Francesca Greenstreet

Modelling dopaminergic signals associated with habit formation through temporal-difference action learning

This paper models dopaminergic signals linked to habit formation using temporal-difference action learning, showing that action prediction errors better represent striatal dopamine activity than reward prediction errors.

Why motor learning involves multiple systems: an algorithmic perspective

This paper proposes a computational framework where the cortico-cerebellar network learns low-dimensional action embeddings and the basal ganglia use reinforcement learning to learn value and policies, demonstrating its relevance to motor learning.

Action prediction error: a value-free dopaminergic teaching signal that drives stable learning

This study identifies a movement-based dopamine signal in mice that acts as a value-free teaching signal for learning sound-action associations, working alongside reward prediction error.