PRIOS
…A community-driven specification for organizing neurophysiology data along with its metadata…
- Participants
- 7
- Size
- 27.6 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
76 results for "neurophysiology" · page 4 of 8 · ranked by relevance
…A community-driven specification for organizing neurophysiology data along with its metadata…
This dataset contains EEG recordings collected as part of the NeuroTechs project examining STEM skills. Data were acquired using the Unicorn EEG device and converted to BIDS format, with signal values expressed in microvolts. The dataset is intended to support research on neural correlates of STEM-related cognitive processes.
…A community-driven specification for organizing neurophysiology data along with its metadata…
Imported from OpenNeuro ds003801
…the International Federation of Clinical Neurophysiology. The SD device was used to…
This dataset comprises intracranial EEG (iEEG) recordings collected by the Hamilton Lab at the University of Texas at Austin, compiled as a teaching resource for the WIRED ICM course in Paris, 2024. It includes evoked responses to naturalistic auditory stimuli, such as movie trailers and TIMIT speech corpus sentences, alongside illustrative examples of seizure activity and vagus nerve stimulator (VNS) artifact. The dataset is intended to demonstrate typical and atypical intracranial recording phenomena in patients with epilepsy.
…Clinical Neurophysiology, 124(5), 901-908. https://doi.org/10.1016/j…
Imported from OpenNeuro ds004745
A multi-session EEG dataset acquired from 15 healthy participants performing resting state and graded cognitive tasks (MATB-II at three difficulty levels). The dataset comprises 62-channel EEG recordings at 500 Hz sampling rate designed for passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. Raw EEG data are provided with standardized event annotations using HED 8.4.0 schema and MOABB-compatible feature extraction pipelines (bandpower analysis and Riemannian covariance methods) for benchmarking purposes.
This dataset comprises simultaneous scalp EEG and intracranial EEG (iEEG) recordings from fifteen epilepsy patients undergoing intracranial monitoring while performing a modified Sternberg verbal working memory task. Recordings include depth electrode iEEG, 10-20 scalp EEG, electrode localization (MNI coordinates and anatomical labels), and derived LCMV beamforming virtual sensor data from multiple brain regions (temporal superior lobe, lateral prefrontal cortex, occipital cortex, posterior parietal cortex, and Broca's area). Behavioral data on trial set size, match/mismatch condition, accuracy, and response time are also provided, enabling analyses of memory encoding, maintenance, and recall processes, connectivity, and neural replay.