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，机械多区域大脑模型 阐明不同大脑区域的具体计算作用以及它们如何协同工作来解决问题 复杂的证据积累和决策问题是我们 U19 项目和 大脑倡议。该项目将利用独特的多区域实验数据集 项目 1-4 构建一组关于多个大脑区域如何协同工作的机械模型 我们基于证据积累的决策任务。 目标 1 重点关注基底神经节的作用，通常与动作的门控或选择相关， 在我们的认知决策任务中。基于项目 4 的实验数据，多区域 相互作用，我们将构建模型，假设两条核心路径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传送到累加器电路 新皮质。反过来，我们将建立模型，说明如何利用新皮质积累的证据来驱动 基底神经节从寻求证据到选择选择性行动的转变。 目标 2 重点关注内嗅皮层和海马体的作用，以及它们与感觉的相互作用 和新皮质的额叶区域，生成动物位置的联合认知图并累积 在我们的项目 2“神经动力学几何和表征”的神经记录中观察到的证据。 该模型将提供一个强有力的理论，以生物学上合理的机制为基础，解释认知如何 地图已形成，并将形成对神经​​元流形结构和因果操作效果的预测 在我们的内嗅、海马和新皮质记录实验中。 目标 3 重点关注小脑的作用及其与新皮质的相互作用 决策过程中的证据积累循环。从经典运动小脑中汲取灵感 实验表明小脑如何介导平滑、协调良好的运动的产生 行动，我们提出了一种新的认知小脑理论，作为稳定嘈杂的神经轨迹以产生 流畅的认知行动。这个目标将由小脑目标告知，并反过来形成对小脑目标的预测 项目4，多区域互动。 目标 4 将目标 1 至 3 的区域模型与进一步的多重互动模型相结合 新皮质区域产生基于证据积累的单一大规模模型 决策。该模型将根据所有项目的数据提供信息，并使我们能够剖析 各个区域及其在执行我们决策任务的许多变体时的相互作用。 总的来说，我们期望这些建模工作能够与其他领域的实验深度结合 四个项目将大幅推进 BRAIN 计划的三个优先领域：大脑在行动、 证明因果关系并确定基本原则。