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BIDS-structured resting-state electroencephalography (EEG) data extracted from an experimental paradigm.

Christoffer Hatlestad-Hall1, Trine Waage Rygvold2, Stein Andersson2

  • 1Department of Neurology, Oslo University Hospital, Oslo, Norway.

Data in Brief
|November 25, 2022
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Summary

This study presents a new, publicly available dataset of electroencephalography (EEG) recordings from 111 healthy individuals. The comprehensive dataset supports advanced analyses in cognitive neuroscience and machine learning.

Keywords:
BIDSEEGElectroencephalographyNeurophysiologyNeuropsychological assessmentPreprocessingResting-state

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Area of Science:

  • Neuroscience
  • Data Science
  • Machine Learning

Background:

  • Electroencephalography (EEG) provides insights into brain activity.
  • A large dataset is crucial for advancing neuroscience research.

Purpose of the Study:

  • To introduce a comprehensive, publicly available EEG dataset.
  • To facilitate research in cognitive neuroscience, data science, and machine learning.

Main Methods:

  • Recorded resting-state EEG data from 111 healthy subjects using 64 electrodes.
  • Performed a subset of recordings (n=42) for test-retest reliability.
  • Collected neuropsychological test scores for each subject.
  • Organized data according to the Brain Imaging Data Structure (BIDS).

Main Results:

  • A large, well-organized EEG dataset is now publicly available.
  • The dataset includes resting-state EEG, test-retest reliability measures, and neuropsychological data.
  • Data structure adheres to BIDS for broad usability.

Conclusions:

  • This dataset serves as a valuable resource for researchers in multiple fields.
  • It enables advanced analyses such as functional connectivity and graph theory.
  • The dataset supports studies on brain dynamics and cognitive function.