Driving with Autonomous Aids
…Such factors will include real-time tracking of variables such as task…
- Participants
- 24
- Channels
- 64 (10-10)
- HED
- v8.1.0
- Size
- 43.1 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
100 results for "neural tracking" · page 6 of 10 · ranked by relevance
…Such factors will include real-time tracking of variables such as task…
This dataset comprises human electroencephalography recordings from 20 participants performing a visual attention task involving rapid sequences of overlaid oriented gratings. Participants detected target gratings while manipulating both attention (cued by color) and temporal expectation (predictable vs. unpredictable stimulus onset timing). The study dissociates feature-based attention effects from temporal expectation and target-related decision processes, providing insights into the temporal dynamics of selective attention.
…of cognitive overload; (2) studying neural (event-related potentials and brain oscillations…
…Subjects were then outfitted and prepped for eye tracking and EEG acquisition…
This dataset comprises 64-channel EEG recordings from 7 participants performing an auditory imagery task, in which they imagined sounds associated with animals and tools following visual stimulus cues. The dataset is intended to support research on semantic decoding of imagined auditory content and brain-computer interface applications.
…Eye tracking data is not included in this dataset. **Initial setup:** Upon…
The PURSUE N170 Face Perception dataset comprises event-related potential (ERP) recordings from a face perception task conducted across three undergraduate institutions. Data were collected from participants in 2017-2018 using a standardized task design documented in the ERP CORE resource. This dataset provides a multisite contribution to open-access human electrophysiological research on face processing and the N170 component.
…Subjects were then outfitted and prepped for eye tracking and EEG acquisition…
This dataset contains multimodal brain–machine interface (BMI) recordings from seven healthy adults who trained over nine longitudinal sessions to control a lower-limb exoskeleton via motor imagery. It includes 60-channel EEG, 4-channel EOG, dual IMU motion data, and exoskeleton control/feedback signals collected during open-loop calibration and closed-loop walk/stop trials. The dataset supports research on EEG-based decoding of motor imagery for neurorehabilitation and human-robot interaction applications.
…EEG and (soon-released) Eye-Tracking Section of the Child Mind Network…