100 results for "random-dot kinematogram" · page 6 of 10 · ranked by relevance
…Evidence from a Randomized, Controlled Trial ### Introduction **Overview:** Both forward and backward…
A multi-joint upper-limb motor imagery EEG dataset comprising 18 healthy subjects performing eight distinct imagery tasks involving hand, wrist, elbow, and shoulder movements. The dataset contains 320 trials per subject acquired at 1000 Hz using 62-channel EEG with visual cue-based paradigm, designed for brain-computer interface research and motor rehabilitation applications.
…files for each story were completely randomized. Random combinations were created so…
This phantom EEG dataset contains recordings from an electrically conductive head model under six controlled conditions: brain-only baseline, and brain signals combined with eye, jaw muscle, neck muscle, motion, or simultaneous artifacts. The dataset includes ground truth brain signals and accompanying EEGLAB scripts for artifact detection validation and parameter optimization, supporting development and benchmarking of EEG artifact removal methods.
…2 per combination, 25s each | | Random | `random` | Free finger contractions at any…
This dataset contains MEG recordings from participants performing a risky decision-making task alongside a localizer task and a probability learning task. It was collected to investigate heuristics in risky decision-making and their relationship to preferential neural representation of choice- and outcome-related information. The dataset includes raw MEG data and derivative event and epoched data tables supporting analyses reported in an associated preprint.
…fMRI, and were aroused at random intervals 8 times during the night.
Beetl2021-A is a preprocessed motor imagery EEG dataset derived from the BEETL Competition 2021 (NeurIPS Task 2), comprising 63-channel, 500 Hz recordings from healthy subjects performing a four-class motor imagery task (rest, left hand, right hand, feet) during an online BCI racing game (Cybathlon2020IC). The dataset was designed to benchmark transfer learning and domain adaptation methods for subject-independent, cross-dataset EEG-based brain-computer interfacing.
…For clicks the trials were not randomized (already random clicks). Trigger onset…
This dataset comprises intracranial EEG (ECoG) recordings from 14 epilepsy patients implanted with subdural grid and depth electrodes, collected while they viewed grayscale and color visual stimuli varying in spatial and temporal properties. The recordings were designed to characterize temporal and spatial dynamics of neural responses in human visual cortex, including population receptive field mapping and category-selective responses. Pre-implantation T1-weighted MRI scans are also included for electrode localization. The dataset supports multiple published studies on visual cortical dynamics and adaptation.