Mechanisms of neural circuit dynamics in working memory and decision-making

工作记忆和决策中的神经回路动力学机制

• 批准号: 10705962
• 负责人: Carlos D Brody
• 金额: $ 468.67万
• 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/10705962
• 关键词: Address; Alzheimer' s Disease; Anatomy; Animals; Architecture; Area; Arousal; Attention deficit hyperactivity disorder; BRAIN initiative; Basic Science; Behavior; Behavioral; Behavioral Paradigm; Biological Assay; Bipolar Depression; Brain; Brain region; Cognitive; Computer Models; Data; Decision Making; Dementia; Development; Electron Microscopy; Electrophysiology (science); Etiology; Exhibits; Family; Geometry; Goals; Hippocampus; Hunger; Image; Individual; Joints; Link; Maps; Mental disorders; Methods; Modeling; Modernization; Mus; Neocortex; Neurons; Neurosciences; Performance; Physiological; Positioning Attribute; Research; Research Personnel; Resolution; Rodent; Role; Running; Schizophrenia; Series; Short-Term Memory; Side; Silicon; Statistical Methods; Structure; System; Task Performances; Technology; Testing; Therapeutic; Thirst; Time; Transmission Electron Microscopy; Variant; Work; autism spectrum disorder; cognitive ability; cognitive process; computer studies; experimental study; member; neocortical; neural; neural circuit; neuromechanism; next generation; novel; operation; population based; programs; scaffold; virtual reality

Project Summary/Abstract: Overall The overarching goal of this U19 program is to determine how neural computations across brain regions produce two core cognitive processes, working memory and decision-making, and thus to derive fundamental principles of brain function. This renewal application proposes to pursue powerful new themes that emerged from our previous work and to broaden our scope substantially. To do so, the eight PIs plan a tightly integrated set of experimental and computational studies of mice doing the accumulating towers task—in which they must remember how many towers flash on each side as they run down a maze in virtual reality—and related tasks. The first theme arises from the finding that neurons across the brain encode task variables and are necessary for task performance. Almost all of these areas exhibit sequential activity, in which neurons are active at different times in the task and, together, tile the trial duration. Project 1 will identify the task features that drive sequential activity, use cooling to identify neural circuits that generate sequential activity, and elucidate its anatomical basis by combining transmission electron microscopy and computational modeling. A second theme is that manifold inference methods, applied to large-scale hippocampal recordings in our task, reveal the geometry of a joint neural representation for an external variable (position) and an internal, cognitive variable (accumulated evidence). Project 2 will extend our work on the geometry of neural representations to other brain regions. We will examine how geometries and representations in these regions interact with each other, and we will develop models to explain how the observed neural manifolds arise. A third theme, fueled by our development of statistical methods to infer internal brain states, is that animals’ brains occupy qualitatively different states from trial to trial during the same task block. Our data suggests that behavior in each state requires different neural structures and circuits—in the same animal and the same trial block. Project 3 will use multi-region recordings and perturbations to investigate whether states are local to subcircuits versus global across the brain, extend our behavioral inference methods to neural data, and examine to what extent our inferred states are linked to internal states of arousal, thirst, and hunger. Elucidating how multiple circuits performing local computations combine into a brain in action is the goal of Projects 4 and 5. Project 4 will probe functional interactions in multi-region recordings, including very large-scale simultaneous electrophysiological recordings with next-generation silicon probes; and through targeted experiments will test two hypotheses of how subcortical regions interact with neocortex. Project 5 will generate a set of mechanistic models that instantiate specific hypothesized roles of different brain regions. These local models will be combined into a single multi-regional model, informed by data from all projects, that will enable us to dissect the roles of individual regions and their interactions in performance of the many variants of our decision-making task.

项目概要/摘要：总体 这个U19项目的首要目标是确定跨大脑区域的神经计算是如何进行的。 产生两个核心的认知过程，工作记忆和决策，从而得出基本的 大脑功能的原则。这个更新的应用程序提出了追求强大的新的主题，出现 从我们以前的工作，并大大扩大我们的范围。为此，八个PI计划一个紧密集成的 一组实验和计算研究的小鼠做积累塔的任务，其中他们必须 还记得在虚拟现实中，当他们沿着迷宫奔跑时，两边有多少座塔在闪烁，以及相关的任务。 第一个主题源于大脑中的神经元对任务变量进行编码， 执行任务所必需的。几乎所有这些区域都表现出连续的活动，其中神经元是 在任务的不同时间激活，并一起平铺试验持续时间。项目1将确定任务特征 驱动连续活动，使用冷却来识别产生连续活动的神经回路， 通过结合透射电子显微镜和计算建模来阐明其解剖学基础。 第二个主题是，多种推理方法，适用于大规模海马记录， 我们的任务，揭示了一个外部变量（位置）和一个内部， 认知变量（累积证据）。项目2将扩展我们在神经网络几何学方面的工作， 其他脑区的表征。我们将研究如何几何和表示在这些地区 相互作用，我们将开发模型来解释观察到的神经流形是如何产生的。 第三个主题是，我们发展了统计方法来推断大脑内部状态， 动物的大脑在同一个任务块中从一次试验到另一次试验占据了性质上不同的状态。我们的数据 这表明，每种状态下的行为需要不同的神经结构和回路-在同一动物中， 同样的试验区。项目3将使用多区域记录和扰动来调查状态是否 是局部的子回路，而不是整个大脑的全局，将我们的行为推理方法扩展到神经数据， 并检查我们的推断状态在多大程度上与唤醒，口渴和饥饿的内部状态相关联。 阐明了执行本地计算的多个电路如何联合收割机组合成一个行动中的大脑， 项目4和项目5的目标。项目4将探索多区域记录中的功能相互作用，包括非常 使用下一代硅探针进行大规模同步电生理记录; 有针对性的实验将测试两个假设，皮质下区域如何与新皮质相互作用。 项目5将生成一组机械模型， 不同的大脑区域。这些地方模型将合并为一个单一的多区域模型， 所有项目的数据，这将使我们能够剖析各个地区的作用及其相互作用， 我们的决策任务的许多变体的性能。