SueYeon Chung

The paper analyzes how olfactory memory in zebrafish is represented through neural manifolds, finding that training enhances the separation of task-relevant odor representations.

The paper shows that mice can discriminate odors in complex mixtures primarily limited by neural sensitivity rather than background complexity.

This study shows a random network with sparse inhibition can explain multiple hippocampal place cell phenomena without requiring specific connectivity or plasticity.

The paper shows how diversity in neuronal tuning amplitude and bandwidth improves perceptual performance through changes in representational geometry.

This paper introduces GLUE, a framework linking neural activity geometry to computational efficiency, showing task-relevant representations untangle across various domains.

The paper investigates an alternative spatial code in hippocampal coactivity dynamics, showing that environment decoding from ensemble coactivity improves with experience and relies on anti-cofiring cell-pair relationships.

This study examines how parietal cortex neurons transform acoustic information into decision variables during auditory tasks, showing task-dependent changes in neural decoding and clustering.

This study examines how classification capacity in deep neural networks improves with hierarchy, showing that changes in object manifold geometry underlie this improvement.