Research project on gaze typing and its effect on the pupil diameter. Development of a virtual keyboard, usable with Tobii Pro Nano Eyetracker.

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This is a repository containing a script for matching neuronal recordings together as coming from the same putative unit or not

A parser for EyeLink data files, built on python-datamatrix. The code base is by Mathot, this fork makes it a proper, tested and runnable package.

Statistics project in R about time spent, relating data to current and past issues. Our data source is the OWID website where we collected data from the data tables.

A scientific utility designed for preprocessing, visualizing, and analyzing raw pupillometry data, configured by default for data exported from the iMotions platform.

Chang & Tang et al., Nature (2025), An open-source implementation of a real-time pupil tracking and closed-loop control system for neuroscience experiments

Pupil size tracking pipeline based on PupilSense

A set of functions to control luminance of colored images.

Preprocess and plot pupil diameter data

A GUI enabled toolbox for analysis of pupil data supporting SMI and Tobii eye tracking data

Computational modeling pipeline integrating pupillometry, behavioral data, and drift diffusion models (DDM) to understand the relationship between brain arousal and decision-making processes.

Preprocessing and analysis for pupillometry data

The pupillometryAnalyzer script can be used to analyse pupillometry raw data saved in a wks-file. It analyzes the time-series of one or both eyes and creates informative csv- and png-outputs that can be used for further statistical analysis.

R functions for processing pupillary light reflex (PLR) recordings — artifact removal, feature extraction, and batch analysis

This project provides an end-to-end solution for pupil diameter estimation using accessible hardware (like webcams) and deep learning techniques.

Pupil reactivity to brief sounds.

Online Material for Vidal et al. (2024). Cholinergic-related pupil activity reflects level of emotionality during motor performance. EJN, 59(9):2193–2207.

🩺 This project aims to detect stress state based on Pupillometry 👀 signals analysis with a deep learning model.

Creation of a data collection system with real-time inference and collection