Copyright 2015-2023 Sebastiaan Mathôt, Kristof Strijkers, Jonathan Grainger

• s.mathot@cogsci.nl
• http://www.cogsci.nl/smathot

• About this repository
• Running the experiments
• Participant data
• Running the analysis
• License

This repository contains materials to accompany the following manuscript:

Mathôt, S., Strijkers, K., & Grainger, J. (2017). Pupillary responses to words that convey a sense of brightness or darkness. Psychological Science. https://doi.org/10.1177/0956797617702699

The experiments are placed in the experiments subfoler.

All experiments were conducted with OpenSesame, but not all with the same version.

• visual experiment: 2.9.6 (with EyeLink plugins, which need to be installed separately)
• ratings experiment: 3.0.0
• auditory experiment: 3.1.0
• valence-control experiment: 3.1.3

The eye-tracking data for each experiment is located in analysis/edf/[experiment name]. This in .edf format, which is the format used by the EyeLink eye tracker.

To run the analysis as described below, the .edf files need to be converted to .asc files using the edf2asc utility that can be downloaded for free from the SR Research forum (registration required)

The .asc files then need to be placed in a folder called analysis/data-pupil-asc/[experiment name]. This folder needs to be created.

The ratings data is located in analysis/data-ratings. This in standard comma-separated values (.csv) format.

Before analyzing the data, the eye-tracking data needs to be converted as described above.

Analysis scripts and participant data are placed in the analysis subfolder.

For a quick example of how the analysis works, see this IPython notebook:

• analysis/basic-analysis.ipynb

The analysis requires the standard numpy/ scipy stack, and DataMatrix and EyelinkParser.

First, parse the ratings data by running:

python3 analyze-ratings.py

This will create a file called ratings.csv, which is used for the main analyses.

Next, run the full analysis for the visual experiment:

python3 analyze-pupil.py --auditory @full

And for the auditory experiment:

python3 analyze-pupil.py --visual @full

And for the control experiment:

python3 analyze-pupil.py --control @annotated_valence_plot

Various other analyses can be performed as well. The logic is that you can execute a function in one of the analysis modules by passing @[function name] as argument.

During the analysis, cache files are created. To start from scratch, pass the --clear-cache argument.

Notes:

• térébrant was misspelled and therefore removed from the analysis.
• pénombre occurred twice in the stimulus list of the pupillometry experiment.

• Analysis and experimental code are released under a GNU General Public License 3.
• Data and text are released under a Creative Commons Attribution-ShareAlike 4.0 International License.