ExBrainable: An Open-Source GUI for CNN-based EEG Decoding and Model Interpretation

TL;DR

ExBrainable is an open-source GUI designed for CNN-based EEG decoding, enabling easy model training, evaluation, and visualization to facilitate neuroscience research across disciplines.

Contribution

It introduces a user-friendly GUI for CNN EEG decoding, combining training, evaluation, and visualization in a single platform, simplifying access for researchers.

Findings

Effective CNN model training and visualization for EEG data

Comparison with neuroscience knowledge validates the approach

Facilitates interdisciplinary EEG decoding research

Abstract

We have developed a graphic user interface (GUI), ExBrainable, dedicated to convolutional neural networks (CNN) model training and visualization in electroencephalography (EEG) decoding. Available functions include model training, evaluation, and parameter visualization in terms of temporal and spatial representations. We demonstrate these functions using a well-studied public dataset of motor-imagery EEG and compare the results with existing knowledge of neuroscience. The primary objective of ExBrainable is to provide a fast, simplified, and user-friendly solution of EEG decoding for investigators across disciplines to leverage cutting-edge methods in brain/neuroscience research.