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Antisaccade Tasks

Fig 1. Anti-saccade task, taken from Luna et al, NeuroImage, 2001.

Scoring by Automatic Eye Scoring, see github readme citation section lab papers methods quotes. See Eye Tracking for camera hardware.

Versions

The breakdown of antisaccade tasks is below. For all Eye Tracking tasks, see EyeTracking Task Table (includes Memory Guided Saccade (MGS) Task).

Version sides cue timing
Dollar Reward 6 rew/nue .5s cue
Anti Antisaccade Task 4 red cross var cue, var iti
Antistate
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

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

  1. Identify data location
  2. Source dollarreward.R script in order to create score_all_anti function [https://github.com/LabNeuroCogDevel/autoeyescore/tree/master/EyeLink]
  3. 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)

  1. 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
  2. Turn to wide format so each row represents a single participant

Coding outcome from Automatic Eye Scoring:

  • -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 Automatic Eye Scoring

Raw files from EEG are .bdf and can be read immediately into MATLAB script

  1. Open MATLAB scoring script score_anti.m [/Volumes/Hera/Projects/7TBrainMech/scripts/eeg/eog_cal]
  2. Identify data location [if Habit: /Volumes/Hera/Raw/EEG/Habit]
  3. Grab subject*_anti.bdf and subject*_eyecal.bdf
  4. Information on stimulus channel output [https://github.com/LabNeuroCogDevel/lncdtask/blob/main/lncdtask/dollarreward.py]

EEG Data (EPrime)

For 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)

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.