DAMP Test Procedure

Technical Manual

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

Created: February 16, 2016

Last Modified: May 25, 2023 by K. Borchert (katjab@millisecond.com), Millisecond

Script Copyright © Millisecond Software, LLC

Background

This script implements a Dynamically Adjusted Motion Prediction Task (DAMP) similarly to the one described in Ullsperger & Crampon (2003).

This script implements 100% informative feedback (Experiment1).

NOTE: Ullsperger & Crampon (2003) kept the error rates constant for each participant (~40% error rate) by (dynamically) adapting the task difficulty of the task to each participant's ability. "Task difficulty" was operationalized solely as the time difference of arrival of the two balls at the finish line. No further details of the adjustment procedure are provided by U & C other than "To keep the error rate high during the first trials of the experiments, individual difficulty levels were determined in a training session (100 trials and only informative feedback) that was performed during the anatomical scans (p. 4309)."

Script DynamicallyAdjustedMotionPrediction_Baseline.iqjs implements an interweaved stairway procedure to assess individual Arrival Times Difference Thresholds. Script DynamicallyAdjustedMotionPrediction.iqjs (current one) uses the established Arrival Times Difference Threshold to keep error rate constant. Arrival Time Difference Threshold in this script: (roughly) the threshold at which participants start to guess with a 50/50 probability which ball reaches the finish line first.

References

Ullsperger, M. & Crampon v., D.Y. (2003). Error Monitoring Using External Feedback: Specific Roles of the Habenular Complex, the Reward System, and the Cingulate Motor Area Revealed by Functional Magnetic Resonance Imaging. The Journal of Neuroscience,23(10),4308–4314.

Duration

17 minutes

Description

Participants view 2 balls that travel towards a finish line starting from different screen positions at different speeds. One ball is assigned the role of 'base' (the arrival time of the base ball is kept constant across all trials in this script) and one ball is assigned the role of 'target' (the target is always faster than the base at the finish Line). Long before the balls reach the finish line, the balls disappear and participants have to predict which ball will first reach the finish line (=target). Smiley or frowny faces provide feedback for each prediction.

Procedure

• Script runs 120 DAMP trials with a base and target ball.
• The arrival time of the base at the finish line is kept constant in this script (default: 7000ms)
• The target is always the one arriving first at the finish line.
• arrival times for targets are calculated in such a way that a set proportion (default: 0.4) is chosen from
below the 'Arrival Time Difference Threshold' (randomly either 60%, 70% or 80% below threshold - selected with replacement)
and a set proportion (default: 0.6) is chosen from above the 'Arrival Time Difference Threshold'
(randomly either 60%, 70% or 80% above threshold - selected with replacement)
• Vertical screen positions of base and target balls are randomly assigned in such a way that each ball has a 50%
probability to be the top ball (actual frequencies might vary with the default set-up).
• Additionally, horizontal start positions (5%, 25%, 45% -> list.xpos1) are randomly assigned to base and target
with the constraint that they cannot be the same. Actual frequencies of the different starting position combinations
likely vary from participant to participant.

Stimuli

see section Editable Stimuli

Instructions

see section Editable Instructions

Summary Data

File Name: dynamicallyadjustedmotionprediction_summary*.iqdat

Data Fields

NameDescription
inquisit.version Inquisit version number
computer.platform Device platform: win | mac |ios | android
computer.touch 0 = device has no touchscreen capabilities; 1 = device has touchscreen capabilities
computer.hasKeyboard 0 = no external keyboard detected; 1 = external keyboard detected
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
atdThreshold Roughly the arrival time difference at which participant starts guessing
script DynamicallyAdjustedMotionPrediction_baseline.iqjs implements a procedure to
assess individual thresholds
propError Overall error proportion

Raw Data

File Name: dynamicallyadjustedmotionprediction_raw*.iqdat

Data Fields

NameDescription
build Inquisit version number
computer.platform Device platform: win | mac |ios | android
computer.touch 0 = device has no touchscreen capabilities; 1 = device has touchscreen capabilities
computer.hasKeyboard 0 = no external keyboard detected; 1 = external keyboard detected
date Date the session was run
time Time the session was run
subject Participant ID
group Group number
session Session number
blockcode The name the current block (built-in Inquisit variable)
blocknum The number of the current block (built-in Inquisit variable)
trialcode The name of the currently recorded trial (built-in Inquisit variable)
trialnum The number of the currently recorded trial (built-in Inquisit variable)
trialnum is a built-in Inquisit variable; it counts all trials run
even those that do not store data to the data file.
trialCount Counts the number of trials run
fixationDuration Stores the current fixation duration as selected from list.fixationdurations
xpos1 Stores the x-coordinate (in canvas width percentage) of the starting point of ball1
xpos2 Stores the x-coordinate (in canvas width percentage) of the starting point of ball2
basePosition 1 = base is top ball; 2 = base is bottom ball
targetPosition 1 = target is top ball (correct response is ball1); 2 = target is bottom ball (correct response is ball2)
atdThreshold Roughly the arrival time difference at which participant starts guessing
script DynamicallyAdjustedMotionPrediction_baseline.iqjs implements a procedure to
assess individual thresholds
aboveThreshold 0 = target arrival time is below threshold; 0 = target arrival time is above threshold
propThresholdDiff Increase/decrease of 25%, 50%, or 75% of Arrival Time Threshold
baselineArrivalTime The constant winning arrival time in ms (default: 7000)
targetArrivalTime The target arrival time (in ms)
arrivalTimeDifference Stores the current difference in arrival Times of Ball1 and Ball2 (in ms)
response The participant's response (scancode of response => 2 for 'ball 1' and 3 for 'ball 2')
responseText The response key pressed
correct The correctness of the response (1 = correct; 0 = incorrect)
latency The response latency (in ms) - measured from onset of trial
propError Overall error proportion

Parameters

The procedure can be adjusted by setting the following parameters.

NameDescriptionDefault
Design
atdThreshold Roughly the arrival time difference at which participant starts guessing
(set by DynamicallyAdjustedMotionPrediction_baseline.iqjs if batch script is run; otherwise set here)
script DynamicallyAdjustedMotionPrediction_baseline.iqjs implements a procedure to assess individual
thresholds
250
propError The targeted error proportion0.4
Position Parameters
xBar X-coordinate (in canvas width percentages) of the left top corner of the finish line90%
Timing Parameters
stimPresentation The presentation duration (in ms) of the moving balls1430
baselineArrivalTime The constant winning arrival time in ms7000
responseWindow Response window in ms1500
iti Intertrial interval (in ms) btw. response trial and feedback trial750
feedbackDuration Duration (in ms) of feedback presentation1000