Yuhang Song

This paper introduces a model where neurons adjust synaptic strengths to minimize somato-dendritic mismatch, enabling network learning and reproducing experimental observations of plasticity.

This paper introduces a new credit assignment mechanism called prospective configuration, showing it can enable efficient learning in biological contexts and replicate observed neural behaviors.

The paper proposes a temporal difference model that explains how dopamine neurons encode different reward dimensions and adapts behavior based on physiological needs.

This paper proposes predictive coding models that implicitly learn covariance information for associative memory, unifying predictive coding and covariance learning in hippocampal networks.