Chisco-2.0 is an EEG dataset of imagined speech recorded from two participants (sub-01 and sub-02). The raw recordings are provided in EDF format and organized according to the BIDS standard. The dataset is intended to support research on decoding imagined speech from brain activity.
…20.0 Hz ## Signal Processing - **Classifiers**: PLS regression with UKF smoothing - **Feature…
…to understand how Personalized smartphone notifications bias auditory salience across processing stages
…Freesurfer outputs, MNE-related files, predictor objects, and processing scripts ## Citation Please…
…This makes the task great for investigating reward processing & reward prediction error…
This dataset contains raw neuroimaging recordings collected with the Visual Attribute-Specific Contextual Trajectory Paradigm 2.0. The paradigm is used to study how the brain generates domain-general visual surprise signals and how their latency depends on the visual attribute that is violated. It accompanies a pre-print on attribute-dependent latency of visual surprise signals.
A BIDS-standardized subset of the EEGEyeNet dataset containing simultaneously recorded EEG and eye-tracking data from a single subject. The original EEGEyeNet resource was designed as a dataset and benchmark for eye movement prediction from EEG. This version was reformatted to BIDS to support reuse and standardized analysis.
Intracranial EEG (ECoG) recordings from 14 epilepsy patients implanted with clinical surface and depth electrodes, with two patients also carrying high-density research grids. Participants viewed grayscale pattern stimuli and color images of several categories. Stimuli varied in spatial and temporal properties, including pRF mapping bars, spatial and temporal patterns, and six-category localizers. Pre-implantation T1 MRI, FreeSurfer surface reconstructions and derivative broadband and preprocessed data are included.
A multimodal SSVEP dataset of 64-channel EEG, an EOG channel, and stimulus markers recorded from 31 healthy participants over up to 3 sessions each (63 sessions in total). Participants viewed LED stimuli flickering at four frequencies in a 4-class SSVEP paradigm (48 trials per session). It is the SSVEP component of a larger resource combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms, and is formatted for use with MOABB.
…Effect of obesity on arithmetic processing in preteens with high and low…