A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies’ HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species. [Display omitted] •Flies need head direction (HD) cells for operant goal learning in visual scenes with heat•Behavior during learning is shaped by co-evolving internal HD and goal representations•Structured but plastic neural circuits provide inductive biases for rapid learning•The stability of internal representations shapes individual variability in learning In novel environments, animals must simultaneously map their surroundings and form goals within them. Dan et al. combine anatomy, physiology, perturbation, and behavior to show how genetically specified circuit architectures with localized plasticity couple multiple evolving internal representations to make this learning fast yet flexible.