A test-retest resting, and cognitive state EEG dataset during multiple subject-driven states

Area of Science:

• Neuroscience
• Cognitive Science
• Psychology

Background:

• Electroencephalogram (EEG) is a key tool for measuring brain activity.
• Understanding EEG test-retest reliability is crucial for clinical and research applications.
• Existing datasets often lack comprehensive behavioral measures or varied cognitive states.

Purpose of the Study:

• To create a robust, multi-session EEG dataset with detailed behavioral assessments.
• To facilitate research on the reliability and validity of EEG measurements.
• To enable investigation of short-term and long-term variability in brain activity and cognitive states.

Main Methods:

• Acquired EEG data from 60 participants across three sessions.
• Included resting states (eyes open/closed) and cognitive tasks (memory, music, subtraction).
• Collected extensive behavioral data on demographics, sleep, emotion, mental health, and mind wandering.

Main Results:

• The dataset captures electrophysiological and behavioral data at high temporal resolution.
• It allows for the analysis of both within-session and between-session variability.
• The data supports examination of changes in resting and cognitive states over time.

Conclusions:

• This open-access dataset provides a valuable resource for EEG research.
• It will aid in understanding the reliability and validity of EEG measures.
• The comprehensive nature of the data supports diverse research questions in neuroscience and psychology.