User Manual: Inquisit NBack Task (numbers)


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						SINGLE N-BACK TASK - NUMBER (nonadaptive, 1-key version)
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Script Author: Katja Borchert, Ph.D. (katjab@millisecond.com) for Millisecond Software LLC
Date: March, 2012
last updated:  05-15-2023 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC

Script Copyright © 05-15-2023 Millisecond Software

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BACKGROUND INFO 	
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This script implements a basic number n-back procedure. The n-back task is a go/nogo working-memory performance task
with increasing levels of difficulty.

The implemented procedure is based on the letter nback procedure by Ragland et al (2002):	
								
Ragland, J.D., Turetsky, B.I., Gur, R.C, Gunning-Dixon, F., Turner, T, Schroeder, L., Chan, R., & Gur, R.E. (2002).
Working Memory for Complex Figures: An fMRI Comparison of letter and Fractal n-Back Tasks. 
Neuropsychology, 16, 370-379.

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)
											
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TASK DESCRIPTION	
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In the 1-key single n-back task, participants are shown a sequence of stimuli (here: a sequence of white numbers
on a black background) and are asked to indicate whether the currently presented stimulus fulfills the 
following criteria:

for N=0 trials:
- is the number the same as the number '1'? If so (it's a target), and press "A". If not, don't respond.

for N=1 trials:
- is the number the same as the one that preceded it? If so (it's a target), and press "A". If not, don't respond.

for N=2 trials:
- is the number the same as the one presented two trials before? If so (it's a target), and press "A". If not, don't respond.

for N=3 trials:
- is the number the same as the one presented three trials before? If so (it's a target), and press "A". If not, don't respond.

etc. for increasing levels of N

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DURATION 
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the default set-up of the script takes appr. 14 minutes to complete

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DATA FILE INFORMATION 
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The default data stored in the data files are:

(1) Raw data file: 'singlenbacktask_numbers_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. 
										
TotalBlocks:					the total number of experimental blocks run
N:								the current level N tested
starttrialcounter:				keeps track of how many start trials have been run
stimulusitem.1:					the number presented
stimulusnumber.1: 				the item number of the presented number
currenttarget:					the item number of the current target

response:						the Response of the participant (scancode of response button):
								0 = no response
								31 = 'A' key (positive response)
											
responseCategory:				"Hit" vs. "Omission Error" vs. "CorrReject" vs. "Commission Error"

correct:						the correctness of the response (1 = correct; 0 = otherwise)

latency:						how fast a participant responded within the given timeframe, if at all (in ms)
								no responses = the entire trialduration
									
list.blockACC.mean:				proportion correct during the current block (start trials are excluded from block ACC assessment by default, editable)

									
									
(2) Summary data file: 'singlenbacktask_numbers_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)n)
																		
Round:							the total number of experimental blocks run

the following summary variables are only based on performance on trial.target/trial.nontarget 
(excludes trial.start even if parameters.excludeStartTrialfromPerformanceMeasure = false)

propCorrect:			overall proportion correct (across all test blocks)
meanHit_RT:				overall mean correct response time (in ms); is equal to the overall mean hit response time		


Note: z-score calculations: adjustments (see Gregg & Sedikides, 2010, p.148)
If the hit rate  FA rate is 0 => 0.005 is used instead (aka 0.005 is added to the hitFA rate)
IF the hit rate  FA rate is 1.0 => 0.995 is used instead (aka 0.005 is subtracted from the hitFA rate)

hitRate_overall:		overall hit rate (across all test blocks) = hitting 'A' for targets
list.hits.itemCount:	the absolute number of target trials (across all test blocks)							
meanHit_RT:				overall mean hit response time (in ms; across all test blocks)

