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Circuits principles of memory-based behavioral choice

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SNA - Theoretical foundations for statistical network analysis

Choosing which behavior to generate based on sensory inputs and previous experience is crucial for survival. To understand the circuit principles by which experience-driven behavioral choices are made it is essential to determine the architecture of networks that mediate these functions, and determine the causal relationships between the structural motifs and function. We combine three levels of analysis: i) circuit mapping with synaptic resolution; ii) physiological measurements of neural activity and iii) neural manipulation in freely behaving animals to dissect the logic of memory-based behavioral choice in Drosophila larva. In an EM volume that spans the entire nervous system we reconstructed a complete wiring diagram of the higher order parallel fiber system for associative learning, the Mushroom Body (MB), including the pathways from the conditioned (CS) and unconditioned sensory (US) neurons to the MB, and the patterns of interactions of MB output neurons with circuits that mediate innate responses to CS and US. Using calcium imaging and optogenetic manipulation of individual MB input and output neurons we elucidated the logic of punishment and reward encoding by the ensemble of dopaminergic MB input neurons and the logic by which the MB interacts with pathways for innate responses to olfactory stimuli in the larva brain, the Lateral Horn (LH). I will discuss key findings from these studies.

This talk is part of the Isaac Newton Institute Seminar Series series.

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