Mala Murthy, PhD - US grants

Neural tuning for species-specific acoustic signals is a conserved feature of auditory systems; it is found from insects to humans. This proposal takes advantage of the genetic tools available in Drosophila to investigate, at the level of individual neurons and patterns of electrical activity, how such tuning arises and how it relates to behavioral outputs. Research findings will contribute to a larger understanding of how nervous systems process auditory information.

Flies communicate via species-specific courtship songs during their mating ritual. Songs are typically produced by males; females are faced with the task of recognizing song, based on its species-specific parameters, and choosing a particular mate, based in part on differences in song between conspecific individuals. The PI proposes to characterize the circuits that underlie this behavior by i) resolving the features of courtship song that drive mating, ii) characterizing, using in vivo imaging and electrophysiology methods, neural responses along the auditory pathway, and iii) determining the relationship between neural tunings and song preference by exploiting cross-species comparisons. As the fly auditory pathway remains unmapped past the receptor neurons, these studies will be among the first to reveal how sound is processed by the Drosophila brain. Ultimately, these results may shed light on mechanisms underlying acoustic perception in more complex nervous systems and may benefit studies of disorders (e.g., autism spectrum) that alter this process.

The research proposal is complemented by an education plan that is directed at inspiring the next generation of neuroscientists at the middle school, high school, and undergraduate levels, and at fostering the entrance and advancement of women in science. The PI will i) develop a new neuroscience course on the genetic and neural basis for behavior for Princeton undergraduates, ii) create a Fly Songs demonstration for area middle school students participating in the Princeton Science and Engineering Expo, and iii) initiate a new and intimate Science Scholars Workshop at Princeton for high school girls from nearby economically-underprivileged areas, providing them exposure to cutting edge research at the university level and encouragement to pursue careers in science, particularly in more computational disciplines.

Animals, from insects to humans, are inherently social, and brains have evolved to be most sensitive to sensory cues that carry social information (for example, speech sounds or pheromones). Very little is known regarding how animal brains process information in the context of social interactions. This proposal seeks to address this complex issue by focusing on the relatively simple nervous system of the fruit fly Drosophila, and takes advantage of the wealth of tools available in this system to dissect the mechanisms underlying social behaviors. The three principal investigators (Murthy, Shaevitz, and Bialek) are experts with behavioral analysis, theory/modeling, and neural circuit analysis, and will use several new methods to study courtship, a robust social behavior that has been shown to involve a complex interaction of a male and a female. This work will not only uncover the mechanism by which sensory inputs and internal states interact to generate behavior, but also benefit studies of disorders (e.g., autism spectrum) that impact the social brain. The research project is complemented by outreach efforts targeted at educating undergraduates, and in particular young women, in modern methods in computational neuroscience.

Animals, from insects to humans, spend a majority of their time engaged in social behaviors, and brains have evolved to be most sensitive to these dynamics and timescales, as they are important for survival. Social interactions involve both sensory perception (detecting cues generated by another individual) and coordinating motor outputs (to generate social behaviors). Most studies examine sensory and motor pathways in an "open loop" framework; however, social interactions are inherently "closed loop", as data gathered through the senses of each individual is profoundly shaped by his/her own actions and those of the other individual. With new methods and new theoretical frameworks, this proposal aims to solve the closed loop aspect of sensory perception between animals using the fruit fly Drosophila melanogaster as a model system. The investigators have pioneered several new methods to facilitate these studies and are experts with behavioral analysis, theory/modeling, and neural circuit analysis. They will combine unbiased behavioral quantification, whole-brain imaging in behaving animals, controlled sensory stimuli, and theoretical modeling to uncover the neural circuit dynamics underlying social behaviors and decision-making. A detailed analysis of the simultaneous behaviors of two courting flies will lead to the first rigorous and quantitative analysis of the dynamic sensory cues and interactions between individuals that shape social behaviors. Theoretical work on these data will reveal the dynamic neural computations that must be active during courtship. Finally, neural circuit recordings in animals engaged in closed loop fictive social interactions will be used to link brain activity to specific courtship behaviors and decisions.

Abstract The ability to recognize complex patterns in nature is typically effortless for the human brain. For example, healthy humans can easily recognize faces, complex odor mixtures and tastes, and words and sentences, even when the patterns are corrupted by noise or occur in different contexts. Pattern recognition is not only essential for communication and interacting with the environment, it is also key to memory formation. However, the underlying mechanisms involved remain mysterious. We do not yet have a complete solution for how any brain (of any model system, large or small) solves this problem, and programming a computer to accomplish the feats of pattern recognition that humans are capable of is still an active area of research. This presents a major roadblock towards treating the large number of individuals with various pattern recognition deficits (e.g., patients suffering from central auditory processing disorder, visual agnosia, autism spectrum disorder, various neurodegenerative diseases, or a recent stroke). Here we propose to find a solution to this problem in a brain capable of pattern recognition, but with orders of magnitude fewer neurons than most mammalian brains. My lab has recently demonstrated, using quantitative behavioral assays, computational modeling, and neural circuit manipulations, that flies can both produce and detect dynamic acoustic patterns that vary over multiple timescales. Moreover, we have uniquely pioneered methods to functionally characterize neurons of the acoustic communication system of Drosophila, from sensory inputs all the way to motor outputs. Building on these achievements, we now propose a strategy for recording from the complete set of input and output neurons of the network(s) underlying acoustic pattern recognition in this model system, and for mapping the underlying connections. To do this, we focus on testing two prominent hypotheses (posited across model systems) for how the brain accomplishes song pattern recognition. The first experiments test the hypothesis that a precise balance of excitation and inhibition within the auditory pathway, ultimately generating sparse and selective responses, is required for temporal feature selectivity and song pattern recognition. The second experiments test the hypothesis that song pattern recognition relies on template matching, or a neural network that compares the incoming auditory signal to an internal representation of a particular pattern. The ultimate goal of this line of research is to inspire the design of simple (based on few neurons) neural prosthetic devices to restore or supplement brain function lost during disease or injury. Because patterns in fly song and human speech vary over similar timescales, neural computations for recognizing song patterns in Drosophila should be informative for solving pattern recognition in more complex systems. More broadly, our results will contribute to a deeper understanding of how nervous systems process auditory and species-specific information, and have the potential to transform our understanding of how nervous systems produce sensory- driven behaviors.

