stroop-task-contrast-toolkit

https://github.com/rassiver/stroop-task-contrast-toolkit

Repository

README.txt

# Stroop Task Suite for PsychoPy  
## High- and Low-Contrast Versions with LSL Support  

**Developer**: Rasmus Åberg Lindell  
**Year**: 2024  
**License**: CC-BY-4.0
Contact: rassiver@hotmail.com  

For citation purposes, please use:  
"Custom Stroop implementation (Lindell, 2024) with LSL markers."

Description
!Version 2: Added backup experiments as contingencies, in case LSL markers do not transfer properly.
Earlier versions do not send pure strings, therefore, some recording software might use default fault codes.

PsychoPy-based Stroop tasks with integrated LabStreamingLayer (LSL) for neurophysiology synchronization:

High Contrast (HC): Black background with saturated colors

Low Contrast (LC): Gray or Black background with desaturated colors

Configured for compatibility with EEG/fNIRS systems (e.g., NIRx, BrainVision).
---------------------------------------------------------------------------------
Stroop Task Variants
Paradigm Name	Contrast	Key Features			Trials	Files
Standard	HC or LC	- Performance feedback (✓/✗)	8/blk	Stroop_feedback_HC/LC.py
				- Fixed 500ms ITI
		
Randomized ITI	HC or LC	- No feedback			8/blk	Stroop_HC/LC_rd_ITI.py
				- Jittered ITI (800-1200ms)
				- fMRI/EEG optimized
		
Extended	HC or LC	- Mixed block lengths (8 & 15)	92 tot	Stroop_HC/LC_rd_ITI-long.py
				- Longer neutral periods
		
Merged Design	Both		- Combined HC/LC		184 tot	Merge_HC_LC_rd_BLOCK.py
				- Smart block sequencing
				- Dual contrast analysis
		
Key:
HC = High Contrast, LC = Low Contrast, blk = block, tot = total
----------------------------------------------------------------------------------
Feature Comparison:

Feature			Standard	Random ITI	Extended	Merged
Feedback		✓		✗		✗		✗
ITI Type		Fixed		Random		Random		Random
Block Lengths		8		8		8 & 15		8 & 15
Contrasts per Run	Single		Single		Single		Both
Best For		Behavior	EEG/fMRI	fNIRS		Multi-modal
----------------------------------------------------------------------------------

------------------

Dependencies
python
pylsl >= 1.16.1  # LSL communication
pandas >= 1.3.0  # Data handling
numpy >= 1.21.0  # Numerical operations
------------------

Usage
Run in PsychoPy:

LSL Integration:

Stream name: StroopMarkers/Stroopmarkers2

Data Output:

Raw trial-by-trial data (.csv)

Summary statistics (accuracy, RTs, Stroop effect)

bibtex

@software{Lindell_Stroop_Contrast_Toolkit_2024,
  author = {Lindell, Rasmus Åberg},
  title = {Stroop Task Contrast Toolkit},
  year = {2024},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/rassiver/Stroop-task-contrast-toolkit}},
  commit = {main},
  url = {https://github.com/rassiver/Stroop-task-contrast-toolkit/tree/main},
  note = {10.5281/zenodo.15306699}
  keywords = {psychopy, stroop-task, cognitive-psychology, neuroimaging, lsl},
  abstract = {A modular PsychoPy implementation of Stroop tasks with high/low contrast variants and LabStreamingLayer integration. Contains four experimental paradigms: Standard Feedback, Randomized ITI, Extended Protocol, and Merged Design. Developed for EEG/fNIRS/fMRI compatibility.},
  version = {1.0},
  license = {CC-BY-4.0}
}

APA
Åberg Lindell, R. (2025). Stroop Task Suite for PsychoPy: High- and Low-Contrast Versions with integrated LabStreamingLayer (LSL) for neurophysiology synchronization (Version 1). Zenodo. https://doi.org/10.5281/zenodo.15284374

Owner

Citation (CITATION.cff)

cff-version: 1.2.0
message: "Please cite this software using these metadata."
title: "Stroop Task Contrast Toolkit"
version: "2.0.0"
authors:
  - given-names: "Rasmus Åberg"
    family-names: "Lindell"
    email: "rassiver@hotmail.com"
license: "CC-BY-4.0"
doi: "10.5281/zenodo.15306699"
repository-code: "https://github.com/rassiver/Stroop-task-contrast-toolkit"
keywords:
  - "stroop"
  - "psychopy"
  - "neuroimaging"
  - "lsl"
  - "cognitive-psychology"
abstract: "Modular PsychoPy implementation of Stroop tasks with high/low contrast variants and LSL integration. Contains four experimental paradigms for behavioral and neuroimaging studies."

GitHub Events