Scientific data
May 23, 2025
Alia Seedat, Alex Lepauvre, Jay Jeschke et al.
5 citations
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.
Scientific data
May 21, 2026
Leonardo Novelli, Devon Stoliker, Tamrin Barta et al.
PsiConnect is a large-scale neuroimaging study that investigates how psilocybin affects brain activity and subjective experience depending on context. Sixty-two participants received a 19 mg dose of psilocybin and underwent functional, structural, and diffusion-weighted MRI, as well as EEG, before and after administration. Scans included resting-state and three naturalistic conditions: guided meditation, music listening, and movie watching. Half of the participants completed an 8-week meditation training program, allowing examination of interactions between meditation, psilocybin, and brain function. Multi-echo fMRI improved signal quality. Behavioral and self-report measures captured acute and long-term effects, with follow-ups up to one year. Data is openly shared to support future research.
Scientific data
May 29, 2026
Ling Liu, Oscar Ferrante, Tara Ghafari et al.
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.
Scientific data
May 7, 2026
Aya Khalaf, David Richter, Yamil Vidal et al.
An adversarial collaboration between proponents of the Global Neuronal Workspace theory and the Integrated Information Theory of consciousness produced a functional magnetic resonance imaging dataset from 118 participants. Participants viewed faces, objects, letters, and false fonts presented at three orientations and three durations (0.5, 1.0, 1.5 seconds) while identifying infrequent targets. Two categories were task-relevant and two were task-irrelevant in each block. The simple design makes the data broadly reusable for testing predictions from other theories of consciousness and for examining visual processing. Anonymized data, quality reports, demographics, behavioral performance, and eye-tracking data are publicly accessible.