Identify the schemata by which subcortical signals influence frontal cortical dynamics and cognitive behaviors

识别皮层下信号影响额叶皮层动态和认知行为的图式

基本信息

批准号：
10546515
负责人：
Karel Svoboda
金额：
$ 63.72万
依托单位：
ALLEN INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-15 至 2026-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10546515
关键词：
Anterior Area Automobile Driving Axon Basal Ganglia Behavior Behavioral Body Weight Changes Brain region Calibration Cell Nucleus Cerebellum Cognition Disorders Cognitive Coma Complex Coupled Data Data Science Core Devices Disease Electrophysiology (science)Future Globus Pallidus Goals Head Hypersomnias Intralaminar Nuclear Group Lateral Left Link Logic Maintenance Maps Measurement Medial Medial Dorsal Nucleus Mediating Medical Memory Methods Midbrain structure Modeling Modernization Molecular Motor Motor Cortex Movement Multivariate Analysis Mus Neurons Pattern Phase Population Prefrontal Cortex Reagent Recurrence Research Project Grants Rewards Role Science Sensory Short-Term Memory Signal Transduction Site Statistical Methods Structure Substantia nigra structure Synapses Testing Thalamic structure Time Update Viral density dynamic system excitatory neuron experience experimental study flexibility frontal lobe motor disorder neural neural circuit neural patterning neurophysiology optogenetics predictive modeling response restraint

项目摘要

Summary, Project 4 (Identify the schemata by which subcortical signals influence frontal cortical dynamics and cognitive behaviors) This research project is focused on dynamic interactions between subcortical areas and frontal cortex via thalamus during flexible behavior. Frontal cortex, including motor cortex and medical prefrontal cortex, displays complex patterns of neural activity that correlate with behavior. These patterns can be decomposed into activity modes (i.e. subspaces in activity space), such as the persistent activity correlated with short-term memory, and the rapidly modulated activity associated with voluntary movements. Complex behaviors correspond to sequences of cortical activity modes. Frontal cortex is tightly coupled with higher-order (non-sensory) thalamus to mediate behavior. Thalamus in turn receives driving input from the basal ganglia the and other subcortical structures. We test the hypothesis that different subcortex inputs to specific thalamic regions control different aspects of cortical activity, including setting the time periods when short-term memories are maintained, the transitions from motor planning to movement execution (Aim 1), and updating and maintaining the values of specific actions during foraging. Our modeling framework (Overall, Project 5) links the dynamical systems perspective of neural computation with actual multi-regional neural circuits and makes predictions that can be tested with neurophysiology. We employ two behavioral tasks in mice that engage well-defined but distinct cortical activity modes. In a memory-guided response task, neurons in the anterior lateral motor cortex (ALM) show preparatory activity, which predicts specific future movements. Just before the onset of movement, preparatory activity collapses in favor of activity modes that drive movement. In a dynamic foraging task, neurons in the medial prefrontal cortex (mPFC) show slowly varying activity patterns that correlate with the value of one action compared to another. This activity is updated based on new information, such as the size of a reward. Projects 1 - 3 provide information about the circuits linking subcortical areas, thalamus, and ALM / mPFC. Building on these circuit mapping experiments we will perform simultaneous recordings from connected subcortex → thalamus → cortex circuits using new multi-shank Neuropixels probes with 5120 recording sites (Project 3). We will combine these recordings with optogenetic manipulations of subcortex and modern multi-variate analysis methods (Data Science Core) to track how subcortical signals propagate through the thalamus into cortex. In the memory-guided response task we will probe the role of the substantia nigra reticulata, acting via the ventromedial nucleus, on maintenance of movement planning, and the impact of midbrain movement centers (e.g. pedunculopontine nucleus), acting via the posterior mediodorsal nucleus, on switching from movement planning to movement initiation (Aim 1). In the foraging task, we will probe how error prediction signals, for example from ventral pallidum (PALv), update memory-related activity in the mPFC via anterior mediodorsal thalamus. These measurements will test key model predictions and in turn inform multi-regional circuit models of cognitive behavior.

摘要，项目 4（确定皮层下信号影响的图式额叶皮层动力学和认知行为）该研究项目的重点是通过皮层下区域和额叶皮层之间的动态相互作用丘脑在灵活行为期间显示额叶皮层，包括运动皮层和医学前额叶皮层。与行为相关的复杂的神经活动模式这些模式可以分解为活动。模式（即活动空间中的子空间），例如与短期记忆相关的持续活动，以及与随意运动相关的快速调节的活动对应于复杂的行为。皮质活动模式序列与高阶（非感觉）丘脑紧密耦合。丘脑反过来接收来自基底神经节和其他皮层下的驱动输入。我们测试了特定丘脑区域的不同皮层输入控制不同的假设。皮质活动的各个方面，包括设定维持短期记忆的时间段、从运动规划过渡到运动执行（目标 1），并更新和维护以下值我们的建模框架（总体而言，项目 5）将动力系统联系起来。从神经计算的角度与实际的多区域神经电路进行比较，并做出可以通过神经生理学测试。我们在小鼠身上采用了两种行为任务，这些任务涉及明确但不同的皮层活动模式。记忆引导的反应任务，前外侧运动皮层（ALM）的神经元表现出准备活动，就在运动开始之前，准备活动就崩溃了。在动态觅食任务中，内侧前额叶皮层的神经元倾向于驱动运动的活动模式。 (mPFC) 显示缓慢变化的活动模式，这些模式与一项行动相对于另一项行动的价值相关。此活动根据新信息进行更新，例如项目 1 - 3 提供的信息的大小。关于连接皮层下区域、丘脑和 ALM / mPFC 的电路建立在这些电路映射的基础上。实验中，我们将从连接的皮层下→丘脑→皮层电路进行同时记录使用具有 5120 个记录位点的新型多柄 Neuropixels 探针（项目 3）。通过皮层下的光遗传学操作和现代多变量分析方法进行记录（数据 Science Core）跟踪皮层下信号如何在记忆引导下通过丘脑传播到皮层。响应任务我们将探讨黑质网状体通过腹内侧核发挥作用，维持运动计划以及中脑运动中心的影响（例如核），通过后内侧核起作用，从运动计划切换到运动启动（目标 1）。在觅食任务中，我们将探究错误预测信号的方式，例如来自腹侧的信号。苍白球 (PALv)，通过前内侧丘脑更新 mPFC 中的记忆相关活动。测量将测试关键模型的预测，进而为认知的多区域回路模型提供信息行为。