Linking brain and behavior states in Zebrafish Larvae locomotion using hidden Markov models.

ABSTRACT: Understanding how collective neuronal activity in the brain orchestrates behavior is a central question in integrative neuroscience. Addressing this question requires models that can offer a unified interpretation of multimodal data. In this study, we jointly examine video-recordings of zebrafish larvae freely exploring their environment and calcium imaging of the Anterior Rhombencephalic Turning Region (ARTR) circuit, which is known to control swimming orientation, recorded in vivo under tethered conditions. We show that both behavioral and neural data can be accurately modeled using a Hidden Markov Model (HMM) with three hidden states. In the context of behavior, the hidden states correspond to leftward, rightward, and forward swimming. The HMM robustly captures the key statistical featu

SUBMITTER: Dommanget-Kott M 

PROVIDER: S-EPMC12803470 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature