.pending_update_path = folder_path
+        self.show_pending_update_popup()
+
+    def on_no_pending_update(self):
+        # No pending update found locally, start server check directly
+        self.parent.statusBar().showMessage("No pending local update found. Checking server...")
+        self.start_update_check_thread()
+
+    def show_pending_update_popup(self):
+        msg_box = QMessageBox(self.parent)
+        msg_box.setWindowTitle("Pending Update Found")
+        msg_box.setText(f"A previously downloaded update for {self.app_name.upper()} (version {self.pending_update_version}) is available at:\n{self.pending_update_path}\nWould you like to install it now?")
+        install_now_button = msg_box.addButton("Install Now", QMessageBox.ButtonRole.AcceptRole)
+        install_later_button = msg_box.addButton("Install Later", QMessageBox.ButtonRole.RejectRole)
+        msg_box.exec()
+
+        if msg_box.clickedButton() == install_now_button:
+            self.install_update(self.pending_update_path)
+        else:
+            self.parent.statusBar().showMessage("Pending update available. Install later.")
+            # After user dismisses, still check the server for new updates
+            self.start_update_check_thread()
+
+    def start_update_check_thread(self):
+        self.check_thread = UpdateCheckThread(self.api_url, self.api_url_sec, self.current_version, self.platform_name, self.app_name)
+        self.check_thread.download_requested.connect(self.on_server_update_requested)
+        self.check_thread.no_update_available.connect(self.on_server_no_update)
+        self.check_thread.error_occurred.connect(self.on_error)
+        self.check_thread.start()
+
+    def on_server_no_update(self):
+        self.parent.statusBar().showMessage("No new updates found on server.", 5000)
+
+    def on_server_update_requested(self, download_url, latest_version):
+        if self.pending_update_version:
+            cmp = self.version_compare(latest_version, self.pending_update_version)
+            if cmp > 0:
+                # Server version is newer than pending update
+                self.parent.statusBar().showMessage(f"Newer version {latest_version} available on server. Removing old pending update...")
+                try:
+                    shutil.rmtree(self.pending_update_path)
+                    self.parent.statusBar().showMessage(f"Deleted old update folder: {self.pending_update_path}")
+                except Exception as e:
+                    self.parent.statusBar().showMessage(f"Failed to delete old update folder: {e}")
+                    
+                # Clear pending update info so new download proceeds
+                self.pending_update_version = None
+                self.pending_update_path = None
+
+                # Download the new update
+                self.download_update(download_url, latest_version)
+            elif cmp == 0:
+                # Versions equal, no download needed
+                self.parent.statusBar().showMessage(f"Pending update version {self.pending_update_version} is already latest. No download needed.")
+            else:
+                # Server version older than pending? Unlikely but just keep pending update
+                self.parent.statusBar().showMessage(f"Pending update version {self.pending_update_version} is newer than server version. No action.")
+        else:
+            # No pending update, just download
+            self.download_update(download_url, latest_version)
+
+    def download_update(self, download_url, latest_version):
+        self.parent.statusBar().showMessage("Downloading update...")
+        self.download_thread = UpdateDownloadThread(download_url, latest_version, self.platform_name, self.app_name)
+        self.download_thread.update_ready.connect(self.on_update_ready)
+        self.download_thread.error_occurred.connect(self.on_error)
+        self.download_thread.start()
+
+    def on_update_ready(self, latest_version, extract_folder):
+        self.parent.statusBar().showMessage("Update downloaded and extracted.")
+
+        msg_box = QMessageBox(self.parent)
+        msg_box.setWindowTitle("Update Ready")
+        msg_box.setText(f"Version {latest_version} has been downloaded and extracted to:\n{extract_folder}\nWould you like to install it now?")
+        install_now_button = msg_box.addButton("Install Now", QMessageBox.ButtonRole.AcceptRole)
+        install_later_button = msg_box.addButton("Install Later", QMessageBox.ButtonRole.RejectRole)
+
+        msg_box.exec()
+
+        if msg_box.clickedButton() == install_now_button:
+            self.install_update(extract_folder)
+        else:
+            self.parent.statusBar().showMessage("Update ready. Install later.")
