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Lookup NU author(s): Csaba Kozma
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2025.We introduce an intracranial EEG (iEEG) dataset collected as part of an adversarial collaboration between proponents of two theories of consciousness: Global Neuronal Workspace Theory and Integrated Information Theory. The data were recorded from 38 patients undergoing intracranial monitoring of epileptic seizures across three research centers using the same experimental protocol. Participants were presented with suprathreshold visual stimuli belonging to four different categories (faces, objects, letters, false fonts) in three orientations (front, left, right view), and for three durations (0.5, 1.0, 1.5 s). Participants engaged in a non-speeded Go/No-Go target detection task to identify infrequent targets with some stimuli becoming task-relevant and others task-irrelevant. Participants also engaged in a motor localizer task. The data were checked for its quality and converted to Brain Imaging Data Structure (BIDS). The de-identified dataset contains demographics, clinical information, electrode reconstruction, behavioral performance, and eye-tracking data. We also provide code to preprocess and analyze the data. This dataset holds promise for reuse in consciousness science and vision neuroscience to answer questions related to stimulus processing, target detection, and task-relevance, among many others.
Author(s): Seedat A, Lepauvre A, Jeschke J, Gorska-Klimowska U, Armendariz M, Bendtz K, Henin S, Hirschhorn R, Brown T, Jensen E, Kozma C, Mazumder D, Montenegro S, Yu L, Bonacchi N, Das D, Kahraman K, Sripad P, Taheriyan F, Devinsky O, Dugan P, Doyle W, Flinker A, Friedman D, Lake W, Pitts M, Mudrik L, Boly M, Devore S, Kreiman G, Melloni L
Publication type: Article
Publication status: Published
Journal: Scientific Data
Year: 2025
Volume: 12
Issue: 1
Online publication date: 23/05/2025
Acceptance date: 14/03/2025
Date deposited: 10/06/2025
ISSN (electronic): 2052-4463
Publisher: Nature Research
URL: https://doi.org/10.1038/s41597-025-04833-z
DOI: 10.1038/s41597-025-04833-z
Data Access Statement: The Matlab code used to run the experiment is available at https://github.com/Cogitate-consortium/cogitateexperiment-code. The code implementing the preprocessing pipeline and analysis scripts is accessible at https://github.com/Cogitate-consortium/iEEG-data-release51. All code is implemented in Python using MNE-python v.1.752 and Matlab. The README file provides an overview of the codebase and instructions on how to set up the environment. While the README offers an overall guide, we recommend that users consult the Jupyter notebook (ieeg-data-release.html) available in the repository for detailed usage instructions. This notebook showcases how to download the data from our repository, implement the described analyses, and provides additional information on interacting with the dataset, including selecting specific conditions and customization options. Extensive information about the experimental paradigm, recording modalities: https://cogitate-consortium.github.io/cogitate-data/
PubMed id: 40410191
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