Evolution of sensorimotor transformation across diptera

Maximilian Jösch - IST Austria, Klosterneuburg
Fyodor Kondrashov - IST Austria, Klosterneuburg

Neuronal circuits evolved ultimately to control behavior. Their intricate connections reflect an evolutionary process that selects for efficient behaviors. Yet, the way in which these circuits implement them is mostly unclear, because it requires one to relate neuronal representations to animal behavior. This daunting task is made considerably easier by studying insects compared to vertebrates, due to their compact and stereotyped neural circuits that govern innate behaviors. Moreover, insects allow for powerful comparative studies; closely-related species may have altered their behavioral strategies by manipulating a conserved set of underlying circuit motifs. Here we aim to take advantage of functional and comparative genomics, proteomics, as well as a system neuroscience perspective, to uncover the underlying genetic mechanisms and functional specialization of circuit adaptations across Diptera. First, we will unravel the differential roles of the visually-guided course-control network in the lobula plate circuitry, called by some the “cockpit of the fly”. By using a novel high-throughput combinatorial approach to characterize behavior, we aim to determine the space of behavioral instructions this network can command. In parallel, we will uncover the molecular mechanisms that are required to wire this network in Drosophila melanogaster and compare the evolution of both the coding and enhancer regions of these genes across all sequenced Diptera – genes that determine the structure and thus the functional adaptations of the LPTC network. Finally, we aim to combine both approaches to establish transgenic Drosophilae that carry site-specific genetic variation found across species and test these modified networks morphologically, physiologically and behaviorally to determine the role of introduced structural changes. Understanding these neuronal adaptations and their behavioral implications across species will confine the parameter space of efficient computations and provide by definition a description of forming principles of neuronal computation. Determining the variations in morphology, connectivity, and activity of these circuits will inform us about circuit function, give us a new platform to study development and ultimately teach us about evolution.