…the EEG and (soon-released) Eye-Tracking Section of the Child Mind…
Preprocessed EEG recordings from 20 individuals with a schizophrenia spectrum disorder and 22 healthy control participants performing a visual random-dot motion discrimination task. Participants reported motion direction with a mouse and then rated their confidence on a visual analog scale. Motion coherence was individually adapted with a staircase procedure to match performance between groups, which allows metacognitive processes to be compared.
…the EEG and (soon-released) Eye-Tracking Section of the Child Mind…
This dataset contains behavioral events and intracranial electrophysiological (iEEG) recordings from a spatial navigation memory task. Participants encoded object locations during guided navigation learning trials and then recalled the locations by navigating to them during test trials. Data were collected at multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania.
…the EEG and (soon-released) Eye-Tracking Section of the Child Mind…
Stereo-electroencephalography (SEEG) recordings from 140 patients with refractory epilepsy undergoing presurgical evaluation, who viewed natural object images at 6 Hz with a face image every fifth item (1.2 Hz) in a fast periodic visual stimulation paradigm. The dataset covers 22,160 intracerebral contacts, most with Talairach coordinates and anatomical labels, sampling the ventral occipito-temporal cortex. It is a derivative release of the authors' minimally preprocessed Letswave data, repackaged in BIDS, and supports the study of concurrent category-selective activity in human visual recognition.
…the EEG and (soon-released) Eye-Tracking Section of the Child Mind…
…the EEG and (soon-released) Eye-Tracking Section of the Child Mind…
EEG recordings from four participants performing motor imagery of the left hand, right hand, and feet, originally reported by Zhou et al. (2016) in a study on automated trial selection for motor imagery brain-computer interfaces. Each participant completed three sessions of two runs, giving 450 trials per subject. Data were recorded from 14 channels at 250 Hz and reformatted into BIDS from a MOABB-generated Zenodo version.
This dataset contains continuous scalp EEG and stereo-EEG (SEEG) recordings from 13 patients undergoing video-EEG monitoring in an epilepsy monitoring unit. It supports a prototype human-AI system in which a conversational smartphone agent collects patient and clinician feedback to retrain seizure detection models. The BIDS conversion includes per-recording-day EDF files, event annotations (seizures, patient events, sleep, medications), and derivative model outputs.