An open-access multi-site fMRI dataset for investigating conscious visual perception.
Aya Khalaf, David Richter, Yamil Vidal, Urszula Gorska-Klimowska, Rony Hirschhorn, Diptyajit Das, Kyle Sinan Taylan Kahraman, Praveen Sripad, Fatemeh Taheriyan, Liad Mudrik, Michael Pitts, Hal Blumenfeld, Floris P De Lange, Niccolò Bonacchi, Tanya Brown, Lucia Melloni
Scientific Data May 7, 2026 DOI: 10.1038/s41597-026-07377-y (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Experimental study Peer reviewed |
|---|---|
| Sample size | 118 |
| Population | Human participants |
| Key findings | The dataset is designed to arbitrate between the Global Neuronal Workspace theory and the Integrated Information Theory of consciousness. |
Abstract
We present a functional magnetic resonance (fMRI) dataset collected as part of an adversarial collaboration aimed at arbitrating between the Global Neuronal Workspace theory (GNWT) and the Integrated Information Theory (IIT) of consciousness. Participants (N = 118) were presented with suprathreshold visual stimuli belonging to four different categories (faces, objects, letters, false fonts) with three orientations (front, left, right view), and three durations (0.5, 1.0, 1.5 seconds). Participants were asked to identify infrequent targets that changed in each block, thereby rendering two categories task-relevant and two task-irrelevant. The simplicity of the experimental design and of the task given to the participants ensures that these data are broadly reusable. Besides testing predictions from other theories of consciousness, these data can be used to examine various aspects of visual processing. The anonymized data were converted to Brain Imaging Data Structure (BIDS), and can be easily accessed through a web platform or an API. The dataset contains quality reports, demographics, behavioral performance, and eye-tracking data. We also provide code for preprocessing and analyzing the data.