Discover datasets

This dataset presents a multimodal collection of naturalistic fMRI, structural MRI, and EEG data from 52 healthy older Cantonese-speaking adults (over 65 years) listening to excerpts from 'The Little Prince' in Cantonese. It aims to address the underrepresentation of non-Indo-European languages and older populations in language neurobiology research, providing insights into brain-behavior relationships and healthy aging. The dataset includes rich behavioral, linguistic, and cognitive measures alongside detailed audio and text annotations.

Participants

52

Channels

64

Citations

3

Size

109 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains behavioral events and electrophysiological recordings from a hybrid spatial-navigation and free recall experiment conducted at the University of Pennsylvania (2021-2022). Participants performed a virtual courier task delivering items across a town, followed by recall testing. The experiment comprised two phases: read-only sessions for generating classifier training data, and closed-loop sessions where stimulus presentation timing was optimized based on real-time neural predictions of memory encoding. The dataset supports investigation of spatial memory dynamics and the efficacy of classifier-based closed-loop stimulation for memory enhancement.

Participants

34

Channels

128 (biosemi)

Citations

5

Size

1.30 TB

Version

v1.0.0

Updated

Jul 10, 2026

This stereoelectroencephalography (sEEG) dataset comprises intracranial recordings from neurosurgical patients passively listening to natural conversational speech. Participants heard 30-45 second passages of speech and answered comprehension questions, with data collected across 6 blocks of 7 passages each. The dataset includes depth electrodes and, for two patients, grid and strip electrodes, providing high-resolution neural activity during speech perception. USAGE RESTRICTIONS: These data may not be used for commercial purposes, including but not limited to use in any kind of training set for commercial machine learning applications. These data may not be used in any way that either in part or in whole disambiguates participant identity, including but not limited to attempts at 3D facial reconstruction.

Participants

10

Size

13.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains intracranial EEG (iEEG) recordings from 8 patients undergoing single pulse electrical stimulation, collected to characterize electrical stimulation-driven network interactions within the human limbic system. The data support investigations into connectivity and evoked responses in the human brain and were formatted according to the BIDS standard.

Participants

8

Citations

18

Size

19.5 GB

Version

v1.0.0

Updated

Aug 19, 2026

TNO (Task-Negative Oscillations) is an EEG dataset containing resting-state and task-based electroencephalography recordings. The dataset includes EEG data collected during cognitive tasks and resting-state conditions, organized in BIDS format with data files in EEGLAB format (.set/.fdt files) and accompanying metadata in BIDS-compatible formats (JSON, TSV). This dataset is designed to investigate neural oscillations and their relationship to task engagement and cognitive processing. The dataset comprises recordings from multiple subjects performing standardized cognitive tasks and resting-state sessions, with complete event annotations and electrode location information.

Participants

21

Channels

32 (10-10)

HED

v8.1.0

Size

7.25 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises multimodal physiological and behavioral recordings (EEG, EOG, ECG, EDA, and gaze tracking) collected during a semi-automated driving task designed to study trust in automation (TiA). Participants performed lane maintenance, following distance, and collision avoidance tasks under varying levels of autonomous driving assistance, with the aim of developing quantitative metrics that predict and track changes in operator trust. The research supports the development of psychophysiology-based indicators for real-time trust monitoring in human-autonomy interaction, relevant to military vehicle survivability and human factors research.

Participants

24

Channels

64 (10-10)

HED

v8.1.0

Size

43.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises intraoperative intracranial EEG recordings from 10 patients undergoing brain tumor resection in the perirolandic region. Median nerve somatosensory evoked potentials (SEP) were recorded simultaneously using two 4-contact ECoG electrode strips with different impedance characteristics (low impedance: 3.4 kΩ and high impedance: 6.9 kΩ) to investigate the efficacy of low-impedance electrodes for detecting high-frequency oscillations in clinical neurophysiology.

Participants

10

Citations

9

Size

1.20 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises continuous EEG recordings from 48 infants (5-10 months old) during passive viewing of relaxing videos, collected to establish reliability metrics for microstate analysis in infant populations. The study demonstrates microstate analysis methodology applied to infant EEG data and provides a tutorial resource for researchers interested in this analytical approach. Data were acquired using a 128-channel geodesic sensor net at 1000 Hz sampling rate.

Participants

48

Channels

129 (egi-geodesic)

Citations

22

Size

30.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings collected to investigate whether hypervigilance to social threats can be dissociated from altered perceptual decision-making in individuals experiencing loneliness. Event-related potentials and Drift Diffusion Modelling were used to examine the neural and cognitive mechanisms underlying social threat processing and decision-making in this population.

Participants

52

Channels

68 (10-10)

Citations

6

Size

19.9 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises high-density, dual-layer EEG, neck EMG, IMU acceleration, ground reaction force, and structural MRI-derived head model data from 32 young adult participants walking over uneven terrain and at varying speeds. Each participant completed two three-minute trials per condition along with a seated rest trial. The dataset is designed to support research on the neural and biomechanical correlates of walking balance and gait adaptation on irregular surfaces.

Participants

32

Channels

120 (other)

Citations

3

Size

62.5 GB

Version

v1.0.0

Updated

Aug 19, 2026