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tools:antisaccade [2025/03/28 16:34] – vid79tools:antisaccade [2025/09/26 13:29] (current) – [Antisaccade Tasks] will
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 ======  Antisaccade Tasks ====== ======  Antisaccade Tasks ======
  
-{{:tools:pasted:20241121-130148.png}}+The LNCD has a collection of tasks varying how a participant should look away from or to a dot.
  
-Fig 1. Anti-saccade task, //taken from Luna et al, NeuroImage, 2001//.+Scoring by [[tools:autoeyescore]], see <wrap tip>[[https://github.com/LabNeuroCogDevel/autoeyescore/?tab=readme-ov-file#citations|github readme citation section]] lab papers methods quotes</wrap>. See [[:tools:eyetracking]] for camera hardware.
  
-Scoring by [[tools:autoeyescore]], see [[https://github.com/LabNeuroCogDevel/autoeyescore/?tab=readme-ov-file#citations|github readme citation section]] lab papers methods quotes. See [[:tools:eyetracking]] for camera hardware.+ 
 +{{ :tools:pasted:20241121-130148.png |}} 
 +Fig 1. Anti-saccade task, //taken from Luna et al, NeuroImage, 2001//.
  
 ===== Versions ===== ===== Versions =====
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 The breakdown of antisaccade tasks is below. For all [[:tools:eyetracking]] tasks, see [[tools:eyetracking#tasks|EyeTracking Task Table]] (includes [[tools:mgs]]).  The breakdown of antisaccade tasks is below. For all [[:tools:eyetracking]] tasks, see [[tools:eyetracking#tasks|EyeTracking Task Table]] (includes [[tools:mgs]]). 
  
-^Version^ sides ^ cue ^ timing ^ +^Version^ sides ^ cue ^ timing ^ grants ^ 
-|[[:tools:antisaccade:DollarReward]]| 6 | rew/nue          | .5s cue| +|[[:tools:antisaccade:DollarReward]]| 6 | rew/nue          | .5s cue|  EPrime [[:grants:cog]]?; Psychopy [[:grants:habit]], [[:grants:spa]]. [[bigdata:ncanda]] | 
-|[[:tools:antisaccade:Anti]]        | 4 | red cross        | var cue, var iti | +|[[:tools:antisaccade:Anti]]        | 4 | red cross        | var cue, 200ms blank, var iti | eprime behave [[:grants:pet]], [[:grants:7t]] | 
-|[[:tools:antisaccade:Antistate]]   | |                  | | +|[[:tools:antisaccade:Antistate]]   | |                  | | | 
-|[[:tools:antisaccade:bars]]        | | rew/pun w/levels | |+|[[:tools:antisaccade:bars]]        | | rew/pun w/levels | | | 
 +|[[:tools:antisaccade:eeg]]         | |                  | | |
 ==== Anti Task by Project ==== ==== Anti Task by Project ====
  
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 |                        | PET   | MRRC (mMR) | Frogger           | ASL LRO | | |                        | PET   | MRRC (mMR) | Frogger           | ASL LRO | |
 |2018-01-24 - 2022-10-27 | 7T    | Loef       | Anti              | ASL     | | |2018-01-24 - 2022-10-27 | 7T    | Loef       | Anti              | ASL     | |
-|                        | 7T    | BST3       | mgs_encode        | ASL LRO | |+|                        | 7T    | BST3 7T    | mgs_encode        | Avotec  | |
 |                        | 7T    | EEG        | Anti              | EOG     | | |                        | 7T    | EEG        | Anti              | EOG     | |
-|                        | Habit | Loef       | DollarReward      | ASL,EyeLink| | +|                        | Habit | Loef       | DollarReward      | Avotec,EyeLink| | 
 |                        | Habit | EEG        | DollarReward      | EOG     | | |                        | Habit | EEG        | DollarReward      | EOG     | |
 |                        | SPA   | Loef       | DollarReward      | ASL,EyeLink?   | | |                        | SPA   | Loef       | DollarReward      | ASL,EyeLink?   | |
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 ==== Exclusion Criteria ==== ==== Exclusion Criteria ====
-  - Fewer than 25 viable trials (this means they have to have 25 (n) that are not dropped/ scored as -1 (can be 0,1,2)) - this is because that would be like the minimal trials where we can do good stats and not have crazy error bars, etc.+  - Fewer than 25 viable trials (this means they have to have 25 (n) that are not dropped/scored as -1 (can be 0,1,2)) - what we consider the minimum of trials where we believe the ppt actually understood the task
   - Less than 50% 'on task' trials (coded as 1,2)   - Less than 50% 'on task' trials (coded as 1,2)
-  - Statistical outliers by the residuals of the model; people whose residuals are ±2 SD from the mean across any measure +  - Statistical outliers by the residuals of the model; ppt whose residuals are ±2 SD from the mean across any measure
- +
--thank you Ashley+
  
