Attractor-like circuits improve visual decoding and behavior in zebrafish

Abstract

Attractor networks are neural circuits with stable states that represent information or memories. They play a crucial role in memory retrieval, decision-making and integrating noisy cues. In zebrafish larvae, the spontaneous dynamics of the optic tectum is structured according to topographically organized neuronal assemblies exhibiting attractor-like behavior. Here, we took advantage of the Methyl-CpG-binding protein 2 (MeCP2) deficient zebrafish mutant, which displays perturbed tectal dynamics, to study the functional role of the attractor-like circuits in visual processing. In comparison to wild-type larvae, the mecp2-mutant showed reduced functional connectivity in the optic tectum. This abnormal connectivity significantly affected the visual response, and the ability to discriminate between visual stimuli. Finally, the mutant larvae where less efficient in hunting paramecia. We argue that the attractor dynamics of the tectal assemblies improve stimulus discrimination, visual resolution, and increase the sensitivity to behaviorally relevant visual stimuli.