…In an extensive offline analysis, we compare our sophisticated encoding model with…
A BIDS conversion of a multicenter intracranial EEG (iEEG) dataset of 3-second single-channel clips for classifying graphoelements (physiological and pathological activity) and artifactual signals. Clips were recorded from stereo-EEG contacts at 5000 Hz and concatenated into runs per subject and contact. Events preserve the original labels, segment IDs, anatomy, reviewer IDs, seizure onset zone flags, and electrode types.
…This study contains open-loop electrical stimulation of the brain during encoding…
EEG dataset of 15 healthy participants performing a four-class auditory stream segregation multiclass ERP (ASME) brain-computer interface task. Two strategies for achieving four classes were compared: ASME-4stream (four streams, one target stimulus each) and ASME-2stream (two streams, two target stimuli each). P300 responses, binary classification and offline BCI simulation with linear discriminant analysis showed average accuracies of 0.83 and 0.86, respectively. NASA-TLX workload ratings were also collected.
A calibrated task subset of Kai J. Miller's library of human electrocorticographic (ECoG) data, comprising 111 recordings from 24 epilepsy patients with subdural electrode grids. Tasks include finger flexion, hand gestures, motor movement and imagery, and verb generation and noun reading. Data were recorded at 1 kHz and converted to BIDS in BrainVision format with source-documented amplitude calibration.
A BIDS example dataset demonstrating annotation of intracranial EEG (iEEG) recordings with the HED schema library for SCORE (Standardized Computer-based Organized Reporting of EEG). It contains iEEG data from one subject recorded during clinical photic stimulation at Mayo Clinic. Events are annotated through an events.tsv column whose levels are defined as HED tags in the events.json sidecar, yielding machine-readable annotations validated with the BIDS and HED validators.
…1) Encoding: participants were presented with a series of audiovisual speech movies…
EEG recordings from 25 healthy, BCI-naive right-handed participants performing motor imagery of two joints of the same limb (right hand and right elbow). Each participant completed 15 sessions over 3 days, giving 600 trials with 62-channel EEG sampled at 1000 Hz plus EOG. The dataset supports research on decoding fine-grained motor imagery within the same limb for motor rehabilitation and prosthetic control BCIs.
[ time-series dataset converted to BIDS format from a MATLAB file containing hemoglobin concentration time series (HbO) from 18 subjects across two sessions, with ICA-based denoising applied. The dataset is a BIDS conversion of an original deposit and includes NIRS recordings and associated metadata.