+
+
+    def install_update(self, extract_folder):
+        # Path to updater executable
+
+        if self.platform_name == 'windows':
+            updater_path = os.path.join(os.getcwd(), f"{self.app_name}_updater.exe")
+        elif self.platform_name == 'darwin':
+            if getattr(sys, 'frozen', False):
+                updater_path = os.path.join(os.path.dirname(sys.executable), f"../../../{self.app_name}_updater.app")
+            else:
+                updater_path = os.path.join(os.getcwd(), f"../{self.app_name}_updater.app")
+
+        elif self.platform_name == 'linux':
+            updater_path = os.path.join(os.getcwd(), f"{self.app_name}_updater")
+        else:
+            updater_path = os.getcwd()
+
+        if not os.path.exists(updater_path):
+            QMessageBox.critical(self.parent, "Error", f"Updater not found at:\n{updater_path}. The absolute path was {os.path.abspath(updater_path)}")
+            return
+
+        # Launch updater with extracted folder path as argument
+        try:
+            # Pass current app's executable path for updater to relaunch
+            main_app_executable = os.path.abspath(sys.argv[0])
+
+            print(f'Launching updater with: "{updater_path}" "{extract_folder}" "{main_app_executable}"')
+
+            if self.platform_name == 'darwin':
+                subprocess.Popen(['open', updater_path, '--args', extract_folder, main_app_executable])
+            else:
+                subprocess.Popen([updater_path, f'{extract_folder}', f'{main_app_executable}'], cwd=os.path.dirname(updater_path))
+
+            # Close the current app so updater can replace files
+            sys.exit(0)
+
+        except Exception as e:
+            QMessageBox.critical(self.parent, "Error", f"[Updater Launch Failed]\n{str(e)}\n{traceback.format_exc()}")
+
+    def on_error(self, message):
+        # print(f"Error: {message}")
+        self.parent.statusBar().showMessage(f"Error occurred during update process. {message}")
+
+    def version_compare(self, v1, v2):
+        def normalize(v): return [int(x) for x in v.split(".")]
+        return (normalize(v1) > normalize(v2)) - (normalize(v1) < normalize(v2))
+
+
+def wait_for_process_to_exit(process_name, timeout=10):
+    """
+    Waits for a process with the specified name to exit within a timeout period.
+
+    Args:
+        process_name (str): Name (or part of the name) of the process to wait for.
+        timeout (int, optional): Maximum time to wait in seconds. Defaults to 10.
+
+    Returns:
+        bool: True if the process exited before the timeout, False otherwise.
+    """
+
+    print(f"Waiting for {process_name} to exit...")
+    deadline = time.time() + timeout
+    while time.time() < deadline:
+        still_running = False
+        for proc in psutil.process_iter(['name']):
+            try:
+                if proc.info['name'] and process_name.lower() in proc.info['name'].lower():
+                    still_running = True
+                    print(f"Still running: {proc.info['name']} (PID: {proc.pid})")
+                    break
+            except (psutil.NoSuchProcess, psutil.AccessDenied):
+                continue
+        if not still_running:
+            print(f"{process_name} has exited.")
+            return True
+        time.sleep(0.5)
+    print(f"{process_name} did not exit in time.")
+    return False
+
+
+def finish_update_if_needed(platform_name, app_name, cfg_path):
+    """
+    Completes a pending application update if '--finish-update' is present in the command-line arguments.
+    """
+
+    if "--finish-update" in sys.argv:
+        print("Finishing update...")
+        
+        update_cfg = configparser.ConfigParser()
+        try:
+            update_cfg.read(cfg_path)              
+            update_cfg.set("Options", "show_welcome_dialog", "true")
+            
+            with open(cfg_path, "w") as f:
+                update_cfg.write(f)
+            print("Welcome dialog flag successfully reset to 'true' for next run.")
+        except Exception as e:
+            print(f"Warning: Could not update welcome dialog preference flag: {e}")
+
+        if platform_name == 'darwin':
+            app_dir = f'/tmp/{app_name}tempupdate'
+        else:
+            app_dir = os.getcwd()
+
+        # 1. Find update folder
+        update_folder = None
+        for entry in os.listdir(app_dir):
+            entry_path = os.path.join(app_dir, entry)
+            if os.path.isdir(entry_path) and entry.startswith(f"{app_name}-") and entry.endswith("-" + platform_name):
+                update_folder = os.path.join(app_dir, entry)
+                break
+
+        if update_folder is None:
+            print("No update folder found. Skipping update steps.")
