…Using Support Vector Machines (SVMs) with L1 regularization, we achieved cross-context…
Nejedly2020 multicenter iEEG graphoelement clips (MAYO) This BIDS dataset is converted from…
…generic model hyperparameters ## Use Cases ### Machine Learning - **Sequence-to-sequence learning**: Similar…
This dataset contains functional near-infrared spectroscopy (fNIRS) recordings collected during a word-color Stroop task using a sparse fNIRS montage. It accompanies a study comparing high-density, multi-distance fNIRS with sparse configurations for detecting task-related brain activity. The data are organized in BIDS format and are mirrored on NEMAR from OpenNeuro.
…Riemannian manifold methods and relevance vector machines for brain-computer interface applications…
Magnetoencephalography (MEG) recordings from participants performing auditory single word recognition. The dataset accompanies a study of auditory word comprehension in isolated words and is organized in BIDS format. Stimuli and TextGrids come from the Massive Auditory Lexical Decision database.
…Data were analyzed using Riemannian manifold methods and relevance vector machines for…
…using Riemannian manifold and relevance vector machine approaches for brain-computer interface…
…based feature extraction and relevance vector machine classification, achieving approximately 49% mean…
TMNRED is an EEG dataset recorded from 30 native Chinese speakers during natural reading of news headlines and short sentences. Participants identified fuzzy semantic targets among target and non-target items. The dataset supports research on semantic processing of Chinese in naturalistic reading and includes raw and preprocessed data in BIDS format.