Materials for Pupillary Responses to Words That Convey a Sense of Brightness or Darkness

Experimental resources for the study "Semantic Pupil"
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Copyright 2015-2017 Sebastiaan Mathôt, Kristof Strijkers, JonathanGrainger
- [e-mail]- http://www.cogsci.nl/smathot
Table of contents=================
- About this repository- Running the experiments- Participant data- Running the analysis- License
About this repository=====================
This repository contains materials to accompany the followingmanuscript:
Mathôt, S., Strijkers, K., & Grainger, J. (in press). Pupillaryresponses to words that convey a sense of brightness or darkness.*Psychological Science*.
Running the experiments=======================
The experiments are placed in the `experiments` subfoler.
All experiments were conducted with[OpenSesame](http://osdoc.cogsci.nl/), but not all with the sameversion.
- 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
Participant data================
Eye-tracking data-----------------
The eye-tracking data for each experiment is located in`analysis/edf/[experiment name]`. This in `.edf` format, which is theformat used by the EyeLink eye tracker.
To run the analysis as described below, the `.edf` files need to beconverted to `.asc` files using the `edf2asc` utility that can bedownloaded 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 becreated.
Ratings data------------
The ratings data is located in `analysis/data-ratings`. This in standardcomma-separated values (`.csv`) format.
Running the analysis====================
Before analyzing the data, the eye-tracking data needs to be convertedas described above.
Analysis scripts and participant data are placed in the `analysis`subfolder.
IPython notebook----------------
For a quick example of how the analysis works, see this IPythonnotebook:
- [analysis/basic-analysis.ipynb](analysis/basic-analysis.ipynb)
Full analysis pathway---------------------
The analysis requires the standard numpy/ scipy stack, and[DataMatrix](https://github.com/smathot/python-datamatrix) and[EyelinkParser](https://github.com/smathot/python-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 mainanalyses.
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 youcan 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.
License=======
- Analysis and experimental code are released under a [GNU General Public License 3](https://www.gnu.org/copyleft/gpl.html).- Data and text are released under a [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/).
Note: This is a frozen snapshot of the following GitHub repository:

- https://github.com/smathot/semantic_pupil