Unsupervised alignment in neuroscience: Introducing a toolbox for Gromov-Wasserstein optimal transport.
Journal:
Journal of neuroscience methods
Published Date:
Apr 14, 2025
Abstract
BACKGROUND: Understanding how sensory stimuli are represented across different brains, species, and artificial neural networks is a critical topic in neuroscience. Traditional methods for comparing these representations typically rely on supervised alignment, which assumes direct correspondence between stimuli representations across brains or models. However, it has limitations when this assumption is not valid, or when validating the assumption itself is the goal of the research.
