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81 results for "neuroergonomics" · page 7 of 9 · ranked by relevance

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on006502
Skill learning and consolidation in healthy humans

ANAT MEG

This longitudinal neuroimaging study investigates neural mechanisms of motor skill learning, consolidation, and retention using magnetoencephalography (MEG) combined with structural MRI. Thirty-one healthy right-handed adults performed a sequential finger-tapping task during an initial training session followed by retest sessions at approximately 24 hours and 30 days post-training. The dataset includes continuous MEG recordings, high-resolution anatomical MRI, behavioral performance metrics, eye-tracking, pupillometry, and electromyography data synchronized across all sessions.

Participants

31

Size

95.7 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Bönstrup et al. OpenNeuro ds006502
nm000107
FRL Wrist Control: Wrist Movement Decoding from Surface Electromyography

EMG

NEMAR Dataset nm000107: wrist - Wrist movement control from EMG

Participants

100

Size

26.8 GB

Version

vv2.0.0

Updated

Jul 10, 2026

by Patrick Kaifosh et al.
on004973
An fNIRS dataset for driving risk cognition of passengers in highly automated driving scenarios

NIRS

This fNIRS neuroimaging dataset captures prefrontal cortex activity from 20 participants during 14 types of highly automated driving scenarios in a simulator environment. The study examines risk cognition in passengers across different age groups, sexes, and driving experience levels using an 8-channel fNIRS device. The dataset aims to identify differences in prefrontal cortex activation between low-risk and high-risk driving episodes to support safety-of-the-intended-functionality (SOTIF) improvements and brain-computer interface applications.

Participants

20

Size

2.31 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Xiaofei Zhang et al. OpenNeuro ds004973
on007012
FOODEEG: An open dataset of human electroencephalographic and behavioural responses to food images

BEH EEG

FOODEEG is an open dataset comprising electroencephalographic (EEG) and behavioral responses from 117 participants to food images. The dataset includes raw and processed EEG recordings from a food categorization task, along with behavioral data from food go/no-go and paired choice tasks. Participants also provided continuous ratings on food attributes and completed questionnaires assessing dietary styles and eating motivations, with normative ratings collected from an additional 624 online participants.

Participants

117

Size

91.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Chae et al. OpenNeuro ds007012
nm000233
BCI Competition 2020 Track 4 — Upper-limb grasping motor imagery

EEG

BCIComp2020UpperLimb is a preprocessed EEG dataset from BCI Competition 2020 Track 4 containing motor imagery recordings of three upper-limb grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. The dataset comprises 60-channel EEG data sampled at 250 Hz with 450 trials per subject (150 trials per session × 3 sessions), designed to evaluate session-to-session transfer learning in brain-computer interface applications. Data were preprocessed with 60 Hz notch filtering and cue-aligned epoching, with the 4-second motor imagery window extracted for analysis.

Participants

14

Channels

60 (10-10)

HED

v8.4.0

Size

795 MB

Version

vv1.0.1

Updated

Jul 10, 2026

by Ji-Hoon Jeong et al.
nm000162
BNCI 2025-001 Motor Kinematics Reaching dataset

EEG

Participants

20

Channels

67 (10-05)

Citations

3

HED

v8.4.0

Size

15.0 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Nitikorn Srisrisawang et al.
nm000336
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study R)

EEG

BigP3BCI Study R is a P300-based brain-computer interface dataset comprising EEG recordings from 20 ALS subjects performing a 9x8 character grid speller task across two sessions. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 32-channel EEG with a g.USBamp amplifier and are organized in BIDS format with HED event annotations for standardized analysis and machine learning applications.

Participants

20

Channels

32 (10-10)

HED

v8.4.0

Size

1.95 GB

Version

vv1.0.1

Updated

Jul 10, 2026

by Boyla Mainsah et al.
nm000132
ERP CORE

EEG

Participants

40

Channels

30 (10-10)

Citations

95

HED

v8.4.0

Size

17.5 GB

Version

vv1.1.1

Updated

Jul 10, 2026

by Emily S. Kappenman et al.
on003766
A resource for assessing dynamic binary choices in the adult brain using EEG and mouse-tracking

BEH EEG

This dataset combines high-density electroencephalography (128-channel HD-EEG) and mouse-tracking to examine dynamic decision-making processes in the human brain. Collected from 31 adults (ages 18-33), it includes resting-state and task-related EEG data acquired during food preference choices and semantic judgment tasks. The resource provides both raw and preprocessed EEG data with synchronized behavioral measures, enabling investigation of neural correlates underlying binary choice decisions.

Participants

31

Channels

129 (egi-geodesic)

Size

153 GB

Version

vv1.0.0

Updated

Jul 22, 2026

by Kun Chen et al. OpenNeuro ds003766
nm000139
BNCI 2014-001 Motor Imagery dataset

EEG

Participants

9

Channels

22 (10-10)

Citations

90

HED

v8.4.0

Size

672 MB

Version

vv1.0.0

Updated

Jul 10, 2026

by Michael Tangermann et al.