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The Natural Object Dataset (NOD) integrates electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) data collected from the same subjects viewing naturalistic object stimuli from ImageNet. This multimodal neuroimaging dataset enables investigation of neural mechanisms underlying object recognition in natural scenes by combining high spatial resolution (fMRI) with high temporal resolution (EEG/MEG) recordings, addressing limitations of single-modality approaches in characterizing both spatial representation patterns and temporal dynamics of visual cognitive processing.

Participants

19

Channels

62 (10-10)

Size

24.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Natural Object Dataset (NOD) integrates magnetoencephalography (MEG), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) data collected from the same subjects viewing naturalistic stimuli from ImageNet. This trimodal neuroimaging resource provides both high spatial resolution (fMRI) and high temporal resolution (MEG/EEG) for investigating object recognition mechanisms. The dataset encompasses diverse naturalistic stimuli and a broad subject pool, facilitating exploration of neural activation patterns across stimuli and subjects. The EEG component is available as a separate dataset (ds005811).

Participants

31

Size

215 GB

Version

v1.0.0

Updated

Jul 10, 2026

MULTI-CLARID is a multimodal neuroimaging dataset combining simultaneous fMRI and EEG recordings from participants performing an auditory category learning task and resting-state fMRI. The dataset includes 64-channel EEG (63 head channels plus ECG) with physiological monitoring (EOG, facial EMG, skin conductance), structural MRI (T1-weighted and PD-weighted UTE), and behavioral measures. This resource enables investigation of neural mechanisms underlying category learning and brain functional connectivity. Data were acquired at the Combinatorial NeuroImaging (CNI) core facility of the Leibniz Institute for Neurobiology (LIN) Magdeburg.

Participants

34

Channels

72 (10-10)

Size

6.43 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains non-invasive spinal cord recordings from 30 healthy young subjects performing an auditory-somatosensory expectation task. Participants received electric median nerve stimulations preceded by auditory cues at either fixed (1100 ms) or variable (100-2100 ms) intervals, while counting rare double-stimulus trials. The study investigates whether temporal expectation modulates initial sensory processing in the human spinal cord using high-frequency electrophysiological recordings from three electrode rings positioned around the cervical spine.

Participants

30

Channels

24 (other)

Size

92.8 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset investigates whether temporal expectation modulates initial sensory processing in the human spinal cord using invasive electrophysiological recordings. Eight patients with neuropathic pain and implanted cervical epidural electrodes performed an auditory-cued median nerve stimulation task under two conditions: fixed (1100 ms) or variable (100-2100 ms) cue-to-stimulus intervals. Participants counted rare double-stimulus trials (80 ms interstimulus interval) within ~5 minute blocks. The study tests the hypothesis that predictive timing signals influence early somatosensory processing at the spinal level. Recordings were obtained from epidural electrode contacts placed alongside the dorsal cervical spinal cord.

Participants

8

Size

722 MB

Updated

Jul 10, 2026

This dataset comprises electrocorticography (ECoG) recordings from 20 C57BL/6 mice exposed to combinations of diagnostic ultrasound (tDUS) and visual stimuli to investigate how transcranially delivered ultrasound modulates visual cortex responses. Recordings from visual and somatosensory cortices were collected at 20 kS/s during three experimental conditions: light-only, ultrasound-only, and combined ultrasound with light stimulation. The study demonstrates that tDUS enhances exogenously induced brain activity when combined with visual stimuli, with implications for understanding ultrasound-mediated neuromodulation.

Participants

20

Size

8.28 GB

Version

v1.0.0

Updated

Jul 10, 2026

PerceiveImagine is an electroencephalography dataset capturing neural activity during visual perception and imagery tasks. Participants viewed images for 6 seconds following a prompt, then closed their eyes and imagined the same images for 6 seconds. The dataset comprises raw EEG recordings designed to investigate neural correlates of visual perception and mental imagery.

Participants

3

Channels

65 (10-10)

Size

4.23 GB

Version

v1.0.0

Updated

Jul 10, 2026

A stereoelectroencephalography (SEEG) dataset containing resting state recordings from two patients with epilepsy. The dataset includes raw recordings acquired using Sinovation SDE-08 medical-grade depth electrodes with standardized specifications. This resource provides intracranial electrophysiological data suitable for investigating epileptic activity and brain network dynamics at high spatial resolution.

Participants

2

Size

709 MB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains raw EEG recordings from participants performing a visual object recognition task designed to investigate how the brain represents object space dimensions over time. The study combines neuroimaging data with behavioral measurements to provide new insights into the temporal dynamics of object space coding in human perception.

Participants

21

Channels

64

Size

35.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

A color change detection task dataset organized in BIDS format containing intracranial electrophysiological (iEEG) recordings from participants performing a visual perception task. Participants were required to detect color changes in visual stimuli while neural activity was recorded from implanted electrodes. The dataset includes raw iEEG data, electrode localization information, and task event markers, organized according to the iEEG-BIDS specification. This standardized format facilitates reproducible analysis and sharing of human intracranial brain imaging data. For complete attribution and dataset documentation, please refer to the dataset files and associated publications.

Participants

24

Size

13.8 GB

Version

v1.0.0

Updated

Jul 10, 2026