Replication and extension of experiments examining the effects of cognitive performance on cognitive control using Stroop and other tasks while varying body posture. Original Stroop body posture experiments that are part of this replication efforts are from:
Experiments and data analysis workflows originally developed
Summer 2021 using a baseline
Ubuntu 20.04 LTS Focal Fossa Desktop
distribution. The bootstrap subdirectory contains
scripts of all additional packages and libraries installed into
the base Ubuntu 20.04 install. The experiments performed
in this project make use of the
Psychtoolbox-3
and the
PsychoPy 3
python library bindings of the psycho toolbox. We used
the NeuroDebian
distribution to setup Psychtoolbox and additional tools.
On a clean Ubuntu 20.04 desktop installation, the bootstrap script can be run to install the tools and libraries used in this project:
$ cd bootstrap
$ ./bootstrap-ubuntu-20.04.sh
Any Linux distribution will probably work fine for this project, as long as the tools or equivalents shown in the bootstrap script are installed and available.
The project bootstrap installs the Psychtoolbox and the PsychoPy
python AIP of the toolbox. Experiments for subject can be
run in the exp subdirectory. To run the stroop-replication
experiment, do the following
$ cd exp
$ /usr/bin/python3 stroop-replication.py
All project products and data analysis workflow may be reproduced from this project. The project workflow performs all steps from the collected raw subject experiment data files to final paper and manuscript products. The general workflow is to
- Perform data cleaning and data tidying of collected raw subject data files for more detailed analysis.
- Generate table products summarizing results and for use in project papers and documents.
- Generate figure / visualization products to visualize important results and analysis.
- Create papers and documents that incorparate figures and tables, and also using literate programming tools to allow directly for code snippts and execution in final documents.
The complete project workflow may be reproduced using the following commands from the top level project directory
$ make clean
$ make
This will change into each subdirectory and perform a recursive make to generate the products of the project workflow in the order given above. You may generate and individual product products by changing into the directory and building it. For example, to recreate all data cleaning and data tidying steps, make the data directory
$ cd data
$ make
This project follows princiiples of reproducible research and open science. A few good general resources to learn more about the principles and best practices of open reproducable research:
- What are the principles of reproducable research?
- Erik Gundersen, O. (2021). The fundamental principles of reproducibility. Philosophical Transactions of the Royal Society A, 379(2197), 20200210.
- Alston, J. M., & Rick, J. A. (2021). A Beginner’s Guide to Conducting Reproducible Research. Bulletin of the Ecological Society of America, 102(2), 1-14.
- What is open science?
This project repository strives to support reprodcible research and open science in many of the ways outlined in the above resources.
- The project code is open source, all code used for data analysis and collecting data is stored and viewable in this open repository.
- This project data is open data / open access. All raw data is collected in this project so that reanalysis and replication from collected data may be performed by any researcher.
- Documentation of software tools, versions and environments is part of this repository so that anyone may recreate the environemnt and (re)run all of the experiments, tools and data analysis collected in this project.
- This project repository strives for a reproducible workflow. No data analysis products or tools are performed by hand. All parts of the workflow of this project, from the raw data to final papers, can be fully reproduced by running the project workflow contained in this repository.