100 results for "motor learning" · page 6 of 10 · ranked by relevance
…In training: 'NEURAL NETWORKS AND DEEP LEARNING' (33 characters), in test: 'PATTERN…
…repeat the sentence without any motor action. The experimental design, a modified…
…Department of Computer Science, Machine Learning Group Address: 10587 Berlin, Germany Country…
…82901/nemar.on004295) Two reversal learning tasks with different reinforcer (monetary reward…
[ Reinforcement learning task with 50 healthy controls (25…
HAD-MEEG is a multimodal neuroimaging dataset combining magnetoencephalography (MEG) and electroencephalography (EEG) recordings from 30 participants viewing 21,600 video clips across 180 human action categories. Designed to complement the previously released HAD-fMRI dataset, this resource leverages the millisecond-level temporal resolution of M/EEG to capture rapid neural dynamics underlying action recognition and social cognition, enabling integrated spatiotemporal analysis of brain responses to visual action stimuli.
…the Reward Positivity during reinforcement learning. Participants were all SCID interviewed to…
…Passive motor (Pass-Mot, Biodex-driven arm movement) 5. Active motor (Act…
This dataset comprises multimodal neurophysiological and kinematic recordings from 25 participants engaged in real-world table tennis gameplay. The collection includes high-density dual-layer electroencephalography, cervical electromyography, inertial measurement unit acceleration data, structural MRI, and synchronized video recordings. Participants completed 60 minutes of table tennis play against both a ball machine and human opponent, with 10 minutes of standing baseline recording. Processed data include independent component analysis decomposition and dipole modeling for EEG signals.