Discover datasets

This dataset comprises EEG recordings from 148 neurologically healthy adults performing an emotion processing and regulation task with static visual stimuli. Participants completed 240 trials in a 2×3 factorial design manipulating stimulus content (social vs. non-social) and regulation requirement (passive viewing of neutral or negative images, or cognitive reappraisal of negative images), with subsequent subjective ratings of arousal and valence. The study investigates discrepancies between self-reported and neurophysiological markers of socio-affective responses in lonely individuals.

Participants

148

Channels

69 (10-10)

Size

118 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings and behavioral data from 120 neurologically healthy adults who completed an emotion processing and regulation task during transcranial direct current stimulation (tDCS). Participants underwent two counterbalanced sessions (sham and active stimulation) while viewing static emotional images and performing either passive viewing or cognitive reappraisal. Stimulation was targeted to the dorsolateral prefrontal cortex using two between-subject alternative montages: left dlPFC (anode at F3) or right dlPFC (anode at F4). The study investigates how targeted neuromodulation of the dlPFC modulates affective response evaluation in individuals experiencing loneliness. This is a BIDS-formatted dataset derived from OpenNeuro (ds006861).

Participants

120

Channels

37 (10-10)

Size

53.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises continuous EEG, ECG, and EDA recordings from 63 participants who viewed and rated Streetview images of urban environments. Participants rated 56 different urban scenes on nine subjective scales (arousal, valence, dominance, stress, openness, safety, beauty, hominess, and fascination) while neural responses were recorded. The study investigates how different urban environmental elements influence subjective appraisals and neural processing, with semantic segmentation features extracted from stimuli to predict both behavioral ratings and event-related potentials.

Participants

63

Channels

66 (other)

Size

34.7 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises 64-channel EEG recordings with concurrent ECG and PPG measurements from 30 healthy young adults during resting state and a verbal working memory task. Participants performed digit span recall under four presentation modes (simultaneous, fast sequential, fast sequential with delay, and slow sequential), enabling investigation of neural oscillations and peripheral physiological responses during working memory encoding, maintenance, and retrieval. The dataset includes behavioral accuracy measures and trial-by-trial performance metrics.

Participants

30

Channels

63 (10-10)

Size

41.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

IACKD is a multimodal neurophysiological dataset combining electroencephalography (EEG) recordings with hand kinematics data collected during a task designed to investigate intention-action conflict. The dataset comprises raw EEG signals and synchronized kinematic measurements from participants performing motor tasks, providing a resource for studying the neural mechanisms underlying motor planning and conflict resolution.

Participants

15

Channels

26 (10-10)

Size

7.35 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings acquired during a sham neurofeedback experiment conducted in virtual reality, investigating how feedback valence modulates alpha-band activity during attentional tasks. Participants received positive, negative, or control feedback while performing an attentional task, with additional resting-state recordings (eyes open and closed). Data were collected using a 32-channel SynAmps RT system and converted to BIDS format.

Participants

36

Channels

29 (10-10)

Size

10.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

A neuroimaging dataset implementing the Visual Attribute-Specific Contextual Trajectory Paradigm 2.0, designed to investigate visual perception and contextual processing. This raw BIDS-formatted dataset provides neuroimaging data collected during a visual attribute task with contextual manipulations, supporting research into how the brain processes visual information within different contextual frameworks.

Participants

35

Size

11.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

The NeuroTechs Dataset for Stem Skills is an EEG neuroimaging dataset designed to investigate neural correlates of science, technology, engineering, and mathematics (STEM) skill acquisition and performance. The dataset contains electroencephalographic recordings from participants and is formatted according to the Brain Imaging Data Structure (BIDS) standard, facilitating standardized analysis and reproducibility in cognitive neuroscience research.

Participants

63

Channels

8 (10-10)

Size

1.39 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 24 dyads of participants engaged in collaborative rule learning and categorization tasks. Participants first negotiated rules for a 4-way categorization task, then performed the task while EEG was recorded, with pre- and post-test assessments on identical stimuli. The study investigates information alignment between interacting brains during collaborative learning.

Participants

24

Size

62.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

The RECAP-EEG dataset comprises resting-state electroencephalography recordings from 21 neurotypical undergraduate students collected before and after three different study conditions: active learning with retrieval practice and feedback, passive learning from personal notes, and a control condition. The study investigates neural correlates of learning processes in educational contexts using 32-channel EEG recordings sampled at 500 Hz with standardized electrode placement according to the 10–20 system.

Participants

21

Channels

31

Size

1.32 GB

Version

v1.0.0

Updated

Jul 10, 2026