A test-retest resting, and cognitive state EEG dataset during multiple subject-driven states.
Yulin WangWei DuanDebo DongLihong DingXu LeiPublished in: Scientific data (2022)
Here we present a test-retest dataset of electroencephalogram (EEG) acquired at two resting (eyes open and eyes closed) and three subject-driven cognitive states (memory, music, subtraction) with both short-term (within 90 mins) and long-term (one-month apart) designs. 60 participants were recorded during three EEG sessions. Each session includes EEG and behavioral data along with rich samples of behavioral assessments testing demographic, sleep, emotion, mental health and the content of self-generated thoughts (mind wandering). This data enables the investigation of both intra- and inter-session variability not only limited to electrophysiological changes, but also including alterations in resting and cognitive states, at high temporal resolution. Also, this dataset is expected to add contributions to the reliability and validity of EEG measurements with open resource.
Keyphrases
- working memory
- functional connectivity
- resting state
- heart rate
- mental health
- transcranial direct current stimulation
- heart rate variability
- optical coherence tomography
- minimally invasive
- high intensity
- depressive symptoms
- blood pressure
- big data
- autism spectrum disorder
- machine learning
- magnetic resonance imaging
- deep learning
- magnetic resonance
- single molecule
- data analysis
- borderline personality disorder