Cortical circuit mechanisms of sensorimotor object localization

项目总结 感觉和运动信号如何在大脑中整合以产生对物体位置的感知仍是个未知数 人们对此知之甚少。初级躯体感觉皮层(S1)是感觉运动整合的候选部位 是对象定位的基础。鼠标S1是一个强大的系统，可以在其中揭示一般原理和 形成物体位置感知的感应器电机集成的具体电路实现。启示性 这些将提供健康的皮质功能的基本知识，处理中断来自 中风、脊椎损伤和其他神经疾病可能会得到更充分的了解。 这项工作的长期目标是了解触觉背后的细胞和电路机制 感知力。本提案关注的是S1如何在主动触摸过程中整合感觉和运动信号 行为。头固定鼠标可以通过单只主动探索来确定物体的角位置 胡须。复杂的神经处理是这种简单行为的基础，这使它成为一个极好的模型 体感统合回路机制剖析系统。存在几种相互竞争的模型 大脑是如何解决这个问题的。它们在感觉运动信号的类型、来源和整合位置上有所不同 使用。区分这些模型对于理解内部运动信号在 大脑皮层回路在构建触觉知觉中起作用。先前的研究未能做到这一点，因为 任务设计和行为变异的量化。该提案通过以下方式克服了这些限制 创新的方法，包括改进的定位任务，高速感应器运动跟踪，细胞类型- 独特的电生理学、钙成像、复杂的解码模型和闭环光遗传学。 该提案的总体目标是通过以下方式区分不同的感应器运动集成模型 量化行为，确定S1中对象位置的候选代码，这些代码是如何构建的，以及它们的 对感知的影响。我们的中心假设是，物体位置是由兴奋性的集合编码的 S1L5B的神经元被触摸激活，L5B细胞中的目标位置调节需要丘脑 从S1的L4输入和运动减去的触摸信号。我们进一步假设M1的输入放大了L5B 活动而不影响对象位置调整。我们的初步数据支持这一假设，包括 S1中的细胞类型和层特定记录以及物体定位过程中的光遗传电路操作。这个 假说将通过追求三个具体目标来检验。1)识别S1中目标位置的候选代码 神经元。2)确定S1神经元中影响目标位置调节的信号的来源。3)测试对象 S1电路的闭环光遗传操作的局部化模型。建议项目的贡献 研究将具有重要意义，因为它将产生关于S1神经动力学的详细知识 触觉的基础，揭示感觉运动整合的一般原理和特定的大脑皮层回路 在行为过程中实现这种集成，并将其打包到一个公共可访问的资源中。

PROJECT SUMMARY How sensory and motor signals are integrated in the brain to produce perception of object location remains poorly understood. Primary somatosensory cortex (S1) is a candidate site for sensorimotor integration that underlies object localization. Mouse S1 is a powerful system in which to uncover general principles and specific circuit implementations of sensorimotor integration that shape perception of object location. Revealing these will provide fundamental knowledge of healthy cortex function from which processing disruptions from stroke, spinal injury, and other neurological disorders may be more fully understood. The long-term goal of this work is to understand cellular and circuit mechanisms underlying tactile perception. This proposal focuses on how S1 integrates sensory and motor signals during active touch behaviors. Head-fixed mice can determine the angular position of objects by active exploration with a single whisker. Sophisticated neural processing underlies this simple behavior, which makes it an excellent model system for dissecting circuit mechanisms of somatosensory integration. Several competing models exist for how the brain solves this task. They differ in the type, origin, and integration location of sensorimotor signals used. Distinguishing between these models is critical for understanding the role internal motor signals in cortical circuits play in construction of tactile perception. Prior studies failed to do so because of limitations in task design and quantification of behavioral variation. This proposal overcomes these limitations with innovative approaches that include an improved localization task, high-speed sensorimotor tracking, cell type- specific electrophysiology, calcium imaging, sophisticated decoding models, and closed-loop optogenetics. The overall objective of this proposal is to distinguish between sensorimotor integration models by quantifying behavior, identifying candidate codes for object location in S1, how these are constructed, and their influence on perception. Our central hypothesis is that object location is encoded by the set of excitatory neurons activated by touch in L5B of S1, and that object location tuning in L5B cells requires both thalamic input and motion-subtracted touch signals from L4 of S1. We further hypothesize that M1 input amplifies L5B activity without affecting object location tuning. This hypothesis is supported by our preliminary data including cell-type and layer-specific recordings in S1 and optogenetic circuit manipulation during object localization. The hypothesis will be tested by pursuing three Specific Aims. 1) Identify candidate codes for object location in S1 neurons. 2) Identify the origin of signals contributing to object location tuning in S1 neurons. 3) Test object localization models with closed-loop optogenetic manipulation of S1 circuits. The contribution of the proposed research will be significant because it will generate detailed knowledge about the neural dynamics in S1 that underlie touch perception, uncover general principles of sensorimotor integration and specific cortical circuit implementations of that integration during behavior, and package it all into a publically accessible resource.