FArate_overall:			overall False Alarm/Commission Error Rate (across all test blocks) = hitting 'A' for nontargets
list.commissions.itemCount:	the absolute number of nontarget trials (across all test blocks)
meanFA_RT:				overall mean False Alarm response time (in ms; across all test blocks)
zhitrate_overall:		the z-score of the overall hit rate
zFArate_overall:		the z-score of the overall False Alarm rate

dprime_overall:			Computes d' (parametric measure of sensitivity):
						The higher the value, the better targets were overall correctly distinguished 
						from nontargets (d' = 0: chance performance; negative values: nontargets were treated as targets
						and targets were treated as nontargets)


The following variables look at the different levels of N. If a level of N was not run,
the variables will store "not run"										

//Level N = 0										
hitRate_N0:				hit rate (hitting 'A' for targets) for level N = 0
meanHit_RT_N0:			mean hit response time (in ms)  for level N = 0
FArate_N0:				False Alarm/Commission Error Rate (hitting 'A' for nontargets) for level N = 0
meanFA_RT_N0:			mean False Alarm response time (in ms) for level N = 0
zhitrate_N0:			the z-score of the hit rate  for level N = 0
zFArate_N0:				the z-score of the False Alarm rate for level N = 0

dprime_N0:				Computes d' (parametric measure of sensitivity):
						The higher the value, the better targets were overall correctly distinguished 
						from nontargets (d' = 0: chance performance) for level N = 0										

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EXPERIMENTAL SET-UP 
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- After instructions, participants receive 9 trials of practice per level N tested (here: N = 0 to N = 3), 
Note: edit list.nextN_practice to change levels of N practiced

- once practice is done, participants get the option to repeat practice (see parameters.allowPracticeRepeat)

- After practice, participants receive 3 blocks per level of N tested. Which particular level a participant works on is
pseudo-randomly determined (see Ragland et al, 2002).
Note: edit list.Nlevel to change N levels tested as well as number of testblocks

Block Information:
- Each single n-task block consists of 15+ trials (Ragland et al, 2002) using 20 different consonants. 
=> + trials are the N trials that cannot display target shapes yet (=start trials). Their numbers vary depending on N. 
		The data collected during these  start trials are NOT included in performance counts for Correct Rejections/False Alarms.
=> Of the actual  15 experimental trials, 5 present a target and 10 do not (1:2 ratio as in Ragland et al, 2002). 
- The computer selects randomly 
a) whether it is a target trial or not and 
b) what number to show if it is not a target trial

Trial Information:
- Each trial presents the number for 500ms and waits another 2000ms before presenting the next number in the sequence
(see Ragland et al. for InterstimulusInterval = 2500ms). The trialduration can be edited by experimenter.
- Participants have the entire 2500ms to respond by pressing "A" if they detect a target.

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STIMULI
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9 numbers, see section Editable Stimuli

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INSTRUCTIONS 
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provided by Millisecond Software - can be edited under section Editable Instructions

Instructions are not original to the task. They are provided by Millisecond Software
as htm pages and simple page elements and can be edited either by changing
the provided html files or directly under Editable Instructions.

Note: in order for the instructions to reflect alternative parameter settings,
some of the conditionalized code used in the htm files can be found in the script itself.

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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:

/allowPracticeRepeat:						true: practice can be repeated as often as indicated (default)
											false: practice cannot be repeated
										

/excludeStartTrialfromPerformanceMeasure:	true (1): performance during start trials that cannot be targets yet is not considered 
											for Block level performance analyses, e.g. for feedback purposes (default)									
											false (0): performance during start trials that cannot be targets yet IS considered for block performance analyses (default)									
										

/SOA:										Stimulus Onset Asynchrony (default: 3000ms) 																						
/stimulusPresentationtime:					the presentation time (in ms) of the stimuli (default: 500ms)										
										
																			
debugmode = 0								debugmode = 1: targetalerts are shown on screen, 
											debugmode = 0, no targetalerts are shown (default)


(in general: if levels of N are changed, adjustments need to be made to instructions and list.Nlevel)