+            return
+        
+        if platform_name == 'darwin':
+            update_folder = os.path.join(update_folder, f"{app_name}-darwin")
+
+        # 2. Wait for updater to exit
+        print(f"Waiting for {app_name}_updater to exit...")
+        for proc in psutil.process_iter(['pid', 'name']):
+            if proc.info['name'] and f"{app_name}_updater" in proc.info['name'].lower():
+                try:
+                    proc.wait(timeout=5)
+                except psutil.TimeoutExpired:
+                    print(f"Force killing lingering {app_name}_updater")
+                    proc.kill()
+
+        # 3. Replace the updater
+        if platform_name == 'windows':
+            new_updater = os.path.join(update_folder, f"{app_name}_updater.exe")
+            dest_updater = os.path.join(app_dir, f"{app_name}_updater.exe")
+
+        elif platform_name == 'darwin':
+            new_updater = os.path.join(update_folder, f"{app_name}_updater.app")
+            dest_updater = os.path.abspath(os.path.join(sys.executable, f"../../../../{app_name}_updater.app"))
+
+        elif platform_name == 'linux':
+            new_updater = os.path.join(update_folder, f"{app_name}_updater")
+            dest_updater = os.path.join(app_dir, f"{app_name}_updater")
+
+        else:
+            print("Unknown Platform")
+            new_updater = os.getcwd()
+            dest_updater = os.getcwd()
+
+        print(f"New updater is {new_updater}")
+        print(f"Dest updater is {dest_updater}")
+
+        print("Writable?", os.access(dest_updater, os.W_OK))
+        print("Executable path:", sys.executable)
+        print("Trying to copy:", new_updater, "->", dest_updater)
+
+        if os.path.exists(new_updater):
+            try:
+                if os.path.exists(dest_updater):
+                    if platform_name == 'darwin':
+                        try:
+                            if os.path.isdir(dest_updater):
+                                shutil.rmtree(dest_updater)
+                                print(f"Deleted directory: {dest_updater}")
+                            else:
+                                os.remove(dest_updater)
+                                print(f"Deleted file: {dest_updater}")
+                        except Exception as e:
+                            print(f"Error deleting {dest_updater}: {e}")
+                    else:
+                        os.remove(dest_updater)
+
+                if platform_name == 'darwin':
+                    wait_for_process_to_exit(f"{app_name}_updater", timeout=10)
+                    subprocess.check_call(["ditto", new_updater, dest_updater])
+                else:
+                    shutil.copy2(new_updater, dest_updater)
+
+                if platform_name in ('linux', 'darwin'):
+                    os.chmod(dest_updater, 0o755)
+
+                if platform_name == 'darwin':
+                    remove_quarantine(dest_updater, app_name)
+
+                print(f"{app_name}_updater replaced.")
+            except Exception as e:
+                print(f"Failed to replace {app_name}_updater: {e}")
+
+        # 4. Delete the update folder
+        try:
+            if platform_name == 'darwin':
+                shutil.rmtree(app_dir)
+            else:
+                shutil.rmtree(update_folder)
+        except Exception as e:
+            print(f"Failed to delete update folder: {e}")
+
+        sys.argv.remove("--finish-update")
+
+
+def remove_quarantine(app_path, app_name):
+    """
+    Removes the macOS quarantine attribute from the specified application path.
+    """
+
+    script = f'''
+    do shell script "xattr -d -r com.apple.quarantine {shlex.quote(app_path)}" with administrator privileges with prompt "{app_name.upper()} needs privileges to finish the update. (2/2)"
+    '''
+    try:
+        subprocess.run(['osascript', '-e', script], check=True)
+        print("✅ Quarantine attribute removed.")
+    except subprocess.CalledProcessError as e:
+        print("❌ Failed to remove quarantine attribute.")
