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100 results for "neural decoding" · page 8 of 10 · ranked by relevance

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nm000224
Imagined speech EEG dataset — short and long words (Nguyen et al. 2017)

EEG

This dataset comprises preprocessed EEG recordings from 6 healthy participants performing imagined speech tasks, specifically discriminating between short and long words ('cooperate' vs 'in'). Data were acquired at 256 Hz using 64 EEG channels and processed with bandpass filtering (8-70 Hz), notch filtering (60 Hz), and artifact removal. The dataset contains 1,200 trials. Classification results (mean accuracy 73.3±8.9%) reported in the original Nguyen et al. 2017 study are provided for reference.

Participants

6

Channels

60 (10-10)

Citations

98

HED

v8.4.0

Size

1.15 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Chuong H. Nguyen et al.
nm000174
Imagined Speech EEG dataset comparing paradigm designs (Aguilera-Rodriguez et al. 2025)

EEG

…design effects on imagined speech decoding performance. ## Dataset Summary | Property | Value | |---|---| | Subjects…

Participants

15

Channels

24 (10-10)

Citations

1

HED

v8.4.0

Size

1.52 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Edgar Aguilera-Rodriguez et al.
nm000142
Ear-EEG motor execution dataset from Wu et al 2020

EEG

This dataset contains simultaneous scalp and ear-EEG recordings from 6 healthy right-handed adults performing a motor execution task involving left and right hand fist clenching, cued by visual arrow stimuli. Recordings were made at 1000 Hz using a 122-channel Neuroscan SynAmps2 system, yielding 1114 trials, and are intended for benchmarking motor task classification algorithms such as EEGNet. The dataset was converted to BIDS format using MOABB and originates from a study investigating the utility of in-ear EEG sensing for motor task classification.

Participants

6

Channels

122 (10-05)

Citations

12

HED

v8.4.0

Size

18.4 GB

Version

v1.0.3

Updated

Aug 20, 2026

by Xiaoli Wu et al.
on006317
Chisco-2.0

EEG

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006317-blue…

Participants

2

Channels

124 (10-05)

Size

52.9 GB

Version

v1.0.0

Updated

Aug 19, 2026

by Zihan Zhang et al. OpenNeuro ds006317
on004745
8-Channel SSVEP EEG Dataset with Artifact Trials

EEG

Imported from OpenNeuro ds004745

Participants

6

Channels

8 (other)

Citations

27

Size

242 MB

Version

v1.0.0

Updated

Jul 10, 2026

by Velu Prabhakar Kumaravel et al. OpenNeuro ds004745
on002338
A multi-modal human neuroimaging dataset for data integration: simultaneous EEG and fMRI acquisition during a motor imagery neurofeedback task: XP2

ANAT EEG FUNC

This dataset comprises simultaneous 64-channel EEG and 3T fMRI recordings from 16 subjects performing motor imagery and neurofeedback tasks. Participants were randomly assigned to receive either mono-dimensional or bi-dimensional neurofeedback displays during five experimental runs with alternating rest and task blocks. The dataset includes raw EEG data in Brain Vision format, preprocessed EEG data, BOLD fMRI acquisitions, computed neurofeedback scores from both modalities (EEG and fMRI), and event timing files, providing a comprehensive resource for multimodal neuroimaging data integration studies.

Participants

17

Size

25.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

by Giulia Lioi et al. OpenNeuro ds002338
nm000106
FRL Handwriting: Handwriting Decoding from Surface Electromyography

EMG

…Computational Neuroscience) INC (Institute for Neural Computation) University of California San Diego…

Participants

100

Size

45.3 GB

Version

v2.0.0

Updated

Jul 10, 2026

by Patrick Kaifosh et al.
nm000268
Shin et al. 2017 (Experiment B) — Open Access Dataset for EEG+NIRS Single-Trial Classification

EEG

This open-access hybrid brain-computer interface dataset combines simultaneous EEG and near-infrared spectroscopy (NIRS) recordings from 29 healthy subjects performing mental arithmetic and motor imagery tasks. Experiment B focuses on mental arithmetic (serial subtraction) versus rest conditions across six sessions with preprocessed data at 200 Hz sampling rate. The dataset includes comprehensive preprocessing (bandpass filtering, ICA-based artifact rejection, common average referencing) and serves as a benchmark for validating hybrid BCI approaches that integrate multimodal neuroimaging signals.

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

6.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Jaeyoung Shin et al.
nm000342
CastillosCVEP40

EEG

…CNN (Convolutional Neural Network) Feature extraction: sliding windows, bitwise decoding Cross-Validation…

Participants

12

Channels

32 (10-10)

Citations

22

HED

v8.4.0

Size

340 MB

Version

v1.0.2

Updated

Aug 18, 2026

by Kalou Cabrera Castillos et al.
nm000237
7-day motor imagery BCI EEG dataset from Zhou et al 2021

EEG

…Relative Power Correlates With the Decoding Performance of Motor Imagery Both Across…

Participants

20

Channels

41 (other)

Citations

15

HED

v8.4.0

Size

93.1 GB

Version

v1.0.3

Updated

Aug 20, 2026

by Qing Zhou et al.