Identification of conserved circuit logic in temperature navigation behavior in fish and fly

Ruben Portugues - MPI of Neurobiology, München
Ilona Grunwald Kadow - Technische Universität München

Temperature critically affects the physiological processes of an organism. A failure to assess its absolute value and rate of change can have a spectrum of consequences, from tissue damage to failure of the entire system. Therefore, animals have evolved different strategies to maintain their body temperature in a narrow optimal range. Regardless of the specific strategy, the brain plays a crucial role in detecting temperature changes, evaluating them in the current context and state of the animal, and directing both physiological and behavioral changes. Given the importance of temperature control for most animals, we postulate the existence of fundamental neurocomputational features shared by different animal species. Specifically, we are interested in where relative changes, as opposed to absolute values in temperature, are computed and then combined with current state and past experience, in order for the nervous system to implement changes in behavior and maintain its temperature optimum. We will compare two classic genetic model organisms, Drosophila melanogaster and Danio rerio, by taking advantage of their genetic tractability and access to the nervous systems. In particular, we will test the hypothesis that fish and flies use a similar decision process and underlying neural network structure in order to control their locomotion and maintain optimal body temperature.