Martin Szinte¹, Dominik R. Bach², Dejan Draschkow³, Oscar Esteban⁴, Benjamin Gagl⁵, Rémi Gau⁶, Klara Gregorova⁷, Sina Kling¹, Sourav Kulkarni², Julia-Katharina Pfarr^6,8; ¹Institut de Neurosciences de la Timone, CNRS, Aix-Marseille Université, Marseille, France, ²University of Bonn, Transdisciplinary Research Area “Life & Health”, Hertz Chair for Artificial Intelligence and Neuroscience, Bonn, Germany, ³Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, ⁴Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵Self-Learning Systems Lab, University of Cologne, Cologne, Germany, ⁶Neuro Data Science ORIGAMI Laboratory, McConnell Brain Imaging Centre, Faculty of Medicine, McGill University, Montréal, Canada, ⁷Department of Psychology and Sports Sciences, Goethe University, Frankfurt am Main, Germany, ⁸Philipps-University Marburg, Department of Psychology, General and Biological Psychology, Marburg, Germany

The Brain Imaging Data Structure (BIDS) is an extensive community effort to establish data and metadata management standards. Due to its enormous success in human brain imaging research, numerous extensions have been developed. Here, we present Eye-Tracking-BIDS, an extension to BIDS for gaze position and pupil data. This community-driven extension aims to enhance practices and transparency within the eye-tracking community, as well as to facilitate the effective integration of eye-tracking data within fMRI, EEG, MEG, and behavioral standardized datasets. It includes standardization of raw synchronous gaze position and pupil data, asynchronous model parameters and trigger messages, as well as detailed metadata information. Compliance with the Eye-Tracking-BIDS by the concerned research community will foster the development of efficient, robust, open, and automatized BIDS-Apps for pre- and post-processing of eye-tracking data, thus enhancing reproducibility and replicability in the field.