+        print(e)
@@ -18,7 +18,7 @@ VSVersionInfo(
           StringStruct('FileDescription', 'FLARES main application'),
           StringStruct('FileVersion', '1.0.0.0'),
           StringStruct('InternalName', 'flares.exe'),
-           StringStruct('LegalCopyright', '© 2025 Tyler de Zeeuw'),
+           StringStruct('LegalCopyright', '© 2025-2026 Tyler de Zeeuw'),
           StringStruct('OriginalFilename', 'flares.exe'),
           StringStruct('ProductName', 'FLARES'),
           StringStruct('ProductVersion', '1.0.0.0')])
@@ -18,7 +18,7 @@ VSVersionInfo(
           StringStruct('FileDescription', 'FLARES updater application'),
           StringStruct('FileVersion', '1.0.0.0'),
           StringStruct('InternalName', 'main.exe'),
-           StringStruct('LegalCopyright', '© 2025 Tyler de Zeeuw'),
+           StringStruct('LegalCopyright', '© 2025-2026 Tyler de Zeeuw'),
           StringStruct('OriginalFilename', 'flares_updater.exe'),
           StringStruct('ProductName', 'FLARES Updater'),
           StringStruct('ProductVersion', '1.0.0.0')])
Author	SHA1	Message	Date
tyler	defd4ec1c8	1.5.2 time	2026-07-31 01:17:29 -07:00
tyler	3e0d83ca9b	implement the new preferences in the backend	2026-07-30 16:15:33 -07:00
tyler	ebd13927e2	new preferences and bug fixes	2026-07-30 14:18:26 -07:00
tyler	f15a5d9433	improvements for 1.5.2	2026-07-29 17:20:23 -07:00
tyler	8b017005c5	pylance standardization	2026-07-21 00:54:51 -07:00
tyler	2b019c1bc0	preparation for 1.5.1	2026-07-17 23:59:42 -07:00
tyler	0680718398	unhardcoding and general cleanup	2026-07-17 00:07:56 -07:00
tyler	2ff7cda93a	more stats	2026-07-15 22:45:07 -07:00
tyler	d300dfb7f7	continuation of the rewrite	2026-07-15 21:43:22 -07:00
tyler	12afc5d3bc	small rewrite to impose dry principles	2026-07-15 21:21:35 -07:00
tyler	ffa14693b3	start to figure out stats	2026-07-15 16:24:13 -07:00
tyler	afde775b17	almost done 1.5.0	2026-06-28 17:17:35 -07:00
tyler	2708c78f8e	fix for packed images	2026-06-28 13:31:50 -07:00
tyler	b5de8709de	testing changes	2026-06-28 12:58:38 -07:00
tyler	ddb30d98f2	mostly finish rewrite	2026-06-28 10:10:27 -07:00
tyler	f10eb64332	cleanup what I just did	2026-06-28 09:09:06 -07:00
tyler	617daa0e9b	partial rewrite into multiple files	2026-06-28 08:57:38 -07:00
tyler	766bf75dd7	massive changes for 1.5.0	2026-06-28 08:17:36 -07:00
tyler	57b7082564	added second changelog that just contains lines from most recent major update	2026-06-27 21:43:01 -07:00
tyler	e1c7e1a0e6	changelog 1.4.3	2026-05-01 11:42:04 -07:00
tyler	69f3df8921	imptovements for blazes and fix fold again	2026-05-01 11:40:34 -07:00
tyler	d74be5cdec	note for updating optode placements	2026-04-15 16:17:01 -07:00
tyler	0f6434121f	qol improvements + optode location fix	2026-04-15 16:15:15 -07:00
tyler	8d922ecae9	fix for quick update that occured	2026-04-14 08:01:23 -07:00
tyler	8655115cca	fix to too many processes	2026-03-30 14:12:35 -07:00
tyler	74ce2eeb2e	final changes for new release	2026-03-28 14:30:20 -07:00
tyler	70c4c1e779	fix zombie process & added more quality metrics	2026-03-27 08:10:34 -07:00
tyler	94be2fb921	delete unneeded method and comment out unused params	2026-03-24 16:51:55 -07:00
tyler	7ef07678ae	no more zombie + additional bad channel detection underneath	2026-03-24 16:50:30 -07:00
tyler	f2c236bec5	fix logic errors	2026-03-24 12:47:10 -07:00
tyler	46255e6aa3	quick changelog improvements	2026-03-24 11:06:46 -07:00
