Abstract
Understanding the complex neural circuits that underpin brain function and behavior has been a long-standing goal of neuroscience. Yet this is no small feat considering the interconnectedness of neurons and other cell types, both within and across brain regions. In this review, we describe recent advances in mouse molecular genetic engineering that can be used to integrate information on brain activity and structure at regional, cellular, and subcellular levels. The convergence of structural inputs can be mapped throughout the brain in a cell type-specific manner by antero- and retrograde viral systems expressing various fluorescent proteins and genetic switches. Furthermore, neural activity can be manipulated using opto- and chemo-genetic tools to interrogate the functional significance of this input convergence. Monitoring neuronal activity is obtained with precise spatiotemporal resolution using genetically encoded sensors for calcium changes and specific neurotransmitters. Combining these genetically engineered mapping tools is a compelling approach for unraveling the structural and functional brain architecture of complex behaviors and malfunctioned states of neurological disorders.
Highlights
Information is processed in the brain by a vast number of diverse neurons that are extensively intermingled and interconnected mainly through synapses
A labeled brain region space (Allen CCF v3 Brain Atlas) facilitates systematic analysis of input/output profiles throughout the whole brain. Taking advantage of these standardized and digitalized platforms, axonal projection datasets from various brain regions can be reconciled to generate a map of convergent circuitry, despite data being obtained through separate experimental performances
This study revealed that the glutamatergic lateral hypothalamic area (LHA)–lateral habenula (LHb) circuit is a critical node in value processing, with further functional assessments using activity actuators and sensors, which we review below
Summary
Information is processed in the brain by a vast number of diverse neurons that are extensively intermingled and interconnected mainly through synapses. The initial step in these connectivity research studies relies on genetic engineering: well-established animal models expressing genetic switches, such as Cre and tetracyclinecontrolled transactivator, for defining and labeling certain populations and types of neurons (Sauer and Henderson, 1988; Gossen and Bujard, 1992; Gong et al, 2007; Gerfen et al, 2013; Harris et al, 2014, 2019; Hooks et al, 2018); viral systems with different features, such as tropism and axonal transduction, in a genetic switch-dependent manner (DeFalco et al, 2001; Wall et al, 2010; Lo and Anderson, 2011; Ährlund-Richter et al, 2019; Lazaridis et al, 2019; Sun et al, 2019; Gong et al, 2020); fluorescent sensors for monitoring neural events, such as intracellular Ca2+ influx and neurotransmitter release in response to neural activity (Lin and Schnitzer, 2016; Sabatini and Tian, 2020); and actuators for manipulating neuronal activity, such as opto- and chemo-genetics (Deisseroth, 2015; Roth, 2016; Atasoy and Sternson, 2018). Beginning with a brief technical account and discussion of the unique significance of these approaches, we discuss recent advances in their applications and combinatorial strategies for exploring structural and functional organization of various circuits
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