Learning accurate path integration in ring attractor models of the head direction system.

ABSTRACT: Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading in flies, and where the networ

SUBMITTER: Vafidis P 

PROVIDER: S-EPMC9286743 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature