Structural Variation in Neuronal Circuits as a Basis for Functional and Behavioral Individuality

Project Summary A fundamental gap in our knowledge of the nervous system is understanding how variations in wiring and connectivity of neuronal circuits relate to variability in neural computations and behavior. This gap has arisen because anatomical connectivity and function are typically studied separately. Here, we will assemble a team of researchers with complementary skills to tackle this problem. We will combine several technologies developed in our labs, including in vivo calcium imaging during behavior to study neuronal population activity during perceptually-guided behaviors and high-throughput electron microscopy (EM) to extract the connectivity of an underlying network essential for that behavior. To do so, we will use Drosophila melanogaster as a model system because it has a powerful genetic toolkit, tractable number of neurons, is amenable to large-scale behavioral screens, and is a realistic target for comparative whole-brain connectomics. This makes the fly an excellent model to develop a comprehensive approach to characterize neuronal circuits. We will apply our new approach to investigate how population codes, network connectivity, and structure-function relationships differ between individuals. Although it is well known that individuals, as well as males and females, exhibit variable behaviors, little is understood about how variations in neuronal wiring and connectivity relate to variations in neural computation and ultimately behavior. In our first aim, we will compare population codes, wiring, and connectivity between multiple isogenic individuals that exhibit differences in visually-guided approach behavior. In a second aim, we will apply similar approaches to investigate differences in odor preference behavior. We will test how stochastic brain asymmetry, weighting of sensory signals, and repertoire of local interneurons influence computations within individual brains. Analyzing structure-function relationships across individuals will examine the tradeoff between neuronal circuit precision and variability, and reveal how specific variations shape information processing and behavior. We will generate models predicting neuronal function and behavior from circuit wiring and neuronal structure. Our work will be among the first to compare whole-brain, synaptic-resolution connectomes of multiple individuals to reveal fundamental constraints on functional network organization and discover how circuit variability supports individuality.