The Developmental Rules of Neural Superposition in Drosophila

Complicated neuronal circuits can be genetically encoded, but the underlying developmental algorithms remain largely unknown. Here, we describe a developmental algorithm for the specification of synaptic partner cells through axonal sorting in the Drosophila visual map. Our approach combines intravital imaging of growth cone dynamics in developing brains of intact pupae and data-driven computational modeling. These analyses suggest that three simple rules are sufficient to generate the seemingly complex neural superposition wiring of the fly visual map without an elaborate molecular matchmaking code. Our computational model explains robust and precise wiring in a crowded brain region despite extensive growth cone overlaps and provides a framework for matching molecular mechanisms with the rules they execute. Finally, ordered geometric axon terminal arrangements that are not required for neural superposition are a side product of the developmental algorithm, thus elucidating neural circuit connectivity that remained unexplained based on adult structure and function alone. [Display omitted] [Display omitted] •Intravital imaging reveals growth cone dynamics during an entire wiring process•Three simple rules are sufficient to generate the seemingly complex neural circuit•A computational model suggests a method for robust targeting in a dense brain region•Aspects of adult circuitry can only be understood in light of developmental algorithm Neural superposition describes a complicated connectivity map in the fly visual system that has fascinated natural scientists for many decades. This study reveals three simple rules that are sufficient to generate the wiring pattern based on intravital imaging and data-driven computational modeling.