====== Antisaccade Tasks ====== {{:tools:pasted:20241121-130148.png}} Fig 1. Anti-saccade task, //taken from Luna et al, NeuroImage, 2001//. 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. ===== Versions ===== 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 ^ |[[:tools:antisaccade:DollarReward]]| 6 | rew/nue | .5s cue| |[[:tools:antisaccade:Anti]] | 4 | red cross | var cue, var iti | |[[:tools:antisaccade:Antistate]] | | | | |[[:tools:antisaccade:bars]] | | rew/pun w/levels | | ==== Anti Task by Project ==== ^ Dates ^ Project ^ Location ^ version ^ Tracker ^ File ^ | | Cog | Loef | DollarReward | ASL | | | | Cog | NIC | DollarReward (MR) | ASL LRO | | | | Reward| Loef | Bars | ASL | | | | Reward| MRRC | Bars (MR) | ASL LRO | | | | PET | MRRC (mMR) | Frogger | ASL LRO | | |2018-01-24 - 2022-10-27 | 7T | Loef | Anti | ASL | | | | 7T | BST3 | mgs_encode | ASL LRO | | | | 7T | EEG | Anti | EOG | | | | Habit | Loef | DollarReward | ASL,EyeLink| | | | Habit | EEG | DollarReward | EOG | | | | SPA | Loef | DollarReward | ASL,EyeLink? | | | | SPA | EEG | Anti | EOG | | ==== 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)) - 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) - Statistical outliers by the residuals of the model; ppt whose residuals are ±2 SD from the mean across any measure -in progress ===== Behavioral Data ===== //RAW FILES FROM EYE TRACKER ARE EDF OR EYD----- NEED TO BE CONVERTED TO ASC FOR SCRIPT TO WORK// To score, you need to - Identify data location - Source dollarreward.R script in order to create score_all_anti function [https://github.com/LabNeuroCogDevel/autoeyescore/tree/master/EyeLink] - Run all data through function [if Habit; ''alldollarreward_data <- score_all_anti("/Volumes/L/bea_res/Data/Temporary Raw Data/lab_eyetracker/subj_info/sub-1*/ses*/*_DollarReward/sub_*.asc*")''] 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) {{:tools:pasted:20241121-123354.png}} - Clean data by extracting lunaid, visit date, neutral vs reward trials, mutate variables you want like mean latency, correct response rate (accuracy), percent of error corrected trials (error rate) see [[https://github.com/LabNeuroCogDevel/Antisaccade-impulsive-control/blob/main/EyeLink/Dollarreward_cleaning.Rmd]] - Turn to wide format so each row represents a single participant Coding outcome from [[:tools:autoeyescore]]: * ''-1'', dropped event or bad eye tracking * ''0'', incorrect- the participant looked directly at the stimulus * ''1'', correct- the participant looked in the opposite direction of the stimulus * ''2'', error corrected- the participant first looked at the stimulus then looked in the opposite direction percent of error corrected trials is computed as trials scored 2/0+1+2, can be computed as 2/1+2. ===== EOG Data ===== //see [[tools:autoeyescore|Automatic Eye Scoring]]// Raw files from EEG are .bdf and can be read immediately into MATLAB script - Open MATLAB scoring script [''/Volumes/Hera/Projects/7TBrainMech/scripts/eeg/eog_cal''] - Identify data location [if Habit: ''/Volumes/Hera/Raw/EEG/Habit''] - Grab ''subject*_anti.bdf'' and ''subject*_eyecal.bdf'' - 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 Processed csv read into R **STEPS REPEATED AS ABOVE FOR BEHAVIORAL DATA** - 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 - Turn to wide format so each row represents a single participant [see code ''/Volumes/Hera/Victoria/Antisaccade-impulsive-control/EOG_Antisaccade_cleaning.Rmd''] **percent of error corrected trials is computed as trials scored 2/1+2. - Analyze variables of interest [''/Volumes/Hera/Victoria/Antisaccade-impulsive-control/Analysis_EOG_as_data.Rmd''] - ===== EEG Data (EPrime) ===== For [[:grants:7t:eeg|7T EEG]] ==== Trigger ==== [micromed_time, mark]=make_photodiodevector(EEG); iti = mode(mark); mark = mark - iti + 254; % 101-105: anti cue % 151-155: target (dot on, look away) % 254 = back to fixation simple = nan(size(mark)); simple(mark == 254)= 1; % (New ITI) simple(mark>=100 & mark<110)= 2; % (new Anti cue - red fixation cross, prepatory) simple(mark>=150 & mark<= 155)= 3; % (new dot on, look away) {{tools:pasted:20230629-163553.png}} {{tools:pasted:20230630-142146.png}} === References: === * Hallett, P. E. (1978). Primary and secondary saccades to goals defined by instructions. Vision research, 18(10), 1279-1296. * Luna, B., Thulborn, K. R., Munoz, D. P., Merriam, E. P., Garver, K. E., Minshew, N. J., Keshavan, M. S., Genovese, C. R., Eddy, W. F., & Sweeney, J. A. (2001). Maturation of Widely Distributed Brain Function Subserves Cognitive Development. NeuroImage, 13(5), 786–793.