 +-in progress
 ===== Behavioral Data ===== ===== Behavioral Data =====
 //RAW FILES FROM EYE TRACKER ARE EDF OR EYD----- NEED TO BE CONVERTED TO ASC FOR SCRIPT TO WORK// //RAW FILES FROM EYE TRACKER ARE EDF OR EYD----- NEED TO BE CONVERTED TO ASC FOR SCRIPT TO WORK//
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 Raw files from EEG are .bdf and can be read immediately into MATLAB script Raw files from EEG are .bdf and can be read immediately into MATLAB script
  
-  - Open MATLAB scoring script ''score_anti.m'' [/Volumes/Hera/Projects/7TBrainMech/scripts/eeg/eog_cal] +  - Open MATLAB scoring script [''/Volumes/Hera/Projects/7TBrainMech/scripts/eeg/eog_cal''] 
-  - Identify data location [if Habit: /Volumes/Hera/Raw/EEG/Habit] +  - Identify data location [if Habit: ''/Volumes/Hera/Raw/EEG/Habit''] 
-  - Grab subject*_anti.bdf and subject*_eyecal.bdf +  - Grab ''subject*_anti.bdf'' and ''subject*_eyecal.bdf'' 
-  - Information on stimulus channel output [https://github.com/LabNeuroCogDevel/lncdtask/blob/main/lncdtask/dollarreward.py]+  - Information on stimulus channel output, see [[https://github.com/LabNeuroCogDevel/lncdtask/blob/main/lncdtask/dollarreward.py|dollarreward.py]]
   - Run script? Should export long-format csv with all variables of interest that can be pulled into R   - Run script? Should export long-format csv with all variables of interest that can be pulled into R
  
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   - Data should have a row for every trial (repeating lunaid) and saccade information per column (ex: dot position, trial type, latency, number of saccades, and computed event outcome)   - Data should have a row for every trial (repeating lunaid) and saccade information per column (ex: dot position, trial type, latency, number of saccades, and computed event outcome)
   - Clean data by extracting lunaid, visit date, neutral vs reward trials, mutate variables you want like mean latency of correct trials, correct response rate (percent of correct trials; accuracy), percent of error corrected trials (error rate), latency variability for correct trials   - Clean data by extracting lunaid, visit date, neutral vs reward trials, mutate variables you want like mean latency of correct trials, correct response rate (percent of correct trials; accuracy), percent of error corrected trials (error rate), latency variability for correct trials
-  - Turn to wide format so each row represents a single participant [see code /Volumes/Hera/Victoria/Antisaccade-impulsive-control/EOG_Antisaccade_cleaning.Rmd] +  - Turn to wide format so each row represents a single participant [see code ''/Volumes/Hera/Victoria/Antisaccade-impulsive-control/EOG_Antisaccade_cleaning.Rmd''] 
  
  
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-  - Analyze variables of interest [ /Volumes/Hera/Victoria/Antisaccade-impulsive-control/Analysis_EOG_as_data.Rmd] +  - Analyze variables of interest [''/Volumes/Hera/Victoria/Antisaccade-impulsive-control/Analysis_EOG_as_data.Rmd''] 
   -    - 
 ===== EEG Data (EPrime) ===== ===== EEG Data (EPrime) =====