An open multi-center MEG-EEG dataset for studying conscious visual perception.
Ling Liu, Oscar Ferrante, Tara Ghafari, Dorottya Hetenyi, Shujun Yang, Rony Hirschhorn, Urszula Gorska-Klimowska, Praveen Sripad, Fatemeh Taheriyan, Tanya Brown, Diptyajit Das, Kyle Kahraman, Niccolò Bonacchi, Michael Pitts, Liad Mudrik, Ole Jensen, Huan Luo, Lucia Melloni
Scientific data May 29, 2026 DOI: 10.1038/s41597-026-07350-9 via PubMed
Summary
AI-generated from the abstractA 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.
Study at a glance
| Characteristics | Adversarial collaboration Peer reviewed |
|---|---|
| Sample size | 100 |
| Population | 100 individuals (mean age 22.79±3.59 years, 54 female, all right-handed) across two research centers (UK and China) |
| Key finding | A standardized, multi-center dataset of MEG, EEG, eye-tracking, and structural MRI recordings was collected through an adversarial collaboration between advocates of two neuroscientific theories of consciousness. |
Abstract
Here, we present a large-scale, multi-center dataset of combined magnetoencephalographic (MEG) and electroencephalographic (EEG) recordings, along with eye-tracking data and high-resolution structural MRI (T1); complementing with iEEG and fMRI datasets that are shared in accompanying data papers. The data was obtained through an adversarial collaboration between advocates of two neuroscientific theories of consciousness: the Global Neuronal Workspace Theory and the Integrated Information Theory. The dataset includes recordings from 100 individuals (mean age 22.79 ± 3.59 years, 54 female, all right-handed) across two research centers (UK and China), using a standardized data collection protocol. During the experiment, participants were asked to perform a non-speeded Go/No-Go target detection task, during which they were exposed to visual stimuli from four distinct categories (faces, objects, letters, false fonts) presented at different orientations (front, left, right view), and for varying durations (0.5, 1.0, 1.5 s), under different task conditions. The quality of the data was assessed and organized according to the Brain Imaging Data Structure (BIDS). It is accompanied by extensive metadata to enhance reusability.