Evolution of Sensorimotor Transformation Across Diptera

Maximilian Jösch – IST Klosterneuburg, Austria
Wiktor Młynarski – LMU München

The focus of this proposal is to investigate the neuronal circuits of invertebrates, particularly the lobula plate tangential cells (LPTCs) in the optic lobes of insects. Despite the remarkable similarities in the structure and function of the LPTCs across different insect species, there are significant differences in their morphology and spatio-temporal tuning, which suggest that they have undergone species-specific adaptations to their ecological niches. However, the functional role of this circuitry in behavioral control remains elusive despite decades of research. In the first phase of this project, we have developed innovative behavioral approaches that have revealed the richness of behavioral instructions of the LPTC network, establishing new close-loop paradigms, and using stochastic optogenetic and neurogenetic perturbation. Additionally, we have explored the molecular rules required for proper circuit assembly of the LPTC network from an evolutionary perspective. This involved identifying and characterizing the genes and molecules that are involved in the development and assembly of the LPTC circuit, as well as their presynaptic elements, and performing comparative genomic analysis across Diptera. Building upon our initial successes, the second phase of this project will focus on refining our previous results by determining the complete set of behavioral repertoires instructed by LPTCs and determining the role of evolutionary-informed molecular candidates in circuit function. Our findings suggest that the LPTC circuitry represents a highly optimized and specialized neural system for behavioral instructions. Thus, to provide a comprehensive description and aid further experimental work, we will embed our experimental results in a statistical and theoretical framework to provide a normative perspective on course control behaviors. Ultimately, our goal is to shed light on the evolutionary processes that have shaped the LPTC circuitry and its adaptation to different ecological niches. By understanding the mechanisms by which the LPTC circuitry evolved to control behavior, we will gain insights into the general principles that underlie the evolution of complex neural systems. Additionally, by developing a comprehensive description of course control, we hope to inspire the development of new algorithms and technologies for controlling autonomous systems.