Locomotory Control Algorithms and Their Neuronal Implementation in Drosophila melanogaster

Citation

Palmer, Emily Hope (2023) Locomotory Control Algorithms and Their Neuronal Implementation in Drosophila melanogaster. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/yyjd-a554. https://resolver.caltech.edu/CaltechTHESIS:05192023-015643241

Abstract

Scientists and engineers alike have long looked to animals in their pursuit of understanding the natural world and how best to interact with it. While researchers have looked across diverse classes, insects have been extensively studied for their rich diversity of life histories and abilities to perform at spatial and temporal scales difficult for engineered systems. Within insects, the fruit fly, Drosophila melanogaster, is a particularly well-studied organism because of its experimental tractability and status as a genetic model organism, providing both detailed descriptions of a broad suite of behaviors and access to and control over specific sets of tissue. In this work, we make use of these tools to study two behaviors in Drosophila, local search, the behavior in which walking flies will search the area around a food site in search of other food sources nearby, and the optomotor response, wherein they will stabilize in response to visual motion during flight. In these studies, we will use modern techniques from both biology and engineering, to exhaustively characterize and describe the observed behaviors and attempt to untangle the underlying algorithms and their neuronal implementation.

First, we explore the algorithmic structure of local search in fruit flies. When flies encounter a piece of food, they will often perform walking searches nearby; as food tends to be patchy in natural settings, searches may allow flies to locate other food sites in the area. We induce local search using optogenetic stimulation of sugar-sensing neurons and constrain the flies to a dark, annular arena. These experimental details result in a simplified behavior, as the fly has access to a limited sensory environment, so that the search can be interpreted as an example of idiothetic path integration, and the search itself is one-dimensionalized and therefore more easily analyzed. Our experiments, in tandem with complementary modeling using a state transition diagram formalization of the behaviors, generate two principle findings. First, flies can integrate their location in two dimensions--after the optogenetic activation is disabled and the flies can no longer receive the food stimulus, they will continue to search over the former food site even after completing a full revolution of the annular arena. Second, when multiple food sites are present, they search over a center of the food sites, rather than over one distinct food site. These results both provide insights into the algorithmic structure of local search and an experimental and descriptive paradigm for further inquiries into the behavior.

Second, we investigate the role of a population of neurons, the DNg02s, in the optomotor response. In response to visual patterns of wide-field motion, such that the entire world is moving in the fly-centric reference frame, the animal will attempt to steer to cancel the visual motion, as the most parsimonious explanation of the motion is that the fly itself is moving in the global reference frame. We demonstrate that the DNg02 neurons are a required component in the neural circuitry underlying the optomotor response, but that they are insufficient to induce steering behaviors. We conclude with a set of models that fully recapitulate the collected dataset. With current techniques, distinguishing between the two possible models of the downstream connectivity from the DNg02s to the motor neurons associated with wing motor output is not possible. However, as new datasets become available, particularly complete connectomes of the Drosophila nervous system, the neuronal pathways from the DNg02s to the motor systems may be elucidated.

Thesis Files