Open multi-center intracranial electroencephalography dataset with task probing conscious visual perception

作者：Alia Seedat, Alex Lepauvre, Jay Jeschke, Urszula Górska, Marcelo Armendáriz, Katarina Bendtz, Simon Henin, Rony Hirschhorn, Tanya Brown, Erika Jensen, Csaba Kozma, David Mazumder, Stephanie Montenegro, Leyao Yu, Niccolò Bonacchi, Diptyajit Das, Kyle Kahraman, Praveen Sripad, Fatemeh Taheriyan, Orrin Devinsky, Patricia Dugan, Werner Doyle, Adeen Flinker, Daniel Friedman, Wendell Lake, Michael Pitts, Liad Mudrik, Mélanie Boly, Sasha Devore, Gabriel Kreiman, Lucía Melloni · 发表于：Scientific Data · 年份：2025 · DOI：10.1038/s41597-025-04833-z · 被引用次数：6 · 研究领域：EEG and Brain-Computer Interfaces、Neural dynamics and brain function、Functional Brain Connectivity Studies

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.