Small brains in complex environments: Social and environmental contexts shape decision-making in Drosophila larvae

All animals rely on sensory systems to transform environmental cues into neural representations that guide behavior. A central question in neuroscience is to understand how these signals are processed and integrated to support adaptive decision-making. Despite having a numerically reduced nervous system, the Drosophila melanogaster larva exhibits complex behaviors and is a powerful model organism because of its well-characterized sensory systems, extensive genetic toolkit, and complete connectome. In this thesis, I investigate the behavioral and neural mechanisms underlying decision-making across multiple contexts.

First, I examine how larvae navigate gustatory gradients, a task that requires continuous comparison of sensory input over time. I show that larvae effectively navigate both attractive fructose and aversive salt gradients. In contrast to conclusions drawn from binary choice assays, my results indicate that attractive and aversive taste signals are processed through distinct yet partially overlapping pathways that converge on the mushroom body output neuron MBON-m1, thereby biasing approach and avoidance behavior.

Second, I address how larvae optimize foraging in patchy environments by combining long-term behavioral tracking with computational modeling. Using non-optimal food patches that vary in resource quality (fructose concentrations) and valence (salt at attractive and aversive concentrations), I show that larvae adaptively regulate patch-leaving decisions. These decisions are further shaped by prior experience. A simple integration model captures these dynamics and provides a quantitative framework linking behavioral strategies to underlying neural computations.

Finally, I investigate how larvae recognize conspecifics and how social context shapes larval behavior. Although larvae are not typically considered social, I find that conspecifics modulate behavior even in the absence of external sensory cues and that larvae can prioritize social information over other external cues. These interactions are shaped by developmental experience and require integrating multiple sensory modalities, thereby establishing a foundation for dissecting the neural circuits underlying social modulation.

This work integrates quantitative behavioral assays, computational modeling, connectomic analysis, and genetic manipulations to investigate decision-making across contexts and establishes the Drosophila larva as an effective model for studying the neural and computational principles underlying naturalistic behavior.