J. M. Górriz

The paper introduces a task-driven EEG dataset with channel-level motion artifact annotations and demonstrates a hybrid CNN-Transformer model for artifact detection and classification.

The paper uses EEG and multivariate pattern analysis to show that selective attention and perceptual expectation involve distinct neural mechanisms during preparatory processing.

MVPAlab is a MATLAB toolbox for analyzing multidimensional EEG and MEG data using machine learning, offering preprocessing, decoding, and statistical analysis tools.

This paper introduces a framework for neuroimaging using concentration inequalities to improve model validation and hypothesis testing with small sample sizes.

This study uses multivariate pattern analysis on EEG data from a Flanker task to investigate conflict-related neural processes and finds evidence of reinstantiation dynamics.