Psychopy SST Template

A complete PsychoPy + R solution for running and analyzing the Stop Signal Task (SST) following Verbruggen et al. (2019).

Stop Signal Task (SST) Template Repository

This repository contains all necessary resources for setting up and running the Stop Signal Task (SST) — a well-established paradigm in cognitive neuroscience for studying response inhibition and cognitive control.

🔗 GitHub Repository: Merluin/Psychopy_SST_template

Overview

This template includes:

• ✅ A PsychoPy3 implementation of the SST
• ✅ An R program to compute Stop Signal Reaction Time (SSRT)
  following the standardized procedures outlined in Verbruggen et al., 2019

Repository Structure

• PsychoPy3 SST Task
  .psyexp and supporting files for running the experiment in PsychoPy

• R Program for SSRT
  Scripts to preprocess data and compute SSRT metrics

Task Design

The SST consists of:

• Go trials: Respond as fast as possible to a green arrow indicating direction.
• Stop trials: Inhibit your response if a stop signal (e.g., "XX") appears after a short delay.

The Stop Signal Delay (SSD) is dynamically adjusted based on the participant’s performance to estimate the Stop Signal Reaction Time (SSRT).

Task Parameters

Parameter	Value / Description
Initial SSD	150 ms after go signal onset
SSD Range	50 ms to 650 ms
Go Stimulus	Green arrow (left or right)
Stop Signal	"XX" shown after variable SSD

Requirements

PsychoPy Task

• PsychoPy version 2022.1.4 or later

R Scripts

• Latest version of R (tested on 4.x)
• Optionally: RStudio for better usability

Installation

1. Run the PsychoPy Task

• Install PsychoPy
• Clone or download the repository
• Open SST.psyexp in PsychoPy
• Run the task

2. Analyze Data in R

• Install R from CRAN
• Open the R script(s) in the R Program for SSRT folder
• Follow in-script comments to:
  • Import task data
  • Clean responses
  • Compute SSRT

Customization

• In PsychoPy:

  • Modify trial durations and timing
  • Change response keys or stop signal format

• In R:

  • Adapt input format for your data
  • Extend analyses (e.g., condition-level SSRT, visualizations)

References

Verbruggen, F., Aron, A. R., Band, G. P., Beste, C., Bissett, P. G., Brockett, A. T., … & Boehler, C. N. (2019).
A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task.
eLife, 8, e46323.
🔗 https://doi.org/10.7554/eLife.46323

☕ The Coffee Machine Corner

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You’re also warmly invited to fork the repo, contribute, or reach out if you’re working on similar tools. Collaboration brews innovation!

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