EEG-fMRI Brain Connectivity Matrices from Simultaneous 1.5T to 7T Studies

Jonathan Wirsich and the University of Geneva provide a connectome dataset for the 2021 NeuroImage publication 'The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T'. The dataset contains static connectivity matrices derived from simultaneous EEG and fMRI recordings, with data structured by subject, session, atlas, and EEG frequency band. It includes connectivity measures for fMRI and multiple EEG metrics across five frequency bands.

Use Cases

• Investigating the reproducibility of EEG-fMRI connectivity relationships across different magnetic field strengths based on the 1.5T to 7T study design.
• Comparing brain network properties derived from different EEG connectivity measures (iCoh, hilb_Ortho, hilb_noOrtho) mentioned in the description.
• Analyzing static functional connectivity across different brain atlases (Desikan or Destrieux) provided in the dataset structure.
• Studying frequency-specific brain network interactions based on the EEG bands (delta, theta, alpha, beta, gamma) included in the data.

Strengths

• Includes data from simultaneous EEG-fMRI recordings, a technically challenging acquisition method.
• Provides connectivity data across five standard EEG frequency bands (delta, theta, alpha, beta, gamma).
• Offers multiple EEG connectivity measures (iCoh, hilb_Ortho, hilb_noOrtho) for comparative analysis.
• Uses two established brain atlases (Desikan and Destrieux) for region parcellation.

Limitations

• Row count and overall dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred from the provided MATLAB structure description after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Geneva, associated with the publication by Wirsich et al. 2021 in NeuroImage.

Collection Method

Simultaneous EEG-fMRI recordings, likely from human subjects, processed into static connectivity matrices.