…Few-shot learning, transfer learning - **Sequence modeling**: Character-level prediction with attention…
Preprocessed 64-channel EEG recordings from 8 healthy participants performing imagined speech of three vowel phonemes (a, i, u) in response to auditory and visual cues. The dataset was re-packaged in BIDS format from the MOABB collection and supports decoding of imagined speech with Riemannian manifold features and relevance vector machine classification.
…Continuous sensorimotor rhythm based brain computer interface learning in a large population…
This dataset provides high-density (128-channel) EEG and mouse-tracking data from 31 adults aged 18-33, collected in 2020. It includes resting-state recordings and task recordings from food preference choices and semantic judgments. The resource is intended for studying the dynamic decision processes underlying binary choices in the human brain.
…Supramodal processing optimizes visual perceptual learning and plasticity. Neuroimage, 93, 32-46…
This dataset contains 64-channel EEG recordings from 62 participants, organized into 31 pairs, who played a computerised version of the competitive Rock-Paper-Scissors game across 480 games. It was collected to study the neural correlates of competitive decision-making and to support decoding of choices and outcomes from brain activity. Each session lasted about one hour.
[, in test: 'PATTERN…
ODE is an EEG dataset formatted according to BIDS with HED annotations, contributed by Johnson, Gordon, Touryan, and King. The available documentation describes it only as a placeholder dataset, so no further details on content or purpose are provided.
…Sensitive Period of Native Phoneme Learning. International Journal of Environmental Research and…