Large-Scale Mapping of Striatal Dynamics during Perceptual Decision Making

项目摘要/摘要 知觉决策过程中纹状体动力学的大尺度映射 随着时间的推移，证据的积累是许多类型的决策的关键方面 人类和动物。最近利用光遗传微扰所做的工作，得到了我的初步数据支持， 表明纹状体的多个亚区对于需要证据的决定是必要的 积累。然而，在这些或其他子区域之间的编码如何比较， 异质结构是未知的。此外，纹状体还散布着两种类型的 具有不同解剖靶点的投射神经元，其在证据积累中的特定作用 没有被研究过。为了限制描述大脑如何执行决策的模型，这些 关键的知识缺口需要填补。 具体地说，有必要系统地记录#年纹状体亚区和亚型。 证据积累模式，这是一项直到最近才可能完成的任务。 克服过去的技术障碍，我将同时记录跨越 整个纹状体，以及周围的输入和输出结构，通过部署我们最近 用于在自由运动中慢性植入多个高产额硅(“神经像素”)探头 老鼠。这样的记录将在纹状体密集铺设的九个目标地点进行。老鼠 将执行一项先前确定的任务，高度服从定量分析，要求他们 积累随机定时的听觉证据脉冲(“泊松点击”任务)。在这些元素的子集中 靶点，光遗传标记将在转基因大鼠中用于识别记录的投射神经元 根据它们的亚型(D1或D2多巴胺受体表达)。 这些数据将成为一组详细功能图的基础，这些功能图描述了 具体的任务变量(即时和累积的证据、选择、奖励等)是分布式的 并通过主要的纹状体输出通路。我将使用泛化的 线性建模(GLM)框架，它明确地利用任务的脉动性，以 解开并量化这些外部协变量对神经元放电率的影响。这些数据 将为证据积累的神经基础的电路模型提供一个强有力的新测试，以及 对纹状体通路的不同功能施加重要限制。 初步数据已经产生了一个新的发现：证据积累的等级 背侧纹状体的时间尺度，与前区整合的证据决定了相对 表示瞬时刺激的长时间刻度和后方区域。这一发现说明了 该提案将抓住机会，将多种强大的技术结合在一起，产生新的 关于纹状体亚回路在决策中的作用的见解。

Project Summary/Abstract Large-Scale Mapping of Striatal Dynamics during Perceptual Decision Making The accumulation of evidence over time is a critical aspect of many types of decision making in humans and animals. Recent work using optogenetic perturbation, supported by my preliminary data, shows that multiple subregions of the striatum are necessary for decisions requiring evidence accumulation. However, how encoding compares across these or other subregions of this large, heterogeneous structure is unknown. Furthermore, the striatum is interspersed with two types of projection neurons with distinct anatomical targets, whose specific role in evidence accumulation has not been studied. To constrain models describing how the brain carries out decision making, these critical knowledge gaps need to be filled. Specifically, it will be necessary to record systematically across striatal subregions and subtypes in an evidence accumulation paradigm, a task which has not been possible until very recently. Overcoming past technical hurdles, I will simultaneously record from hundreds of neurons spanning the entire striatum, along with surrounding input and output structures, by deploying a system we recently developed for chronic implantation of multiple, high-yield silicon (“Neuropixels”) probes in freely moving rats. Such recordings will be carried out at a set of nine targets sites densely tiling the striatum. Rats will perform a previously established task, highly amenable to quantitative analysis, requiring them to accumulate randomly timed pulses of auditory evidence (the “Poisson Clicks” task). In a subset of these target sites, optogenetic tagging will be used in transgenic rats to identify recorded projection neurons based on their subtype (D1 or D2 dopamine receptor expression). These data will be the basis for a set of detailed functional maps describing how encoding for specific task variables (instantaneous and accumulated evidence, choice, reward, etc.) is distributed across striatal subregions and routed through the major striatal output pathways. I will use a generalized linear modeling (GLM) framework, that explicitly takes advantage of the pulsatile nature of the task, to disentangle and quantify the influence of these external covariates on neuronal firing rates. These data will provide a powerful new test for circuit models of the neural basis of evidence accumulation, and place important constraints on the distinct function of striatal pathways. Preliminary data has already yielded a novel finding: a hierarchy of evidence accumulation timescales in the dorsal striatum, with anterior areas integrating evidence for a decision over a relatively long timescale and posterior areas representing the instantaneous stimulus. This finding illustrates how the proposal will seize an opportunity to bring together multiple powerful techniques to yield new insights about the role of striatal subcircuits in decision making.