======  Antisaccade Tasks ======

The LNCD has a collection of tasks varying how a participant should look away from or to a dot.

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.


{{ :tools:pasted:20241121-130148.png |}}
Fig 1. Anti-saccade task, //taken from Luna et al, NeuroImage, 2001//.

===== 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 ^ grants ^
|[[: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, 200ms blank, var iti | eprime behave [[:grants:pet]], [[:grants:7t]] |
|[[:tools:antisaccade:Antistate]]   | |                  | | |
|[[:tools:antisaccade:bars]]        | | rew/pun w/levels | | |
|[[:tools:antisaccade:eeg]]         | |                  | | |
==== 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 7T    | mgs_encode        | Avotec  | |
|                        | 7T    | EEG        | Anti              | EOG     | |
|                        | Habit | Loef       | DollarReward      | Avotec,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 ====
<code> 
[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) 
</code>



{{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.