User Manual: Inquisit Food Go/No Go Task


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										Food GO-NOGO TASK
										(Spanish instructions)
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Script Author: Katja Borchert, Ph.D. (katjab@millisecond.com) for Millisecond Software, LLC
Date: 02-21-2017
last updated:  09-25-2024 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC

Script Copyright © 09-25-2024 Millisecond Software


Millisecond Software thanks Dr. John Gunstad for his help with this script and Marta Becerra Losada for sharing 
the Spanish instructions!

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BACKGROUND INFO 	
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Go/Nogo Tasks are used as behavioral measures of inhibition and cognitive control. The Food Go/No Tasks leverages
this paradigm to investigate cognitive control in the context of food.

Teslovich, T. et al (2014). Probing behavioral responses to food: Development of a foodspecific
go/no-go task. Psychiatry Res, 30, 219(1): 166–170.

E-prime script available at: 
http://fablab.yale.edu/page/assays-tools

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TASK DESCRIPTION	
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Go-Nogo task: general task is to press the spacebar whenever an stimuli of the Go category  (e.g. food images) 
is presented and refrain from responding whenever a stimuli of the NoGo category (e.g. toys) is presented.
In this script, participants work through 4 conditions:
(1) high-calorie food “go” with toy “no-go” 
(2) low-calorie food “go” with toy “no-go”
(3) toy “go” with high-calorie food “no-go”
(4) toy “go” with low-calorie food “no-go”
Each condition runs ~75% go trials (35) and ~25% (13) nogo trials. 

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DURATION 
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the default set-up of the script takes appr. 20 minutes to complete

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DATA OUTPUT DICTIONARY
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The fields in the data files are:

(1) Raw data file: 'foodgonogo_raw*.iqdat' (a separate file for each participant)*

build:						The specific Inquisit version used (the 'build') that was run
computer.platform:			the platform the script was run on (win/mac/ios/android)
date, time: 				date and time script was run 
subject, group: 			with the current subject/groupnumber
session:					with the current session id

blockCode, blockNum:		the name and number of the current block (built-in Inquisit variable)
trialCode, trialNum: 		the name and number of the currently recorded trial (built-in Inquisit variable)
								Note: trialNum is a built-in Inquisit variable; it counts all trials run; even those
								that do not store data to the data file such as feedback trials. Thus, trialNum 
								may not reflect the number of main trials run per block.
										
order:						the order in which the four test blocks were run
				
calorieType:				"high" vs. "low" vs. "ctrl"
goType:						"go" vs. "nogo"
iti:						current intertrial interval in ms
									
stim:						stores the currently presented target picture

response:					the participant's response (scancode of response button)
								Spacebar: 57
								no response: 0
										
correct:					the correctness of the response (1 = correct; 0 = otherwise)
latency: 					the response latency (in ms); measured from onset of image until response is registered


(2) Summary data file: 'foodgonogo_summary*.iqdat' (a separate file for each participant)*

inquisit.version: 		Inquisit version run
computer.platform:		the platform the script was run on (win/mac/ios/android)
startDate:				date script was run
startTime:				time script was started
subjectId:				assigned subject id number
groupId:				assigned group id number
sessionId:				assigned session id number
elapsedTime:			time it took to run script (in ms); measured from onset to offset of script
completed:				0 = script was not completed (prematurely aborted); 
						1 = script was completed (all conditions run)

order:					the order in which the four test blocks were run

propCorrect:			overall proportion correct across all trials
meanRT:					mean correct reaction times across all GO trials
sd:						standard deviation of correct reaction times in GO trials
maxRT:					reaction time that is 3 standard deviations slower than the overall mean
minRT:					reaction time that is 3 standard deviations faster than the overall mean

///////////////
food:
///////////////
hitRateFood:			hit rate in food GO trials (across low and high calorie food)
omissionFood:			miss rate in food GO trials (should have responded to food but did not)

commissionFood:			false alarm rate in food (across low and high calorie food) NOGO trials (should NOT have responded to food but did)
						Note: => the higher the commission rate, the lower cognitive control in the face of food stimuli 
						(aka cannot refrain from responding)
						
corrRejectRateFood:		correct rejection Rate in food NOGO trials (correctly suppressed response to food nogo trials)						
						

meanRTFoodOrig:			mean hit reaction time (in ms) in food GO trials (no outliers removed)										
meanRTFoodCleaned:		mean hit reaction time (in ms) in food GO trials (outliers removed*)

+ separate variables
a) HC:  high calorie (HC) food
b) LC:  low calorie (HC) food

