on004942
SpatialMemory
EEG
…Results indicate that VSWM sequence encoding is related to later (~700 ms…
- Participants
- 62
- Channels
- 65 (10-10)
- Citations
- 1
- Size
- 25.1 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
Discover datasets
100 results for "encoding model" · page 4 of 10 · ranked by relevance
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- on007655
MorseEEG-ATP
BEH EEG…MC provides a controlled and parameterizable stimulus model for this purpose because…
- Participants
- 32
- Channels
- 62 (10-10)
- Size
- 14.6 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- on005383
TMNRED, A Chinese Language EEG Dataset for Fuzzy Semantic Target Identification in Natural Reading Environments
EEGTMNRED is an EEG dataset collected from 30 healthy, right-handed native Chinese speakers performing a natural reading task designed to investigate fuzzy semantic target identification. Participants read Chinese news headlines and short sentences containing target and non-target semantic items while EEG was recorded across 8 blocks of 400 trials each. The dataset supports research into semantic processing mechanisms during naturalistic reading in the Chinese language.
- Participants
- 30
- Channels
- 30 (10-10)
- Citations
- 1
- Size
- 17.4 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000253
Wang et al. 2024 — Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli
iEEGBrain 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
- nm000207
Kojima et al. 2024 (Dataset B) — Four-class ASME BCI: investigation of the feasibility and comparison of two strategies for multiclassing
EEGThis dataset comprises EEG recordings from 15 healthy subjects performing an auditory brain-computer interface task based on the ASME (Auditory Stream segregation Multiclass ERP) paradigm. The study investigates two strategies for achieving four-class classification: ASME-4stream (four independent streams with single target stimuli) and ASME-2stream (two streams with dual target stimuli each). EEG data were recorded at 1000 Hz from 64 channels and analyzed using event-related potential methods and linear discriminant analysis classification, achieving accuracies of 83% and 86% respectively.
- Participants
- 15
- Channels
- 64 (10-10)
- Citations
- 6
- HED
- v8.4.0
- Size
- 23.5 GB
- Version
- v1.0.4
- Updated
- Aug 18, 2026
- on006334
Neocortical and Hippocampal Theta Oscillations Track Audiovisual Integration and Replay of Speech Memories
ANAT MEG…1) Encoding: participants were presented with a series of audiovisual speech movies…
- Participants
- 30
- Citations
- 7
- Size
- 172 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on005095
STERNBERG DIFFICULT
EEG…500-1000 ms fixation cross. Encoding (letter set), retention (blank screen), and…
- Participants
- 48
- Channels
- 63 (10-10)
- Citations
- 2
- Size
- 14.3 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000167
Motor imagery dataset from Ma et al. 2020
EEG Zarr verifiedThis dataset contains 62-channel EEG recordings from 25 healthy, right-handed subjects performing kinesthetic motor imagery of the right hand versus right elbow, a within-limb discrimination paradigm. Each subject completed 15 sessions over 3 days, yielding 600 trials total, designed to study brain-computer interface (BCI) decoding of different joint movements from the same limb. The dataset supports research into motor rehabilitation and prosthetic control applications using EEG-based BCI systems.
- Participants
- 25
- Channels
- 62 (10-10)
- Citations
- 52
- HED
- v8.4.0
- Size
- 53.8 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on007431
Diffuse predictions stabilize and reshape neural code during memory encoding
EEG[
- Size
- 145 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- on005964
FRESH Audio Dataset
NIRSFRESH Audio Dataset is a functional near-infrared spectroscopy (fNIRS) dataset collected during audio processing tasks. The dataset contains raw fNIRS measurements organized according to the Brain Imaging Data Structure (BIDS) standard. This dataset supports research into auditory neuroscience and the neural correlates of sound processing. NOTE: Dataset status should be verified as complete and finalized before DOI minting.
- Participants
- 17
- Size
- 65.5 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026