100 results for "scientific data" · page 9 of 10 · ranked by relevance
…MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data…
This dataset investigates brain signal-based emotion recognition through magnetoencephalography (MEG) recordings collected while participants viewed validated emotional video stimuli. It comprises three components: a large-scale online behavioral survey of 500 participants rating 40 video clips, head digitization data for co-registration, and MEG neural recordings from 23 participants viewing the same stimuli. Emotional states were assessed using Self-Assessment Manikin ratings, discrete emotion categories (PrEmo), and temporal highlight annotations, providing multi-faceted ground truth for affective neuroscience research.
NEMAR Dataset nm000103: HBN-EEG NC - Healthy Brain Network EEG data
…MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data…
…Scientific Data, 12, 587. https://doi.org/10.1038/s41597-025-04861…
…Scientific Data, 12, 1069. https://doi.org/10.1038/s41597-025-05378…
An open-access EEG dataset containing recordings from 15 healthy Spanish-speaking subjects performing imagined speech tasks. The dataset comprises 11 imagery classes (5 Spanish vowels and 6 directional commands) acquired using 6-channel EEG at 1024 Hz with preprocessed data (bandpass filtered 2-45 Hz). This BIDS-reformatted derivative is based on the original data described in Pressel et al. 2016 and supports brain-computer interface research and motor imagery classification studies.
…Presented in Rapid Visual Streams.” Scientific Data. https://doi.org/10.1038…
This dataset comprises EEG recordings from 15 healthy subjects performing six different upper limb movements (elbow flexion/extension, forearm supination/pronation, hand open/close) and rest conditions in both movement execution and motor imagery modalities. The study investigates neural encoding of individual upper limb movements using low-frequency EEG signals (0.3-3 Hz) and achieves classification accuracies of 55-87% for executed movements and 27-73% for imagined movements. Source localization analysis identifies discriminative movement information in premotor areas, primary motor cortex, somatosensory cortex, and posterior parietal cortex, with applications toward non-invasive control of motor neuroprostheses and robotic arms.
…MEG-BIDS, the brain imaging data structure extended to magnetoencephalography. Scientific Data…