Discover datasets

FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.

Participants

117

Size

91.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

Imported from OpenNeuro ds006126

Participants

6

Channels

3 (other)

Size

1.08 GB

Version

v1.0.0

Updated

Jul 10, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005241-blue…

Participants

24

Size

140 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains cue-locked EEG recordings and behavioral event annotations from 43 healthy adults performing a random-dot kinematogram (RDK) task designed to dissociate low-level and high-level hierarchical priors during perceptual decision-making. The study examines how such priors bias behavior via signal detection theory and generalized drift-diffusion modeling, and how they modulate occipital oscillatory and aperiodic EEG activity. Participants also completed questionnaires assessing psychosis proneness and psychological flexibility traits.

Participants

43

Channels

31 (10-10)

Size

8.76 GB

Version

v1.0.0

Updated

Aug 18, 2026

A comprehensive EEG dataset comprising 54 healthy subjects performing three major brain-computer interface (BCI) paradigms: motor imagery (MI), event-related potential (ERP), and steady-state visually evoked potential (SSVEP) across two sessions. The dataset investigates BCI illiteracy rates and performance variations, revealing that while MI showed the highest illiteracy rate (53.7%), all participants could control at least one BCI paradigm. Data were acquired at 1000 Hz using 62 EEG channels with concurrent electromyography recordings.

Participants

54

Channels

62 (10-05)

Citations

99

HED

v8.4.0

Size

121 GB

Version

v1.0.5

Updated

Aug 18, 2026

This dataset comprises electroencephalography (EEG) recordings from individuals with acute mild traumatic brain injury (mTBI) and matched controls performing a visual working memory task with embedded mind wandering probes. Data were collected at three timepoints spanning approximately four months post-injury, with the initial session occurring 3-14 days after injury. The dataset includes fully preprocessed and cleaned EEG data, behavioral measures, and analysis scripts, providing a longitudinal resource for investigating cognitive dysfunction and neural recovery following mild TBI. Note: This dataset has not been published in peer-reviewed literature.

Participants

91

Channels

65 (10-10)

Size

37.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

Brain Treebank is a large-scale intracranial EEG dataset comprising 43 hours of iEEG recordings from 10 epilepsy patients watching naturalistic Hollywood movies, with 1,688 electrodes sampled at 2048 Hz. The dataset includes time-aligned linguistic annotations with word-level transcripts and Universal Dependencies syntax trees, providing a unique resource for studying neural language processing during naturalistic stimulation.

Participants

10

Size

508 GB

Version

v1.0.0

Updated

Jul 10, 2026

…The goal was to reveal whether temporal expectation influences initial sensory processing…

Participants

30

Channels

24 (other)

Size

92.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

Imported from OpenNeuro ds005628

Participants

102

Channels

8 (10-10)

Citations

1

Size

633 MB

Version

v1.0.0

Updated

Jul 10, 2026

…prefrontal lobe - **Sensor type**: Ag/AgCl - **Line frequency**: 50.0 Hz - **Online…

Participants

10

Channels

60 (10-10)

Citations

94

HED

v8.4.0

Size

5.64 GB

Version

v1.0.2

Updated

Aug 18, 2026