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Andrew X Stewart

Researcher exploring the intersection of neuroscience, machine learning, and signal processing

Paper Highlights

Click on a paper to learn more about the research

Machine Learning

Single-trial classification of EEG in a visual object task using ICA and machine learning

Journal of Neuroscience Methods

This study demonstrates how Independent Component Analysis (ICA) combined with machine learning algorithms can effectively classify single-trial EEG responses during visual object recognition tasks, advancing brain-computer interface research.

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Neuroimaging

The LIMO EEG Toolbox: extending the statistical analysis of EEG data to the spectral domain

Organization for Human Brain Mapping

An extension of the LIMO EEG toolbox enabling robust statistical analysis of spectral EEG data, providing researchers with powerful tools for frequency-domain analysis of brain activity.

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Open Source Projects

Tools and software for the research community

ERPLAB Neuroimaging Toolbox

A powerful MATLAB toolbox for ERP (Event-Related Potential) data analysis. ERPLAB extends EEGLAB's capabilities for processing continuous and event-related EEG data, offering a comprehensive suite of tools for artifact correction, filtering, binning, and statistical analysis.

GitHub Repository Documentation