FRL Handwriting: Handwriting Decoding from Surface Electromyography
…Few-shot learning, transfer learning - **Sequence modeling**: Character-level prediction with attention…
- Participants
- 100
- Size
- 45.3 GB
- Version
- v2.0.0
- Updated
- Feb 23, 2026
…Few-shot learning, transfer learning - **Sequence modeling**: Character-level prediction with attention…
Intracranial EEG (iEEG) dataset titled 'Neural spatial volatility', collected by Kuroda, Asano, Nakasato and colleagues, with ethics approval from the IRBs of Wayne State University and Tohoku University. The dataset is organized in BIDS format and mirrored on NEMAR from its original OpenNeuro deposit (ds006107).
…Continuous sensorimotor rhythm based brain computer interface learning in a large population…
A multi-session dataset of simultaneous EEG-fMRI recorded from 24 healthy adults aged 18-35 while they performed a gradual-onset continuous performance task (GradCPT) and a resting-state condition with intermittent multidimensional experience sampling. The same protocol was repeated on two days. Carbon wire loop sensors in the EEG cap support artifact removal. The dataset also includes ECG, behavioral responses, and mental health surveys. It supports study of attentional fluctuations, mind-wandering, and the test-retest reliability of EEG-fMRI relationships.
…Supramodal processing optimizes visual perceptual learning and plasticity. Neuroimage, 93, 32-46…
This dataset, named DataSet2, is an EEG dataset originally deposited on OpenNeuro (ds002833) and mirrored on NEMAR. It was contributed by Mheich and colleagues. The available documentation gives no details on the experimental paradigm or participants.
…In training: 'NEURAL NETWORKS AND DEEP LEARNING' (33 characters), in test: 'PATTERN…
MEG dataset from a logical reasoning study collected by the Cognitive and Computational Neuroscience Laboratory (UPM - UCM). The dataset is organized in BIDS format and mirrored on NEMAR from the OpenNeuro deposit ds003483.
…Sensitive Period of Native Phoneme Learning. International Journal of Environmental Research and…
This dataset contains 32-channel EEG recordings acquired during a sham neurofeedback experiment in a virtual reality environment. The study examined how feedback valence (positive, negative, or none) modulates alpha-band activity during an attentional task. Each participant completed positive, negative, control, and resting-state (eyes open/eyes closed) conditions.