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Ctrl (Toys)
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hitRateCtrl:			hit rate in ctrl GO trials (across blocks when toys were paired with low calorie OR high calorie nogo trials)
omissionCtrl:			miss rate in ctrl GO trials (should have responded to toys but did not)
commissionCtrl:			false alarm rate in ctrl NOGO trials (should NOT have responded to toys but did)						
corrRejectRateCtrl:		correct rejection Rate in ctrl NOGO trials (correctly suppressed response to toys nogo trials)						
						
meanRTCtrlOrig:			mean hit reaction time (in ms) in ctrl GO trials (no outliers removed)										
meanRTCtrlCleaned:		mean hit reaction time (in ms) in ctrl GO trials (outliers removed*)

+ separate variables
a) CtrlHC:  toys when run in the same block as high calorie (HC) food (both as signals and as noise)
b) CtrlLC:  toys when run in the same block as low calorie (HC) food (both as signals and as noise)

//////////////////////////////////
Signal Detection Measures
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Note: *Adjustments to z-scores as recommended by:
Gregg, A. & Sedikides, C. (2010). Narcissistic Fragility:
Rethinking Its Links to Explicit and Implicit Self-esteem, Self and Identity, 9:2, 142-161 (p.148)										
=> Adjustments are made if the  FArate (hitRate) = 0 (increased to 0.005) or 1 (decreased to 0.995)*

////////////////////////////////
signal: High Calorie Food
noise: Toys
////////////////////////////////

zHitRateHC:		z-value of the hit rate with signal = HCfood and noise = toys 
zFARateHC:		z-value of the false alarm rate with signal = HCfood and noise = toys 

dPrimeHC:		Computes d' (parametric measure of discriminability btw. signals and noise)
				=> Range (in this script): 
				-5.1516586840152740479 <= dprime <= 5.1516586840152740479 (=perfect performance)
				=> The higher the value, the better signals (HC food stims) were  distinguished from noise (toys)
				(d' = 0: chance performance; negative d-primes: participant treated nontargets as targets and targets as nontargets)
													
cHC: 			c-criterion in signal detection:The absolute value of c provides an indication of the strength of
				the response bias/response style
				negative: participant more likely to report that signal (HC food stims) is present (liberal response style);
				may favor faster responding in speed-accuracy trade-off response paradigms
				positive: favoring caution (conservative response style) 
				
				
same for: LC (signal: Low Calorie Food; Noise: Toys)
same for: CtrlHC (signal: Toys; Noise: High Calorie Food)
same for: CtrlLC (signal: Toys; Noise: Low Calorie Food)

* separate data files: to change to one data file for all participants (on Inquisit Lab only), go to section
"DATA" and follow further instructions


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EXPERIMENTAL SET-UP 
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(I) Practice: 
~3min practice session with a) Food (high and low calorie) Go / Toy Nogo and b) Food Nogo / Toys Go
Total practice trials: 22; trial/stimuli order fixed (see http://fablab.yale.edu/page/assays-tools)

(II) Test:
4 conditions tested: 
(1) high-calorie food “go” with toy “no-go” (block.highGO, 48 trials: 35 go trials, 13 nogo trials)
(2) low-calorie food “go” with toy “no-go”, (block.lowGO)
(3) toy “go” with high-calorie food “no-go”, (block.highNOGO)
(4) toy “go” with low-calorie food “no-go”, (block.lowNOGO)

tested within participants in a blocked format. The order of the 4 conditions were counterbalanced
by groupnumbers (4 orders, see section EXPERIMENT).
Each block runs 35 go trials and 13 nogo trials (= 4 x 48 test trials = 192 test trials total)
By default all blocks run trials/stimuli in a fixed order. Orders taken from:
http://fablab.yale.edu/page/assays-tools

To run the trials/stimuli in random order, go to section Editable Lists and follow further instructions.

Default Trial Timings:
Fixation Cross (ITI duration: either fixed or random*) -> Target Image (500ms) -> Fixation Cross until response or up to 2000ms (End of Trial)

* if parameters.runRandomITI is set to false, a fixed ITI is run. Default is: 2500ms (can be set under section Editable Parameters).
Random ITIs are controlled by list.intertrialIntervals under section Editable Lists.
**Each block starts with a trial that presents the fixation cross in red for 500ms 

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STIMULI
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Stimuli used provided by:
http://fablab.yale.edu/page/assays-tools

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INSTRUCTIONS 
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instructions modelled after instructions used by:
http://fablab.yale.edu/page/assays-tools

all instructions can be edited under section Editable Instructions

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EDITABLE CODE 
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check below for (relatively) easily editable parameters, stimuli, instructions etc. 
Keep in mind that you can use this script as a template and therefore always "mess" with the entire code 
to further customize your experiment.

The parameters you can change are: