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.

项目概要/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共同解决 复杂的证据积累和决策问题是我们的U19计划的一个关键目标， BRAIN倡议。该项目将利用独特的多区域实验数据集， 项目1-4，构建一组多个大脑区域如何协同工作以执行 我们基于证据积累的决策任务。 目标1关注基底神经节的作用，通常与动作的门控或选择有关， 在我们的认知决策任务中。以项目4的实验数据为基础，多区域 相互作用，我们将构建模型，假设两个核心通路如何穿过基底神经节， 直接和间接路径可以用于将证据或位置信息选通到累加器电路， 大脑皮层反过来，我们将建立新皮层积累的证据如何用于驾驶的模型， 基底神经节从循证行为向选择行为的转变。 目的2着重于内嗅皮层和海马的作用，以及它们与感觉神经元的相互作用。 和额叶区的新皮层，在产生联合认知地图的动物的立场和积累 我们在项目2的神经记录中观察到的证据，神经动力学和表征的几何。 该模型将提供一个强有力的理论，基于生物学上合理的机制， 地图形成，并将形成预测的神经元流形结构和因果操纵的影响 在我们的内嗅、海马和新皮层记录实验中。 目标3集中在小脑的作用，以及它与新皮质的相互作用 在决策过程中的证据积累电路。从经典的小脑运动中汲取灵感 实验表明小脑如何介导产生平稳，协调良好的运动 行动，我们提出了一个新的理论，认知小脑稳定嘈杂的神经轨迹，以产生 平滑的认知行为。这个目标将被告知，并反过来形成预测，小脑的目标， 项目4，多区域互动。 目标4将联合收割机目标1至3的区域模式与另一个多重相互作用模式相结合 新皮层区域产生一个单一的，大规模的积累模型的证据的基础上 决策的该模型将由所有项目的数据提供信息，并使我们能够剖析 在执行我们的决策任务的许多变体时，各个区域及其相互作用。 总之，我们希望这些建模工作，与其他领域的实验深度结合， 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， 证明因果关系，并确定基本原则。