Large-Scale Mapping of Striatal Dynamics during Perceptual Decision Making

感知决策过程中纹状体动力学的大规模绘图

• 批准号: 10544487
• 负责人: Adrian Gopnik Bondy
• 金额: $ 7.87万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10544487
• 关键词: Address; Anatomy; Animal Model; Animals; Anterior; Area; Auditory; Brain; Brain Diseases; Chronic; Cognitive; Communities; Corpus striatum structure; Data; Data Set; Decision Making; Dopamine D2 Receptor; Dorsal; Electrophysiology (science); Event; Human; Impairment; Implant; Knowledge; Linear Models; Maps; Mediating; Methods; Modeling; Nature; Neurons; Neurosciences; Output; Pathway interactions; Performance; Physiologic pulse; Population; Primates; Process; Publishing; Ramp; Rat Transgene; Rattus; Recovery; Reporting; Research; Rewards; Role; Sensory; Silicon; Site; Source; Stimulus; Structure; System; Tail; Techniques; Testing; Time; Work; cell type; clinically relevant; experimental study; implantation; insight; neural model; novel; optogenetics; receptor expression; response; segregation; sound; tool

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.

项目总结/摘要 感知决策过程中纹状体动力学的大规模映射 随着时间的推移，证据的积累是许多类型决策的关键方面， 人类和动物。最近的工作使用光遗传学扰动，支持我的初步数据， 表明纹状体的多个亚区对于需要证据的决策是必要的 积累然而，编码如何在这个大的， 异质结构是未知的。此外，纹状体散布着两种类型的 投射神经元具有不同的解剖目标，其在证据积累中的特定作用 尚未研究。为了限制描述大脑如何进行决策的模型，这些 关键的知识差距需要填补。 具体来说，有必要系统地记录纹状体亚区和亚型， 一个证据积累的范例，一个直到最近才成为可能的任务。 克服了过去的技术障碍，我将同时记录数百个神经元， 整个纹状体，沿着周围的输入和输出结构，通过部署一个系统，我们最近 专为自由移动的多个高产硅（“神经像素”）探针的长期植入而开发 大鼠这种记录将在一组9个密集平铺纹状体的靶部位进行。大鼠 将执行一项先前确定的任务，非常适合定量分析，要求他们 积累听觉证据的随机定时脉冲（“泊松点击”任务）。在其中的一个子集中， 靶位点，将在转基因大鼠中使用光遗传学标记来鉴定记录的投射神经元 根据其亚型（D1或D2多巴胺受体表达）。 这些数据将是一组详细功能图的基础，这些功能图描述了 特定任务变量（瞬时和累积的证据、选择、奖励等）分布 穿过纹状体亚区并通过主要的纹状体输出通路。我将使用一个广义的 线性建模（GLM）框架，明确利用了任务的脉动性质， 解开和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强大的新测试， 对纹状体通路的独特功能施加了重要的限制。 初步数据已经产生了一个新的发现：证据积累的层次 在背侧纹状体的时间尺度，与前区整合的证据，为决定一个相对 长时间尺度和代表瞬时刺激的后部区域。这一发现说明了 该提案将抓住机会，将多种强大技术结合在一起， 关于纹状体子回路在决策中的作用的见解。