High-resolution synaptic and functional connectivity mapping of a neural circuit architecture underlying a behavioral sequence

The ability to generate complex motor behaviors by assembling sequences of movements is essential for purposeful actions and survival. Defects in the brain regions thought to drive such movement selection can lead to behaviors becoming abnormally repetitive (e.g. autism spectrum disorder). Yet, the neural circuit architectures

that underlie this fundamental function of the nervous system remain poorly understood. A central model of a neural circuit architecture that can account for how movements are assembled into sequences has emerged from studies across multiple species. In this architecture, all movements are readied in parallel. Movements

within the sequence are then selected through hierarchical suppression, whereby earlier movements suppress later ones. Prior studies have been unable to decipher how the model might arise from neuronal connectivity and activity, in part due to the overwhelming complexity of neural circuitry in rodent models. We propose to

overcome this barrier through dissection of the neural circuitry underlying sequential body grooming movements in the fruit fly, Drosophila melanogaster. Drosophila offer a useful compromise between complexity and tractability as they display a rich behavioral repertoire, while their brains are numerically compact and have

uniquely identifiable neurons whose activity can be visualized and manipulated using powerful genetic-based techniques. Grooming is ideal for probing the circuit principles of movement sequences because it consists of a predictable sequence of distinct movements. Using this system, we previously showed that the Drosophila

grooming sequence has the hallmarks of a parallel model, and established an infrastructure of tools and approaches to dissect the circuit basis of the model. The objective of this proposal is to define how the neural circuit synaptic connectivity and activity ready the different movements in parallel and then produce hierarchical

suppression, two fundamental mechanisms predicted by the parallel model. In Aim 1, we will define how the circuitry is organized to enable the movements to be readied in parallel. In Aim 2, we will elucidate how hierarchical suppression controls grooming movement selection. These Aims will contribute to the first

description of a neural circuit architecture that produces sequential behavior via hierarchical suppression. Such architectures are not only proposed to underlie movement sequences across species including humans, but can also provide a general mechanism by which competing parallel inputs can be integrated to produce a prioritized

output. Thus, our proposed study in the fruit fly will be relevant to other animals, both for understanding how complex motor behaviors are produced and for understanding neural circuit organization and function more broadly.