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

基本信息

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
项目类别：
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&apos 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

项目摘要

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.

项目摘要/摘要：总体该 U19 项目的总体目标是确定跨大脑区域的神经计算如何产生两个核心认知过程：工作记忆和决策，从而得出基本的认知过程这个更新的应用程序建议追求强大的新主题。为了实现这一目标，八位 PI 计划紧密整合。一组小鼠进行堆积塔任务的实验和计算研究，其中它们必须记住当他们在虚拟现实中跑过迷宫时，每侧有多少塔闪烁，以及相关任务。第一个主题源于这样的发现：大脑中的神经元编码任务变量并且是几乎所有这些区域都表现出顺序活动，其中神经元处于活动状态。在任务中的不同时间处于活动状态，并且一起平铺试验持续时间项目 1 将确定任务特征。驱动顺序活动，使用冷却来识别产生顺序活动的神经回路，以及通过结合透射电子显微镜和计算模型来阐明其解剖学基础。第二个主题是流形推理方法，应用于大规模海马记录我们的任务是揭示外部变量（位置）和内部变量的联合神经表示的几何形状，认知变量（积累的证据）项目 2 将扩展我们在神经几何方面的工作。我们将研究这些区域的几何形状和表征。彼此相互作用，我们将开发模型来解释观察到的神经流形是如何产生的。第三个主题是由我们开发推断内部大脑状态的统计方法推动的我们的数据显示，在同一任务块中，动物的大脑在不同的试验中处于不同的状态。表明每种状态下的行为都需要不同的神经结构和回路——在同一动物和项目 3 将使用多区域记录和扰动来调查状态是否相同。是局部的子电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，并检查我们推断的状态与觉醒、口渴和饥饿的内部状态之间的关联程度。阐明执行本地计算的多个电路如何组合成一个正在运行的大脑是项目 4 和 5 的目标。项目 4 将探讨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皮质下区域如何与新皮质相互作用的两种假设。项目 5 将生成一组机械模型，实例化特定的捕获角色这些局部模型将被组合成一个单一的多区域模型，由来自所有项目的数据，这将使我们能够剖析各个区域的作用及其在我们决策任务的许多变体的表现。