on004127
Somatosensory Cortex Rat DISC Data
iEEG
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004127-blue…
- Participants
- 8
- Citations
- 2
- Size
- 188 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
Discover datasets
100 results for "model interpretability" · page 7 of 10 · ranked by relevance
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- on003885
Capacity for movement is an organisational principle in object representations: EEG data from Experiment 1
EEGThis dataset contains electroencephalographic (EEG) recordings from 24 participants performing object classification and passive viewing tasks in Experiment 1 of a study investigating how the brain represents object movement and aliveness. Participants classified static images of objects with varying capacities for movement (moving/non-moving) and animacy (alive/not alive) as either alive or capable of movement. The study demonstrates that movement capacity is a significant organizational principle in visual object representation, independent of animacy.
- Participants
- 24
- Citations
- 15
- Size
- 82.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000196
c-VEP dataset from Thielen et al. (2015)
EEG…We defined a linear generative model that decomposes full responses into overlapping…
- Participants
- 12
- Channels
- 64 (10-10)
- Citations
- 72
- HED
- v8.4.0
- Size
- 11.0 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- nm000256
The Brain, Body, and Behaviour Dataset (1.0.0) - Experiment 3
BEH EEGThe Brain, Body, and Behaviour Dataset - Experiment 3 is a multimodal neurophysiological dataset comprising 29 subjects across 2 sessions designed to investigate the effects of attentional state on learning from educational videos. Participants watched six educational videos under two conditions: attentive (with post-video testing) and distracted (with concurrent cognitive load), while simultaneous recordings of brain activity, cardiovascular function, eye movements, and head motion were collected. The dataset includes concurrent EEG, ECG, EOG, gaze tracking, pupil size, and head position data, along with behavioral measures including memory questionnaires and ADHD symptom assessments.
- Participants
- 29
- Channels
- 64 (10-10)
- Size
- 7.44 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000180
Brennan2019: EEG during Naturalistic Listening to Alice in Wonderland
EEG…model (`NGRAM`) | | `rnn_surprisal` | Surprisal from a recurrent neural-network language model…
- Participants
- 45
- Channels
- 60 (other)
- Citations
- 127
- Size
- 3.81 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on007471
Joint agency EEG dataset
BEH EEGThis dataset contains behavioural and EEG hyperscanning data collected from 32 pairs of participants performing a musical joint action task. The data were collected to examine cognitive and neural signals underlying the sense of joint agency during synchronized musical performance. Each pair's data includes behavioural ratings and synchronization measures alongside dual-participant 64-channel EEG recordings in BrainVision format.
- Participants
- 32
- Citations
- 2
- Size
- 8.06 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- nm000107
FRL Wrist Control: Wrist Movement Decoding from Surface Electromyography
EMG Zarr verified…1.51s (2.2× slower than trackpad) **Model architecture**: MPF features + LSTM…
- Participants
- 100
- Size
- 24.9 GB
- Version
- v2.0.0
- Updated
- Jul 10, 2026
- on004276
Auditory single word recognition in MEG
BEH MEGThis dataset comprises magnetoencephalography (MEG) recordings of auditory single word recognition in human subjects. Participants listened to isolated words while neural activity was recorded, providing insights into the temporal dynamics of auditory word comprehension. The dataset is described in Gaston et al. (2022) 'Auditory word comprehension is less incremental in isolated words' published in Neurobiology of Language. The dataset includes raw MEG data, stimulus information, and associated metadata organized according to the Brain Imaging Data Structure (BIDS) standard. This is a NEMAR-converted version of OpenNeuro dataset ds004276.
- Participants
- 19
- Citations
- 1
- Size
- 11.6 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005107
FACE-DEC
BEH MEG[
EEGA high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects), with 72 photographs per category, presented for 500 ms each. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.
- Participants
- 10
- Channels
- 124 (egi-geodesic)
- Citations
- 93
- HED
- v8.4.0
- Size
- 3.40 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026