Reverse Engineering the Brain Stem Circuits that Govern Exploratory Behavior

点击翻译按钮获取中文摘要

Overview - Abstract Brainstem function is necessary for life-sustaining functions such as breathing and for survival functions, such as foraging for food. Individual motor actions are activated by specific brainstem cranial motor nuclei. The specificity of individual motor actions reflects the participation of motor nuclei in circuits within closed loops between sensors and muscle actuators. However, these loops are also nested and connect to feedback and feedforward pathways, which underlie coordination between orofacial motor actions. A key question for this proposal is how different actions are coordinated to form a rich repertoire of behaviors, such as rhythmic motions linked to breathing, and the orchestrated displacements of the head, nose, tongue, and vibrissae during exploration. We postulate that the best candidate interface for orofacial motor coordination are premotor and pre2motor neuron populations in the brainstem reticular formation: these neurons project to cranial motor nuclei, receive descending inputs from outside of the brainstem, and interconnected to each other. Our approach exploits and expands upon a broad spectrum of innovative experimental tools. These include state-of-the-art behavioral methods to study motor actions and their coordination into behaviors. From an experimental perspective, the underlying neuronal circuitry for each orofacial motor action may be accessed via transsynaptic transport starting at the muscle activators or associated sensors in the periphery. These studies will make use of molecular, genetic, and functional labeling methods to enable cell phenotyping and circuit tracing. These data will establish the "Components", i.e., brainstem nuclei connectivity for all Research Projects. These studies are complemented by in vivo electrophysiology and optogenetics in order measure and perturb the signal flow during exploration and decision-making: these studies will establish orofacial “Wiring Diagrams”. The sum of these techniques will permit us to elucidate the functions of intrinsic brainstem circuits and their modulation by descending pathways. Our data will be integrated in two ways. First we will begin development of computational models of the dynamics of active sensing by the orofacial motor plant and brainstem circuits. These will initially focus on the vibrissa system, starting with characterizations of mechanics and mechano-neuronal transformations of vibrissa movement and extending to exploration of brainstem circuits that drive vibrissa set-point and rhythmic whisking. Finally, vibrissa feedforward pathways will be computationally modeled to explore how sensory input affects vibrissa dynamics. Second, to record connectivity data that arises from our experimental tracing studies, we will construct an Trainable Texture-based Digital Atlas that utilizes machine learning to automate anatomical annotation of brainstem nuclei. The Atlas is designed to allow accurate 3D alignment of labeled neurons, even when labeled neurons reside in small sub-regions outside of well-defined brainstem nuclei, based on triangulation to Atlas landmark structures. Further, digitization of serially sectioned brain data sets allows 3D reconstruction and alignment of small brainstem subregions as well as the collation of this data from different brains into the same Atlas. Our proposed program on brainstem circuitry and dynamics will yield general lessons about the nature of neuronal computation. The analytic and anatomical tools developed for these studies will be made available through our data science core to the larger neuroscience community.