Quantifying Spatial Domain Explanations in Brain-Computer Interface (BCI) using Earth Mover's Distance

Proposing an optimal transport theory-based approach using Earth Mover's Distance (EMD) to quantify and compare the feature relevance maps generated by different deep learning and Riemannian geometry-based classification models with the domain knowledge of neuroscience in the context of motor imagery-based BCI.