Discover datasets

An EEG study investigating the effects of episodic future thinking on temporal discounting behavior. Participants generated descriptions of future events and subsequently used mental imagery of these events as cues during intertemporal choice tasks, with concurrent measurement of imagery vividness. This dataset provides neurophysiological recordings during decision-making processes influenced by prospective cognition.

Size

16.1 GB

Updated

Jun 18, 2026

…https://github.com/ncclabsustech/Chinese_reading_task_eeg_processing. ## Experiment Procedures Participants…

Citations

24

Size

696 GB

Updated

Jun 26, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on002312-blue…

Size

35.0 GB

Updated

Jun 21, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005007-blue…

Size

7.99 GB

Updated

Jun 26, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on002908-blue…

Citations

1

Size

58.3 GB

Updated

Jun 21, 2026

This dataset comprises synchronized electroencephalogram (EEG), electrocardiogram (ECG), and pupillography recordings from 75 participants (36 young and 39 older adults) during auditory cued reaction time tasks and passive listening conditions. Participants performed a simple reaction time task and a go/no-go task, with EEG acquired at 500 Hz using 64 scalp electrodes, ECG recorded bipolarly from chest electrodes, and pupil data sampled at 240 Hz. The dataset is designed to investigate age-related differences in neural, cardiac, and pupillary responses during cognitive and perceptual decision-making tasks.

Citations

29

Size

21.5 GB

Updated

Jun 22, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004660-blue…

Size

7.24 GB

Updated

Jun 25, 2026

This dataset comprises stereoelectroencephalography (sEEG) recordings from patients performing a forced two-choice response task, collected in the epilepsy monitoring unit at Oregon Health & Science University. The data extends characterization of movement-related neural oscillations using intracranial electrode recordings, providing insights into canonical motor-related activity patterns across distributed brain regions.

Size

14.2 GB

Updated

Jun 24, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004075-blue…

Size

7.39 GB

Updated

Jun 23, 2026

BCIComp2020UpperLimb is a preprocessed EEG dataset from BCI Competition 2020 Track 4 containing motor imagery recordings of three upper-limb grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. The dataset comprises 60-channel EEG data sampled at 250 Hz with 450 trials per subject (150 trials per session × 3 sessions), designed to evaluate session-to-session transfer learning in brain-computer interface applications. Data were preprocessed with 60 Hz notch filtering and cue-aligned epoching, with the 4-second motor imagery window extracted for analysis.

Size

795 MB

Updated

Jun 23, 2026