Behavioral and circuit principles of temperature gradient navigation

Behavioral thermoregulation is critical for survival across animals, including endothermic mammals. However, we do not understand how neural circuits control navigation toward preferred temperatures. Zebrafish exclusively regulate body temperature via behavior, making them ideal for studying thermal navigation. Here, we combine behavioral analysis, machine learning, and calcium imaging to understand how larval zebrafish seek out preferred temperatures within thermal gradients. Using a stimulus-controlled Markov model of thermal navigation, we find that hot avoidance largely relies on the modulation of individual swim decisions. The avoidance of cold temperatures, a particular challenge in ectotherms, however, relies on a deliberate strategy combining gradient alignment and directed reversals. Calcium imaging across the medulla identified seven classes of temperature-responsive neurons. These response types represent position and direction within temperature gradients relative to the preferred temperature. Medullary response types furthermore predict transitions within the Markov model. Medullary encoding thereby enables navigation. Our findings establish a key link between neural activity and thermoregulatory behavior, elucidating the neural basis of how animals seek out preferred temperatures.