Project Summary/Abstract Social interactions across the animal kingdom, from courtship rituals and aggressive interactions to spoken conversation, are wondrously complex - they necessarily involve back- and-forth feedback between nervous systems transmitted through multiple sensory modalities and each animal's behavior. Typical experiments in this field observe only a tiny fraction of the activity in any neuronal circuit, and then only under a very limited range of behavioral conditions. To overcome this limitation, the proposed research leverages the compact nervous system of Drosophila melanogaster, combined with its wealth of genetic tools, to study the dynamic behavioral interactions and detailed neural mechanisms that underlie courtship between males and females. The project combines unbiased measurement of behavior, neural circuit manipulations, neural recordings in behaving animals, and sophisticated computational models. The specific aims include: i) elucidating the computations that the brain performs during courtship by mapping the sensorimotor transformations underlying male and female interactions over time via quantitative behavioral assays and the generation of predictive models; ii) combining models with neural perturbations to map the underlying circuits that govern the link between sensory inputs and behaviors; And, iii) testing the models of neural control during courtship by monitoring neural activity in behaving animals experiencing fictive courtship stimuli in a virtual-reality apparatus. This work will substantially advance our understanding of how two interacting brains process and transfer information, and will uncover general principles of neural circuit function that will inform studies of sensorimotor integration in more complex animals, such as rodents and humans. The project will also produce new experimental and theoretical tools for studying social behaviors. Finally, it will shed light on the mechanisms that go awry in several disorders, including Autism Spectrum Disorder (ASD), in which sensory perception becomes disentangled from motor outputs ? these disorders have profound effects on cognitive well-being and a major impact on public health.

Project Summary: Natural sensory inputs are typically complex, and often combine multiple modalities. Human speech, for example, combines auditory signals with visual cues, such as facial expressions, that inform the interpretation of the spoken words. As individual sensory pathways only provide a partial representation of the sensory information available, selecting the context-appropriate behavioral response to a multimodal stimulus often requires integrating information across modalities. How do neural circuits perform this fundamental computation? Our current understanding of sensory processing is predominantly built upon studies that have focused on single sensory modalities, working into the brain beginning from sensory receptors. As a result, we have a deep understanding of peripheral circuit computations in many different experimental contexts. However, working inward, cell-type by cell-type, has left our understanding of the circuits and computational principles that link sensation to action incomplete. Moreover, experimental strategies that focus exclusively on single sensory modalities cannot, by design, lead to insights into how the unified percepts that guide behavior can be assembled from information emerging in separate sensory processing streams. Here we leverage whole-brain imaging and advanced computational approaches to establish the fruit fly Drosophila as a model system for uncovering fundamental principles underpinning multisensory integration. This proposal has three goals. First, we will optimize whole-brain imaging in this experimental system, and use this technology to comprehensively characterize population dynamics underpinning the sensations of vision, mechanosensation and taste. Second, we will systematically quantify circuit interactions between these sensory modalities and across-animal variability, testing computational models of statistical inference, and identifying the algorithmic bases of multimodal integration. Third, we will link population dynamics to the response properties of single cell-types, providing a powerful path to characterizing circuit and synaptic mechanisms. Taken together, by developing and applying improved methods for large-scale monitoring of neural activity, combined with computational modeling and quantitative analysis, this project will greatly expand our understanding of sensory processing mechanisms across the brain.

Over the past eight years, my lab has pioneered studies of the acoustic communication system of Drosophila, to address fundamental questions related to the neural mechanisms underlying sensory perception and the generation of behaviors. Similar to other animals, flies produce and process patterned sounds during their mating ritual. Using a combination of novel behavioral assays, neural circuit perturbations, neural recordings, and computational modeling, we discovered that male song structure and intensity are continually sculpted by interactions with the female, over timescales ranging from tens of milliseconds to minutes. Building on this finding, we have gone on to dissect the neural mechanisms underlying the visual modulation of song patterning in males. Using a similar set of tools, we have also interrogated the female side of acoustic communication, and have successfully related song representations along the auditory pathway to changes in locomotor behavior, again across multiple timescales. My lab has developed several new methods to facilitate these studies, including methods for tracking and segmenting animal behavior, for population neural imaging, and for single-cell transcriptomics in the Drosophila brain. Our system and discoveries lay the essential foundation for now solving the bigger challenge of how an animal's internal state and experiences contribute to shaping these neural mechanisms. To do so, we will employ new computational models to identify the neural correlates of internal state. We will also use a new paradigm to induce learning during acoustic communication, and will characterize how learning shapes sensorimotor integration in this system. Finally, we will manipulate the hunger or arousal status of flies to determine, again at the cellular level, how long timescale modulation of neural activity shapes fast timescale sensorimotor processes. These new research directions will leverage the methods we have optimized for the recording and analysis of neural and behavioral data, in addition to incorporating new methods for recording activity in behaving flies that experience naturalistic, multimodal courtship stimuli timed to their movements on a spherical treadmill. What we discover in this system will reveal fundamental principles regarding how brains mediate perceptions, thoughts, actions, and ultimately the ability to communicate with another individual.