Simultaneous and Bidirectional Chemogenetic Control of Mesolimbic and Nigrostriatal Circuits

Duke University, Durham NC

Investigators

Abstract

ABSTRACT Most mental disorders have strong underlying genetic component, with many disease-associated variants occurring in genes involved in neuronal development and synaptic transmission. This suggests that deficits in cellular mechanisms may ultimately alter brain-circuit connectivity to yield dysfunctions in specific behavioral domains. Consistent with the RDoC framework, several independent circuit deficits likely synergize to create a distinct emergent state in large-scale networks ultimately yielding mental disorders. While multiple rodent models have begun to link circuit function with behavior, modeling these complex network-level alterations has been largely intractable with current optogenetic and chemogenetic tools that only target individual circuit elements of complex networks. This proposal presents a solution to this problem by developing and validating a new tool to simultaneously and bidirectionally control distinct brain circuits via chemogenetics. We then apply these reagents to two dopamine (DA) circuits in the brain, the nigrostriatal and mesocorticolimbic circuits. The resulting model will be characterized behaviorally and with state-of-the-art electrophysiological techniques to measure the functional consequences of concurrent bidirectional modulation of DA circuity. In Aim 1, we present the design and validation experiments necessary to generate and verify the correct function of these reagents. In Aim 2, we will use these reagents to associate DA circuit functional status with specific behavioral domain dysfunctions through the use of electrophysiological ensemble recordings during behavioral tasks. After completing these aims, we will have established proof-of-concept that a mouse model can recapitulate distinct and simultaneous modifications in two brain circuits that can be used to identify synergistic or antagonistic interactions between these brain circuits at the network level.