Circuit principles of demotivation in the decision to switch behaviors

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Project Summary: The decision to commence a new behavior often requires termination of the ongoing behavior. This implies that the many drive states produced by an animal impact not only the neural circuits underlying their directly associated behaviors, but also those of many other behaviors. My lab has shown that the mating behaviors of male Drosophila are under motivational control and may be abandoned in the presence of stimuli evoking competing drives—depending on the relative intensities of the contending drives. These behaviors are motivated by dopaminergic neurons, one of many features shared with human motivational control. I present preliminary data demonstrating that multiple competing drives integrate synergistically to cause male Drosophila to prematurely terminate copulations that would last ~23 minutes if left undisturbed. This integration occurs at a set of eight male-specific, GABAergic Copulation Demotivating Neurons (CDNs) that cause immediate termination when stimulated beyond a threshold and can integrate diverse inputs over long timescales. During the first 5 minutes of mating, even the most severe threats cannot stimulate the CDNs and therefore do not cause termination; but as the mating progresses the CDNs become more accessible to diverse demotivating stimuli, gradually permitting termination in response to weaker and weaker inputs. I present a computational model for synergistic integration of competing inputs at behavior-specific demotivating neurons, demonstrating how this circuit logic can promote either behavioral stability, or flexibility, depending on the individual strengths of the full complement of drive states. I also propose a novel hypothesis for how behavior- specific demotivating neurons increase their sensitivity as the goals of the behavior are achieved. These experimental findings place the rarely studied topic of demotivation at the center of behavioral decision making and our computational work suggests several novel and testable hypotheses. The main goals of this grant are i) to understand how information from competing drives is processed and delivered to behavior-specific demotivation circuitry; and ii) to understand how this information is integrated with the motivational state of the ongoing behavior to decide whether or not to switch behaviors. This work will establish a new, front-line model system for high-order interactions between multiple motivations, with strong indications that the principles and models we derive will provide a framework for understanding motivations and decision making in humans. Project Relevance: This project explores a fundamental but understudied principle of motivational regulation: demotivation as goals are achieved and circumstances change. Dysregulation of motivation is central to drug addiction, depression, compulsive disorders, among many other behavior and mood disorders. The robust behaviors and precise manipulations in this proposal will relate neuronal activity to behavior and allow a direct attribution of causality. The data collected will be used to extend our circuit and computational models that are generalizable across animals and behaviors.