Discover datasets

This multimodal neuroimaging dataset comprises task-based and resting-state fMRI, structural MRI, and EEG recordings from 52 healthy older Cantonese speakers (mean age 69 years) listening to naturalistic speech from 'The Little Prince' in Cantonese. The dataset includes comprehensive behavioral assessments, detailed linguistic annotations with time-aligned speech segmentation and prosodic features, and natural language processing-derived predictors. This resource addresses a significant gap in language neuroscience by providing robust neuroimaging data from an underrepresented demographic and non-Indo-European language population.

Participants

52

Channels

64

Citations

2

Size

109 GB

Version

v1.0.0

Updated

Jul 10, 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

4

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

13.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings from 8 patients during single-pulse electrical stimulation of the limbic system. The data were collected to investigate electrical stimulation-driven network interactions in human brain circuits, with stimulation parameters of 200 microseconds duration, biphasic waveform, and 6 mA amplitude (4 mA for one subject). The dataset is organized according to BIDS specification and includes raw iEEG data with associated metadata and event timing information.

Participants

8

Citations

18

Size

19.5 GB

Version

v1.0.0

Updated

Jul 22, 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

7.24 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises physiological and behavioral recordings from a semi-automated driving task designed to investigate trust in automation (TiA). Participants completed lane maintenance, following distance control, and collision avoidance maneuvers with optional autonomous driving assistance under varying performance conditions. The autonomous assistant could manage following distance alone or in combination with lane position maintenance, but collision avoidance required manual operator intervention. The study employed multimodal psychophysiological monitoring including EEG, electrooculography, electrocardiography, electrodermal activity, and gaze tracking to develop quantitative metrics for real-time assessment of operator trust and trust-related decision-making in human-autonomy vehicle control interactions.

Participants

24

Channels

64 (10-10)

HED

v8.1.0

Size

43.1 GB

Version

v1.0.0

Updated

Jul 10, 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 investigates the dissociation between hypervigilance to social threats and altered perceptual decision-making in lonely individuals using event-related potentials (ERP) and Drift Diffusion Modeling. The study combines electrophysiological recordings with computational modeling to examine whether loneliness-related social threat sensitivity reflects genuine perceptual changes or decision-level alterations in threat processing.

Participants

52

Channels

68 (10-10)

Citations

6

Size

19.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises multimodal neurophysiological and biomechanical recordings from 32 young adults performing walking tasks over uneven terrain at varying speeds. Data include high-density dual-layer electroencephalography (EEG), neck electromyography (EMG), inertial measurement unit (IMU) acceleration, ground reaction forces, and structural MRI-derived head models. Each participant completed two trials per condition lasting three minutes, plus a seated rest baseline, providing a comprehensive resource for investigating neural and muscular control mechanisms during dynamic locomotion.

Participants

32

Channels

120 (other)

Citations

3

Size

61.9 GB

Version

v1.0.0

Updated

Jul 10, 2026