on005523
Spatial Memory of Object Locations with Open-Loop Stimulation at Encoding
BEH iEEG Zarr
…For learning trial 1, participants are placed at a random location at…
- Participants
- 22
- Size
- 69.7 GB
- Version
- v1.0.0
- Updated
- Jun 27, 2026
Discover datasets
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- nm000232
THINGS-EEG2: A large and rich EEG dataset for modeling human visual object recognition
EEG ZarrTHINGS-EEG2 is an EEG dataset from 10 participants who viewed 16,540 training images and 200 repeated test images from the THINGS database, using rapid serial visual presentation at 5 Hz. Each participant completed four sessions, recorded with a 63-channel BrainVision actiCHamp system at 1000 Hz, plus resting-state recordings. The dataset supports modeling of human visual object recognition and encoding models of neural responses.
- Participants
- 10
- Channels
- 63 (10-10)
- Citations
- 88
- Size
- 241 GB
- Version
- v1.1.1
- Updated
- Oct 15, 2026
- on004295
Reward gain and punishment avoidance reversal learning
EEG Zarr…82901/nemar.on004295) Two reversal learning tasks with different reinforcer (monetary reward…
- Participants
- 26
- Channels
- 66 (10-10)
- Citations
- 10
- Size
- 31.5 GB
- Version
- v1.0.0
- Updated
- Jun 23, 2026
- on005356
MEG: Major Depression & Probabilistic Learning Task
MEG Zarr…the Reward Positivity during reinforcement learning. Participants were all SCID interviewed to…
- Participants
- 85
- Size
- 162 GB
- Version
- v1.0.0
- Updated
- Jun 26, 2026
- nm000133
Alljoined1
EEG ZarrAlljoined1 is an EEG dataset of neural responses to natural images presented in a rapid serial visual presentation paradigm, built for EEG-to-image decoding research. Eight healthy adults viewed images from the Natural Scenes Dataset (MS-COCO) while 64-channel BioSemi EEG was recorded across one or two sessions. This BIDS version contains raw BDF recordings of 960 shared images, event tables linked to stimuli, and epoched derivatives from the original authors.
- Participants
- 8
- Citations
- 5
- Size
- 8.04 GB
- Version
- v1.0.4
- Updated
- Sep 23, 2026
- on003506
EEG: Reinforcement Learning in Parkinson's
EEG Zarr…10.82901/nemar.on003506) Reinforcement learning task with 28 Parkinson patients and…
- Participants
- 56
- Channels
- 67 (10-10)
- Citations
- 2
- Size
- 16.2 GB
- Version
- v1.0.0
- Updated
- Jun 22, 2026
- on005574
The "Podcast" ECoG dataset
ANAT iEEG ZarrThe "Podcast" electrocorticography (ECoG) dataset captures intracranial neural activity from 9 participants (1,330 grid, depth, and strip electrodes) who listened to a 30-minute naturalistic story containing over 5,000 words. It includes raw recordings, a minimally preprocessed high-gamma version, the auditory stimuli, an aligned word-level transcript, and linguistic features ranging from acoustic properties to large language model embeddings. Tutorials replicating prior findings are provided to support research on natural language comprehension.
- Participants
- 9
- Size
- 14.4 GB
- Version
- v1.0.0
- Updated
- Jun 27, 2026
- on006260
Dataset of psychophysiological data from children with learning difficulties who strengthen reading and math skills through assistive technology
EEG Zarr…data from Mexican children with learning difficulties who strengthen reading and math…
- Participants
- 76
- Channels
- 32 (10-10)
- Size
- 2.76 GB
- Version
- v1.0.0
- Updated
- Jun 28, 2026
- nm000306
Jia2019: Motor-imagery EEG dataset for stroke patients (Jia 2019)
EEG ZarrThis dataset contains 63-channel EEG recorded at 512 Hz from 15 stroke patients performing cue-based left-hand versus right-hand motor imagery, with 40 trials per class. For each patient one hand is paretic and the other unaffected, and both were imagined. It is a BIDS re-release of the original figshare deposit, prepared via MOABB with HED event annotations, and is intended for brain-computer interface and neurorehabilitation research.
- Participants
- 15
- Channels
- 63 (other)
- HED
- v8.4.0
- Size
- 1.74 GB
- Version
- v1.0.0
- Updated
- Oct 8, 2026
- on005571
Expectation of Conflict Stimuli
ANAT EEG FMAP FUNC ZarrThis dataset, titled Expectation of Conflict Stimuli, accompanies a study of how the brain forms expectations about upcoming conflict and adapts to it. It is associated with research on the role of lateral prefrontal theta oscillations in a computational mechanism underlying conflict expectation and adaptation. The dataset is organized in BIDS format and mirrored on NEMAR from OpenNeuro.
- Participants
- 29
- Channels
- 66 (10-10)
- Citations
- 8
- Size
- 63.3 GB
- Version
- v1.0.0
- Updated
- Jun 27, 2026