Learning in neural circuits: applied optogenetics in non-genetic models

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DESCRIPTION (provided by applicant): While great advances have been made in understanding the mechanisms of learning in the single synapse or cell, a large gap remains between this understanding and our knowledge of learning at the behavioral level. We know that the activity of large-scale neuronal circuits gives rise to behavior, yet we have little knowledge of what changes in those circuits during learning or how sensory feedback drives these changes. The biggest impediment to answering these questions is the inability to quantitatively measure large-scale circuit properties (e.g. connectivity between brain areas) or to precisely manipulate the activity patterns across these circuits. Optogenetics offers the potential to bridge this gap by allowing the direct control of neural activation in targeted cell types on the millisecond timescale. The development of these tools is progressing most rapidly in mouse, due to the relative ease of genetic manipulations in that species. In contrast, behavioral and circuit-level studies of learning are most practical and have been most successful in "non-genetic" species. Within our team, we have expertise in studying both the behavioral and neural bases of learning in rat, songbird, and nonhuman primate. We propose to develop the optogenetic tools and experimental techniques required to study the circuit-level mechanisms of learning in these species and to apply these to two specific scientific aims: Aim 1: Determine the functional connectivity of learning-related circuitry and how it is altered by experience. It is widely presumed that learning relies on the ability of instructive signals to drive functional modifications of connectivity in the circuits that underlie behavior. However, the tools for measuring functional connectivity in vivo have been limited. We will overcome this limitation using temporally and/or spatially precise optical activation of neurons within a circuit. Functional connectivity will be measured by recording optical-stimulation-triggered changes in activity in downstream neurons. We will assess how functional connectivity is dynamically altered by learning and by factors that may contribute crucially to learning. Connectivity changes will serve as a mechanistic index of the nature and sites of the plasticity that give rise to behavioral change. Aim 2: Test the causal contributions of patterned activity to learning in vivo. Prior research has generated specific and testable hypotheses about how and where patterned activity drives learning. Yet support for these hypotheses has derived primarily from correlative observations of activity during learning rather than causal tests of the proposed mechanisms. We will use optogenetics to causally test the contributions of patterned activity to learning. We will test the sufficiency of instructive signals by imposing precisely controlled patterns of activity at defined loci in a circuit and test their necessity by eliminating the putative signals for learning. PROJECT NARRATIVE This project is aimed at revolutionizing the study of the mechanisms of learning within large neural circuits in the brain by directly measuring large-scale properties of these circuits and precisely manipulating circuit activity. To accomplish this, we will make use of, and continue to develop, advanced new techniques that permit the control of specific population of neurons using optical stimulation (light). The knowledge and tools that we gain from these studies are likely to find broad application in the search for treatments of neurological disorders.