P5: Mechanistic Multi-Region Brain Models

P5：机械多区域大脑模型

• 批准号: 10705967
• 负责人: MARK S GOLDMAN
• 金额: $ 76.7万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-08 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705967
• 关键词: Animals; Area; BRAIN initiative; Basal Ganglia; Behavior; Brain; Brain region; Breathing; Cerebellum; Cognition; Cognitive; Complex; Computer Models; Control Animal; Corpus striatum structure; Coupled; Cues; Data; Data Analyses; Data Set; Decision Making; Etiology; Experimental Models; Foundations; Geometry; Goals; Hippocampus; Individual; Joints; Learning; Machine Learning; Maps; Mediating; Memory; Modeling; Motion; Motor; Neocortex; Neurons; Neurophysiology - biologic function; Pathway interactions; Performance; Positioning Attribute; Prefrontal Cortex; Production; Role; Sensory; Short-Term Memory; Side; Signal Transduction; Structure; System; Task Performances; Training; Variant; Work; entorhinal cortex; evidence base; experience; experimental study; model building; motor control; neocortical; network models; neural; neural circuit; neuromechanism; optogenetics; programs; scaffold; sensory input; sequence learning; sound; success; theories

Project Summary/Abstract: Project 5, Mechanistic Multi-Region Brain Models Elucidating the specific computational roles of different brain areas and how they work together to solve complex evidence-accumulation and decision-making problems is a key goal of our U19 program and of the BRAIN initiative. This project will take advantage of the unique multi-region experimental datasets from Projects 1-4 to construct a set of mechanistic models of how multiple brain regions work together to perform our accumulation-of-evidence based decision-making task. Aim 1 focuses on the role of the basal ganglia, often associated with the gating or selection of actions, within our cognitive decision-making task. Building on the experimental data in Project 4, Multi-Region Interactions, we will construct models hypothesizing how the two core pathways traversing the basal ganglia, the direct and indirect pathways, may serve to gate evidence or position information to accumulator circuits in the neocortex. In turn, we will build models of how accumulated evidence from the neocortex is used to drive the transition from evidence-seeking to choice-selective actions in the basal ganglia. Aim 2 focuses on the role of the entorhinal cortex and hippocampus, and their interactions with sensory and frontal regions of neocortex, in generating the joint cognitive map of animal position and accumulated evidence observed in our neural recordings of Project 2, Geometry of Neural Dynamics and Representations. The model will provide a powerful theory, grounded in biologically plausible mechanisms, for how cognitive maps are formed and will form predictions for neuronal manifold structures and effects of causal manipulations in our entorhinal, hippocampal, and neocortical recording experiments. Aim 3 focuses on the role of the cerebellum, and its interactions with neocortical accumulation-of-evidence circuits, in decision-making. Drawing inspiration from classic motor cerebellar experiments suggesting how the cerebellum may mediate the production of smooth, well-coordinated motor actions, we propose a new theory of the cognitive cerebellum as stabilizing noisy neural trajectories to produce smooth cognitive actions. This Aim will be informed by, and in turn form predictions for, the Cerebellar aim of Project 4, Multi-Region Interactions. Aim 4 will combine the regional models of Aims 1 to 3 with a further model of multiple interacting neocortical regions to produce a single, large scale model of accumulation-of-evidenced based decision-making. The model will be informed by data from all projects and will enable us to dissect the roles of individual regions and their interactions in the performance of the many variants of our decision-making task. Taken together, we expect that these modeling efforts, deeply integrated with experiments in the other four Projects, will substantially advance three priority areas of the BRAIN Initiative: the brain in action, demonstrating causality, and identifying fundamental principles.

项目摘要/摘要：项目5，机械多区域脑模型 阐明不同大脑区域的特定计算角色以及它们如何协同工作来解决 复杂的证据积累和决策问题是我们U19项目和 大脑的主动性。该项目将利用独特的多区域实验数据集 项目1-4构建一套机制模型，说明多个大脑区域如何协同工作来执行 我们的基于证据积累的决策任务。 目标1侧重于基底节的作用，通常与选通或选择动作有关， 在我们的认知决策任务中。以项目4多区域实验数据为基础 相互作用，我们将构建模型，假设两条核心通路如何穿越基底节， 直接和间接路径可以用来将证据或位置信息选通到 大脑皮层。反过来，我们将建立模型，说明从大脑皮层积累的证据是如何用于驱动 在基底节，从寻找证据到选择行为的转变。 目的2重点研究内嗅皮层和海马体的作用以及它们与感觉的相互作用 和额叶区的新皮质，在产生动物位置的联合认知地图并积累 在我们的项目2的神经记录中观察到的证据，神经动力学的几何和表示。 该模型将提供一个强大的理论，基于生物学上看似合理的机制，来解释认知 映射被形成，并将形成对神经元流形结构和因果操作的影响的预测 在我们的内嗅觉、海马体和新皮质的记录实验中。 目标3侧重于小脑的作用及其与新皮质的相互作用 决策中的证据积累循环。从经典运动小脑中汲取灵感 表明小脑如何调节平滑、协调良好的运动的产生的实验 行动，我们提出了一种新的理论，即认知小脑作为稳定噪声的神经轨迹产生 流畅的认知动作。这一目标将由小脑目标提供信息，并反过来从预测中得出 项目4，多区域互动。 目标4将把目标1至3的区域模式与进一步的多重互动模式结合起来 新皮质区域产生一个单一的、大规模的证据积累模型 决策。该模型将由所有项目的数据提供信息，并将使我们能够剖析 各个区域及其相互作用在执行我们的决策任务的许多变体中。 综上所述，我们希望这些建模工作与另一方的实验深度结合 四个项目，将大大推进大脑倡议的三个优先领域：大脑在行动， 论证因果关系，并确定基本原则。