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This study introduces a new dataset combining electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) to analyze brain activity during rest. The data allows researchers to explore the link between neural signals and spontaneous thoughts.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Data Science

Background:

  • Simultaneous electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) offer complementary temporal and spatial insights into neural activity.
  • Characterizing spontaneous mental experiences and their neural correlates remains a key challenge in cognitive neuroscience.

Purpose of the Study:

  • To introduce and describe a novel, multi-session simultaneous EEG-fMRI dataset.
  • To facilitate research on the relationship between brain activity, behavior, and subjective experience during wakeful rest.
  • To enable investigations into the reliability of EEG-fMRI findings across sessions.

Main Methods:

  • Acquired simultaneous EEG-fMRI data from 24 healthy adults across two sessions.
  • Included continuous performance task (CPT) responses, experience sampling of 13 thought dimensions, and mental health surveys.
  • Organized data in Brain Imaging Dataset Structure (BIDS) format, featuring artifact-removed EEG and high-temporal-resolution fMRI.

Main Results:

  • The dataset comprises approximately 1.33 hours of high-quality simultaneous EEG-fMRI data per participant.
  • Includes detailed behavioral and experiential data, allowing for rich correlational analyses.
  • Provides a robust foundation for studying neural dynamics during resting state and their link to cognition.

Conclusions:

  • This comprehensive dataset serves as a valuable resource for the neuroscience community.
  • Enables in-depth exploration of the neural basis of spontaneous thought and its variability.
  • Supports research on the test-retest reliability of multimodal neuroimaging measures.