An intracranial EEG dataset was collected from 38 epilepsy patients across three research centers as part of an adversarial collaboration testing Global Neuronal Workspace Theory and Integrated Information Theory. Participants viewed visual stimuli—faces, objects, letters, and false fonts—in three orientations and for three durations, performing a Go/No-Go target detection task. The dataset includes demographics, clinical information, electrode reconstructions, behavioral performance, and eye-tracking data, all converted to BIDS format. It is intended for reuse in consciousness science and vision neuroscience to investigate stimulus processing, target detection, and task-relevance.
A large-scale, multi-center dataset combines MEG, EEG, eye-tracking, and structural MRI recordings from 100 individuals (mean age 22.79, 54 female, all right-handed) across two research centers (UK and China). The data were collected through an adversarial collaboration between advocates of the Global Neuronal Workspace Theory and the Integrated Information Theory of consciousness. Participants performed a non-speeded Go/No-Go target detection task with visual stimuli from four categories (faces, objects, letters, false fonts) at different orientations and durations (0.5, 1.0, 1.5 s) under various task conditions. The dataset follows the Brain Imaging Data Structure (BIDS) and includes extensive metadata to enhance reusability.