A test-retest resting, and cognitive state EEG dataset during multiple subject-driven states
DOI: 10.1038/s41597-022-01607-9
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Summary
This paper introduces a comprehensive test-retest electroencephalogram (EEG) dataset designed to address the scarcity of high-quality, open-access EEG data for investigating brain function and methodological reliability. The study was motivated by the need to assess the stability of EEG measures during both resting and subject-driven cognitive states, as well as to explore the relationship between electrophysiological signals and spontaneous mental fluctuations. Unlike many existing datasets that focus solely on resting states or externally driven tasks, this resource captures continuous, self-generated cognitive states, enabling researchers to evaluate the reproducibility of EEG features such as power spectrum, functional connectivity, and network construction across short-term (within 90 minutes) and long-term (one month) intervals. The dataset comprises EEG and behavioral data from 60 undergraduate participants (mean age 20.01 years) recorded across three sessions. Each session included five distinct states: eyes-open resting, eyes-closed resting, and three subject-driven cognitive tasks (memory retrieval, silent music singing, and serial subtraction). EEG signals were acquired using 63 or 64 Ag/AgCl active electrodes at a 500 Hz sampling rate. To account for dynamic spontaneous brain fluctuations, the study collected extensive behavioral assessments, including the Self-rating Anxiety Scale, Self-rating Depression Scale, Epworth Sleeping Scale, Amsterdam Resting-State Questionnaire, Karolinska Sleepiness Scale, Positive and Negative Affect Schedule, and the Mini New York Cognition Questionnaire. These questionnaires were administered repeatedly to monitor changes in sleep, emotion, mental health, and the content of self-generated thoughts. Technical validation analyses revealed that participants’ anxiety, depression, and daytime sleepiness levels remained stable over the one-month interval. Similarly, subjective sleepiness and affect scores did not significantly change across the three experimental sessions. However, mind-wandering content, as measured by the Amsterdam Resting-State Questionnaire, showed significant variance; specifically, participants reported significantly less "planning" and more "verbal thought" in the third session compared to the first. Analysis of the Mini New York Cognition Questionnaire indicated that while the content of self-generated thoughts varied between eyes-closed and subtraction states, the overall variance across sessions was consistent with the nature of mind wandering. Notably, previous work using this dataset found that the mental subtraction state exhibited the highest reproducibility among the cognitive tasks. The significance of this dataset lies in its utility for validating EEG-based methods and decoding subject-driven cognitive states. By providing both electrophysiological data and rich behavioral metadata, it allows researchers to investigate the reliability of EEG measures and the correspondence between mental states and neural activity. The data is publicly available in Brain Imaging Data Structure (BIDS) format on OpenNeuro, facilitating reproducibility and further exploration of intra- and inter-session variability in brain function. This resource supports the development of robust EEG-based classifiers and contributes to a deeper understanding of the functional significance of EEG generation during naturalistic cognitive processes.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 11 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
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- Empirical Findings: physiological data
- Methodological Resource: validation psychometrics