P1: Sources and Mechanisms of Sequential Activity

P1：顺序活动的来源和机制

• 批准号: 10705963
• 负责人: DAVID W TANK
• 金额: $ 33.43万
• 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/10705963
• 关键词: Anatomy; Appearance; Architecture; Area; BRAIN initiative; Behavior; Brain; Brain region; Code; Corpus striatum structure; Cues; Data; Data Science; Decision Making; Dorsal; Electron Microscopy; Etiology; Excision; Exhibits; Foundations; Generations; Geometry; Hippocampus; Lateral; Level of Evidence; Location; Medial; Modeling; Mus; Neocortex; Neuroanatomy; Neurons; Optics; Photic Stimulation; Population; Positioning Attribute; Property; Ramp; Recurrence; Resolution; Role; Short-Term Memory; Source; Structure; Testing; Time; Work; entorhinal cortex; experimental study; model building; neocortical; network architecture; network models; neural; neural circuit; neural model; neural network architecture; neuroimaging; neuromechanism; response; scaffold; virtual

Project Summary/Abstract: Project 1, Sources and Mechanisms of Sequential Activity Sequential activity is widespread and predominant across the mouse brain during an evidence-accumulation decision task and in other tasks as well. Such activity may form a “temporal scaffold,” on top of which other variables are encoded in the amplitude of these sequentially active responses. This activity, different from the ramps and persistent activity often studied in perceptual decisions, could be driven by navigation. The first aim will be to test this idea by identifying conditions that produce sequential representations, such as the task’s timing structure, navigation through spatial locations, or visual stimulation. To distinguish these possibilities, we will record neural activity from regions containing sequential activity during tasks that isolate these key features: active navigation, passive navigation, and visual stimulation. This work will establish whether removal of task features eliminates sequential activity, producing ramps or persistence. The second aim will be to use focal cooling to test a potential role of the striatum as a master temporal scaffold. Medium spiny neurons of dorsal medial striatum (DMS) show sequential activity. Inactivation of this region in the cue period has large effects on choice, yet few DMS sequences are choice-specific in this period. We propose instead that DMS generates a temporal scaffold that controls the timing of choice and evidence-encoding sequences in neocortex and hippocampus. To test this hypothesis, we will use focal cooling to slow striatal neural dynamics, while recording in neocortex and hippocampus. These results will constrain models of sequence generation and reveal the mechanistic foundations of sequential neural activity. The third aim will be to identify network architectures that could underlie the observed data, by building models with three architectures that generate choice-selective sequences. In the moving bump attractor model, activity location in a population jointly encodes position and evidence. In the competing-chains model, evidence is encoded in amplitude, while position is encoded in activity location, in two competing sequences. In the position-evidence multiplicative model, evidence is accumulated in classic ramping activity that controls the gain of activity that is sequentially activated with position. These models will make testable experimental predictions to help us distinguish these network architectures. The fourth aim will be to compare ultrastructural anatomical connectivity with neural coding. We will use cellular-resolution imaging of neural activity during behavior, followed by serial-section electron microscopy of the same neurons in the dorsal hippocampus and neocortex, to empirically test network models of sequential activity. Together, the results of this project will identify task features, brain regions, neural architectures, and microscale anatomy underlying the appearance, timing, and function of sequential activity. We expect that the experiments and models in this project 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1，顺序活动的来源和机制 在证据积累期间 决策任务以及其他任务。这种活动可能形成“时间脚手架”，上面是其他 变量在这些顺序有效响应的放大器中编码。这项活动与 经常在感知决策中研究的坡道和持续活动可能是由导航驱动的。第一个目标 将通过识别产生顺序表示的条件来测试这个想法，例如任务的 正时结构，通过空间位置导航或视觉刺激。为了区分这些可能性，我们 将记录在隔离这些键的任务期间包含顺序活性区域的神经元活动 功能：主动导航，被动导航和视觉刺激。这项工作将确定是否删除 任务功能消除了顺序活动，产生坡道或持久性。 第二个目的是使用焦点冷却来测试纹状体作为大师临时性的潜在作用 脚手架。背培养基纹状体（DMS）的中刺神经元显示顺序活性。失活 提示期的区域对选择具有很大的影响，但在此期间，很少有DMS序列是特定于选择的。 相反，我们建议DMS生成一个临时脚手架，该脚手架控制着选择的时机， 新皮层和海马的循证编码序列。为了检验这一假设，我们将使用焦点冷却 在新皮层和海马中记录时，慢慢纹状体神经动力学。这些结果将限制 序列产生的模型并揭示了顺序神经元活性的机械基础。 第三个目的是通过构建可以识别可以观察到的数据的基础的网络架构 具有生成选择选择序列的三个体系结构的模型。在移动的碰撞吸引子模型中， 人口中的活动位置共同编码位置和证据。在竞争链模型中， 证据是在放大器中编码的，而位置则以两个竞争序列在活动位置中编码。 在位置证据乘法模型中，在控制的经典横斜活动中积累了证据 用位置依次激活的活动的增益。这些模型将进行可测试的实验 预测以帮助我们区分这些网络体系结构。 第四个目标是将超微结构解剖连通性与神经编码进行比较。我们将使用 行为过程中神经元活性的细胞分辨率成像，然后是串行部分电子显微镜 背侧海马和新皮层中的相同神经元，以经验测试顺序的网络模型 活动。该项目的结果在一起将确定任务功能，大脑区域，神经体系结构以及 微观解剖结构是顺序活性的外观，时机和功能。我们期望 该项目中的实验和模型将接下来推进大脑计划的三个优先领域： 动作中的大脑，证明因果关系并确定基本原则。