100 results for "emotion processing" · page 6 of 10 · ranked by relevance
This magnetoencephalography (MEG) dataset comprises neuroimaging data collected to establish standardized protocols for cross-site pooling of MEG data. The dataset demonstrates the application of BIDS formatting to MEG neuroimaging, facilitating data harmonization and reproducible analysis across multiple research institutions.
[ recordings from 50 healthy control participants performing a reinforcement learning task under two mood conditions (sad and happy mood manipulation). The study examines how affective state influences learning and decision-making processes, with data collected between 2019-2021. The task includes distinct training and testing phases, with mood manipulation administered prior to each training block.
[ 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.
…82901/nemar.on004262) # Continuous Feedback Processing Twenty-one participants learned to predict…
This dataset comprises intracranial EEG recordings from 14 epilepsy patients implanted with clinical surface and depth electrodes, collected during visual stimulation tasks between 2017-2020. Participants viewed grayscale patterns with varied spatial and temporal properties, as well as color images from six semantic categories, while performing a fixation task. The dataset includes raw voltage data, common-average-referenced recordings, broadband responses, preprocessed epochs, and surface reconstructions with electrode localizations, enabling investigation of neural dynamics in human visual cortex.
The YOTO (You Only Think Once) dataset is a human electroencephalography resource comprising high-resolution EEG recordings from 20 participants performing multisensory perception and mental imagery tasks. Signals were acquired at 1000 Hz sampling rate during exposure to unimodal (visual and auditory) and multimodal stimuli, with participants providing subjective vividness ratings. Technical validation through event-related potentials and power spectral density analyses confirmed distinct neural responses across stimulus conditions, supporting applications in neural decoding, perception, and cognitive modeling.
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