The Role of the Midbrain Reticular Nucleus in Vision and Perceptual Decision-Making

中脑网状核在视觉和知觉决策中的作用

• 批准号: 10676026
• 负责人: Jordan Robert Shaker
• 金额: $ 4.36万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10676026
• 关键词: Address; Alzheimer' s Disease; Area; Basal Ganglia; Behavioral; Brain; Brain region; Cell Nucleus; Code; Cognitive; Complex; Computer Analysis; Cues; Decision Making; Disease; Electrophysiology (science); Environment; Goals; Histologic; Human; Image; Impairment; Institution; Learning; Maps; Medical; Mental disorders; Mentors; Midbrain structure; Modeling; Modernization; Morbidity - disease rate; Motor; Movement; Mus; Pathway interactions; Physicians; Process; Prosencephalon; Rodent; Role; Scheme; Schizophrenia; Scientist; Sensory; Signal Transduction; Stimulus; Task Performances; Techniques; Training; Vision; Visual; Work; career; clinical training; design; improved; nervous system disorder; neuropsychiatric disorder; novel; response; skills; superior colliculus Corpora quadrigemina; vaping; visual map; visual plasticity; visual processing

Project Summary: Impairments in visual processing and perceptual decision-making are a significant cause of morbidity in neuropsychiatric disorders such as Alzheimer’s disease and schizophrenia. The primary goal of this training proposal is to characterize a potentially novel node in the distributed network underlying visual perceptual decision-making - the midbrain reticular nucleus (MRN). Classical models of perceptual decision-making ascribe decision formation to forebrain sensorimotor regions, with the midbrain existing at the end of a feedforward pathway to relay motor commands. However, there is substantial evidence that the midbrain, especially the superior colliculus (SC), participates in the visual decision process. Additionally, our recent work has shown that a variety of coding, from movements, to action selection, to even abstract cognitive representations such as cue valuation, is simultaneously distributed in multiple regions throughout the brain. We hypothesize that this coding scheme applies to visual decisions as well, with midbrain regions including MRN and SC participating in a network with regions in the cortex and basal ganglia to form the decision. The MRN has traditionally been thought of as a purely motor-related region. Challenging this notion, we recently found visual and action selection signals in MRN during a visual decision-making task. Questions remain however regarding how the diverse coding in MRN is organized topographically, whether visual responses are a result of task learning, the encoding of abstract decision signals in MRN, and how MRN interacts with the broader perceptual decision-making circuitry. This training proposal addresses each of these questions by leveraging the scale of Neuropixels 2.0 probes and a novel visual reverse contingency task I have designed and implemented to distinguish sensory, motor, and decision signals. Aim 1A uses Neuropixels 2.0 recordings across MRN in mice viewing a variety of stimuli to build a topographic map of sensory and motor coding, and Aim 1B uses similar recordings in task-naive and trained mice passively perceiving task stimuli to assess visual plasticity in MRN. Aim 2A uses recordings across MRN during task performance to establish the presence of abstract decision signals, and Aim 2B uses multi-probe recordings throughout the visual decision network to establish inter-area interactions during decision formation. Together these aims will advance our understanding of the distributed regions and the complex computations that give rise to visual decision-making, thereby improving our ability to precisely target key circuits in disorders where this process goes awry. During my tailored training period, I will learn Neuropixels electrophysiology, rodent behavioral task design and implementation, whole-brain histological processing and imaging, and advanced computational analysis techniques under the guidance of experts in a supportive training environment. These skills, combined with clinical training in a world-leading medical institution, will ideally prepare me for an independent career as a physician-scientist working to advance the understanding and treatment of neurological disorders.

项目概述：视觉处理和感知决策的损伤是导致 神经精神疾病如阿尔茨海默病和精神分裂症的发病率。其主要目标是 训练建议是表征分布式网络中潜在的新颖节点， 中脑网状核（MRN）。知觉决策的经典模型归因于 决定形成到前脑感觉运动区，中脑存在于前馈的末端 传递运动指令的路径然而，有大量证据表明，中脑，特别是 上级丘（SC）参与视觉决策过程。此外，我们最近的工作表明， 各种各样的编码，从动作到动作选择，甚至抽象的认知表征，如提示， 评估，同时分布在整个大脑的多个区域。我们假设这种编码 该方案也适用于视觉决策，包括MRN和SC在内的中脑区域参与了视觉决策。 与大脑皮层和基底神经节的区域形成网络以形成决策。 MRN传统上被认为是一个纯粹与运动相关的区域。根据这一概念，我们 最近发现视觉和动作选择信号在MRN在视觉决策任务。问题仍然 然而，关于MRN中的不同编码如何在地形上组织，视觉反应是否 任务学习的结果，MRN中抽象决策信号的编码，以及MRN如何与 更广泛的感知决策电路。本培训建议通过以下方式解决上述每个问题： 利用Neuropixels 2.0探针的规模和我设计的一种新颖的视觉反向应急任务， 被实施以区分感觉、运动和决策信号。Aim 1A使用Neuropixels 2.0记录 在小鼠的MRN中观察各种刺激，以建立感觉和运动编码的地形图， Aim 1B使用类似的记录在任务幼稚和训练的小鼠被动感知任务刺激，以评估视觉 MRN的可塑性。目标2A在任务执行期间使用MRN的记录来确定 抽象决策信号，Aim 2B在整个视觉决策网络中使用多探头记录， 在决策形成过程中建立区域间的相互作用。这些目标将共同促进我们的理解 分布式区域和复杂的计算，从而产生视觉决策， 提高我们的能力，以精确的目标关键电路在混乱的地方，这一过程出错。 在量身定制的培训期间，我将学习Neuropixels电生理学，啮齿动物行为任务 设计和实施，全脑组织学处理和成像，以及先进的计算 在支持性培训环境中，在专家指导下学习分析技术。这些技能结合起来 在世界领先的医疗机构接受临床培训，将为我作为一名独立的职业生涯做好理想的准备。 致力于促进对神经系统疾病的理解和治疗的医生科学家。