tyler	3a0eaef30d	new saving format again	2026-03-24 11:04:14 -07:00
tyler	868a67b44b	raised issue fixes	2026-03-23 23:44:34 -07:00
tyler	9a32c8e301	issue fixes	2026-03-23 22:18:22 -07:00
tyler	3afcb54b77	mac + windows standalone craching fixes	2026-03-23 16:49:02 -07:00
tyler	9fe4a4dc30	changes to ignore	2026-03-23 13:35:08 -07:00
tyler	8d893f846e	fold fix	2026-03-21 22:22:01 -07:00
tyler	540793d150	too many fixes to document just read changelog	2026-03-21 15:26:59 -07:00
tyler	4922405138	fix to design matrix parameters	2026-03-17 12:50:43 -07:00
tyler	1b23f2f81a	Merge branch 'main' of https://git.research.dezeeuw.ca/tyler/flares	2026-03-17 12:48:44 -07:00
tyler	3f1161a03a	fix to support both xlsx and txt in same dropdown, update to git ignore	2026-03-17 12:48:42 -07:00
tyler	1b5c31e4ef	add pyinstaller to dependcies	2026-03-16 14:20:39 -07:00
tyler	276e1b1876	fix for xlsx and upgrade dependencies	2026-03-16 14:08:21 -07:00
tyler	3cfc6f01a2	typo	2026-03-13 16:57:51 -07:00
tyler	91fb9b38d4	copyright	2026-03-13 16:55:49 -07:00
tyler	1e346f8ef2	generalization and status bar fix	2026-03-13 14:07:40 -07:00
tyler	8c207b17ad	more generalization	2026-03-13 13:40:49 -07:00
tyler	f794b98d18	changelog and generalization of updater exe	2026-03-13 13:14:00 -07:00
tyler	06972bee28	plz	2026-03-13 13:01:47 -07:00
tyler	c279f269da	update logic seperated and blazes import	2026-03-13 13:00:57 -07:00
tyler	c7d044beed	group fc	2026-02-03 17:29:34 -08:00
tyler	76df19f332	further issue fixes	2026-02-02 13:08:00 -08:00
tyler	22695a2281	functions instead of repeating 6 times	2026-02-01 14:12:46 -08:00
tyler	f1dd9bd184	release worthy?	2026-01-31 23:42:49 -08:00
tyler	dd2ac058af	temp fc	2026-01-30 20:16:55 -08:00
tyler	98c749477c	preferences	2026-01-30 15:38:12 -08:00
tyler	92973da658	fix to fold and memory leaks	2026-01-29 22:30:28 -08:00
tyler	f82978e2e8	changes and improvements	2026-01-29 17:23:52 -08:00
tyler	7007478c3b	update ignore	2026-01-28 10:10:26 -08:00
tyler	fb728d5033	added support updating optode positions from .xlsx	2026-01-28 10:09:06 -08:00
tyler	1b78f1904d	further variable changes	2026-01-23 11:25:01 -08:00
tyler	9779a63a9c	crash and documentation fixes	2026-01-15 12:04:55 -08:00
tyler	2ecd357aca	fix bad dependency	2026-01-14 23:57:54 -08:00
tyler	fe4e8904b4	improvements	2026-01-14 23:54:03 -08:00
tyler	473c945563	fix for desktop windows	2025-11-30 15:42:56 -08:00
tyler	64ed6d2e87	more parameters	2025-11-03 16:56:05 -08:00
tyler	1aa2402d09	updates to hr	2025-10-31 21:21:10 -07:00
tyler	45c6176dba	quick bug fixes	2025-10-21 18:05:30 -07:00
tyler	a4bbdb90c8	update to changelog for build 1.1.5	2025-10-20 16:08:34 -07:00
tyler	953ea90c67	fix to bandpass filter	2025-10-20 16:07:18 -07:00
tyler	20b255321b	improvements	2025-10-20 09:33:50 -07:00
tyler	b5afcec37d	fixes to cross platform saves	2025-10-15 17:09:51 -07:00
tyler	5361f6ea21	changed the changelog	2025-10-15 16:12:51 -07:00
tyler	ee023c26c1	changelog fix	2025-10-15 16:10:48 -07:00
tyler	06c9ff0ecf	update changelog	2025-10-15 15:59:26 -07:00
tyler	542dd85a78	general fixes	2025-10-15 15:51:02 -07:00
tyler	3e0f70ea49	fixes to build version 1.1.3	2025-10-15 12:59:24 -07:00
tyler	d6c71e0ab2	changelog fixes and further updates to cancel running process	2025-10-15 10:48:07 -07:00
tyler	87073fb218	more boris implementation	2025-10-15 10:00:44 -07:00
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