Wolf and Sheep Task

Technical Manual

Script Author: Katja Borchert, Ph.D. (katjab@millisecond.com), Millisecond

Created: January 13, 2023

Last Modified: January 02, 2025 by K. Borchert (katjab@millisecond.com), Millisecond

Script Copyright © Millisecond Software, LLC

Background

This script implements Millisecond's version of the Wolf and Sheep Task, a visual search task used to study agency attribution. The Millisecond script is based on Lisøy (2018).

Researchers can select to run the task with an absolute screen size to ensure that distances stay the same across devices. The default setup uses proportional sizing. Go to section Defaults for more information.

References

Lisøy, R.S. (2018). Seeing minds: a signal detection study of agency attribution in autism and psychosis. NTNU. (Dissertation)

Lisøy RS, Biegler R, Haghish EF, Veckenstedt R, Moritz S, Pfuhl G. Seeing minds - a signal detection study of agency attribution along the autism-psychosis continuum. Cogn Neuropsychiatry. 2022 Sep;27(5):356-372. doi: 10.1080/13546805.2022.2075721. Epub 2022 May 17. PMID: 35579601.

Lisøy, R.S., Pfuhl, G., Hope, W.N & Biegler, R. Seeing Minds: A Signal Detection Study of Agency Attribution in Autism and Psychosis downloaded from: https://osf.io/preprints/osf/6yn89 License: CC-By Attribution 4.0 International

Gao, T., Newman, G. E., & Scholl, B. J. (2009). The psychophysics of chasing: A case study 603 in the perception of animacy. Cogn Psychol, 59(2), 154-179. 604 doi:10.1016/j.cogpsych.2009.03.001

Duration

10 minutes

Description

Participants watch videos with 16 red balls (the 'wolves') and one yellow ball (the 'sheep') moving around the screen. The task is to decide whether the sheep is hunted ('stalked') by one of the wolves. If participant reply 'yes' to the question of whether 'the sheep was hunted', they are further asked to identify the hunting wolf by selecting the letter printed on the red ball that represents the 'hunting wolf'.

Procedure

(1) Practice:
- 2 warm-up trials (practice trials only run 10 wolves instead of 16)
- by default, the two videos are run in fixed sequence
1. video: no wolf
2. video: wolf (letter 'L')
In this script, participants get to watch the video again if they make a mistake for either the
'agency' and the 'identification' questions during practice

(2) Test:
- 50 videos (16 wolves)
- by default, the videos are presented in a fixed sequence
- half the videos present a wolf

Trial Sequence (Test)
-> get ready (2000)
-> video (until video is done running), about 5seconds for each
-> agency question: 'was the sheep being hunted?' until response (yes or no)
-> if YES: identification question: the 16 letters are presented in a 4x4 matrix in the center of the screen
and participants can select the letter. They can change their answer until they press the 'submit' button

-> if NO: start of next trial sequence

there is no performance feedback given during test

Stimuli

provided by Lisøy et al (2018) under the CC-By Attribution 4.0 International License:
https://osf.io/qaeyu/

Instructions

the instructions are not original to Lisøy et al (2018);
they are provided by Millisecond - can be edited under section 'Editable Instructions'

Summary Data

File Name: wolfandsheeptask_summary*.iqdat

Data Fields

NameDescription
inquisit.version Inquisit version number
computer.platform Device platform: win | mac |ios | android
startDate Date the session was run
startTime Time the session was run
subjectId Participant ID
groupId Group number
sessionId Session number
elapsedTime Session duration in ms
completed 0 = Test was not completed
1 = Test was completed
propCorrectAgency Proportion correct agency responses (out of 50 trials)
numberIdentityResponses Number of YES responses to agency question (= number of identity responses)
propCorrectID Proportion correct identity responses (out of numberIdentityResponses)
propCorrectIDTransformed Arcsine square root transformed propCorrectID (see )
meanCorrAgencyRT Average correct agency response time (in ms)
meanCorrIdRT Average correct identity response time (in ms)
hitRate Hitrate (= saying 'yes' when the sheep was hunted)
missRate Missrate (=saying 'no' when the sheep was hunted) - error response
faRate False alarm rate (= saying 'yes' when the sheep was NOT hunted) - error response
crRate Correct rejection rate (= saying 'no' when the sheep was NOT hunted)
zHitRate Calculates the z-score for the hitrate. Adjustments are made if the hitrate = 0 (increased to 0.005) or 1 (decreased to 0.995)*
zFARate Calculates the z-score for the false alarm rate. Adjustments are made if the FArate = 0 (increased to 0.005) or 1 (decreased to 0.995)*
dPrime 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 ('wolf present') were overall distinguished from noise ('wolf absent')
(d' = 0: chance performance; negative d-primes: participant treated noise as signals and signals as noise)
=> Lisøy et al target a d-prime around '1' to get enough false alarms for a meaningful c-value
(aka avoiding ceiling/floor effects)
c C-criterion in signal detection:The absolute value of c provides an indication of the strength of
the subject bias (Anderson, 2015)
=> Response bias c in this case 'reflects the participants’ propensity to perceive the wolf as present or absent'
(Lisøy et al)
=> negative when participant is more likely to report that signal ('wolf present')
is present (propensity towards seeing agency), positive for favoring caution ('wolf absent')
*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)

Raw Data

File Name: wolfandsheeptask_raw*.iqdat

Data Fields

NameDescription
build Inquisit version number
computer.platform Device platform: win | mac |ios | android
date Date the session was run
time Time the session was run
subject Participant ID
group Group number
session Session number
blockCode Name of the current block
blockNum Number of the current block
trialCode Name of the current trial
trialNum Number of the current trial
phase "practice" vs. "test"
trialCounterPerBlock TrialCounter for the current practice or test block
itemNumber The itemnumber of the currently presented video
video Stores the presented video
wolfPresent 0 = no wolf; 1 = wolf present
sheepCaught 0 = sheep is not caught by the wolf; 1 = sheep is caught by the wolf
actualWolf The letter assigned to the current wolf (if any)
Custom Dvs
agencyRsp "yes" or "no" (response to: )
selectedID The selected letter ID of the wolf
agencyAcc 1 = agency response was correct (answer to question "is the sheep being hunted?")
0 = agency response was incorrect
agencyRT Latency (in ms) of agency response; measured from onset of question "is the sheep being hunted?"
idAcc 1 = wolf identity was correctly identified (only relevant if participant chose 'yes' for agency response)
0 = wolf was not correctly identified
idRT Latency (in ms) of identity response (measure from onset of question until 'submit' button is selected)
Built-In Dvs
response The response of participant for the current trial
correct Correctness of response (1 = correct, 0 = error)
latency Response latency (in ms)
!!! the final trial data is recorded by trial.end

Parameters

The procedure can be adjusted by setting the following parameters.

NameDescriptionDefault
Color Parameter
canvasColor Display color of the actively used portion of the screen (the 'canvas')
if set to a color other than the screenColor, the active canvas
appears 'anchored' on the screen regardless of monitor size
black
screenColor Color of the screen not used by the canvas ('inactive screen')black
defaultTextColor Default color of text items presented on active canvaswhite
videoSize The proportional size of the video relative to active canvas
by default: covers the entire active canvas
100%
Timing Parameters
getReadyDuration Duration (in ms) of the get ready trials2000
feedbackDuration Duration (in ms) of the practice feedback stims1000