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Related Experiment Video

Updated: May 13, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

Topographical Estimation of Visual Population Receptive Fields by fMRI

Published on: February 3, 2015

An open-access multi-site fMRI dataset for investigating conscious visual perception.

Aya Khalaf1, David Richter2,3, Yamil Vidal2

  • 1Department of Neurology, Yale School of Medicine, New Haven, CT, USA.

Scientific Data
|May 11, 2026
PubMed

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Summary

This study provides a reusable fMRI dataset from 118 participants to test theories of consciousness and visual processing. The data, including behavioral and eye-tracking metrics, are available in Brain Imaging Data Structure format with analysis code.

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Psychology

Background:

  • Consciousness research seeks to differentiate between competing theories like the Global Neuronal Workspace theory (GNWT) and Integrated Information Theory (IIT).
  • Existing datasets may lack the specific design or comprehensive data required for direct theoretical arbitration.

Purpose of the Study:

  • To present a novel, reusable functional magnetic resonance imaging (fMRI) dataset designed to arbitrate between the GNWT and IIT.
  • To facilitate research in consciousness and visual processing through accessible, well-documented data.

Main Methods:

  • Collected fMRI data from 118 participants performing a visual stimulus identification task.
  • Utilized suprathreshold visual stimuli across four categories, three orientations, and three durations, with task-relevance manipulated.

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Last Updated: May 13, 2026

Topographical Estimation of Visual Population Receptive Fields by fMRI
06:02

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Published on: October 20, 2023

  • Anonymized and converted data to Brain Imaging Data Structure (BIDS) format, including quality reports, demographics, behavioral, and eye-tracking data.

    • Main Results:

    • The dataset is structured for broad reusability in testing consciousness theories and exploring visual processing.
    • Provided accompanying code for data preprocessing and analysis, enhancing accessibility and utility.

    Conclusions:

    • This dataset offers a valuable resource for researchers investigating the neural correlates of consciousness and visual perception.
    • The adversarial collaboration design and BIDS format ensure the data's robustness and ease of integration into diverse research pipelines.