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Hippocampo-cortical contributions to world building in freely behaving macaques

海马皮质对自由行为的猕猴世界建设的贡献

基本信息

批准号：
10447412
负责人：
KARI HOFFMAN
金额：
$ 231.67万
依托单位：
VANDERBILT UNIVERSITY
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：
2022-05-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10447412
关键词：
Address Age Appearance Area Behavior Biological Models Brain Brain region Categories Cognition Complex Computer Models Coupling Decision Making Dissociation Electrodes Environment Episodic memory Event Future Habitats Haplorhini Hippocampus (Brain)Human Immersion Influentials Interruption Intervention Knowledge Learning Location Longevity Macaca Measures Memory Memory impairment Methodology Methods Modeling Monkeys Movement Mus Nature Neocortex Neurodegenerative Disorders Neurons Pathway interactions Performance Play Population Predisposition Primates Process Rattus Research Resolution Rodent Rodent Model Role Roter Seizures Semantics Site Structure System Systems Theory Testing Time Traumatic Brain Injury Visual adjudicate density educational atmosphere entorhinal cortex episodic memory impairment experimental study healthy aging learning strategy memory recall memory retrieval microstimulation neocortical neuronal circuitry predictive modeling prevent recruit relating to nervous system spatiotemporal statistical learning stem theories wireless

项目摘要

PROJECT SUMMARY/ABSTRACT When learning in complex, realistic, or even real worlds, we have the benefit of using different strategies adaptively. For most primate brains, adaptive means adjusting as a function of where we are, who we are with, and what things of use are in view or in reach. Learning theories like Complementary Learning Systems (CLS) originally suggested that the hippocampus and neocortical structures contributed distinct computations to represent different kinds of memory. This theory relied heavily on assumptions about the finer structure of neurons in these areas, built largely from knowledge of these structures in rats and to some extent mice. Methodological limitations have prevented measuring in primates (human or monkey) the fine circuit computations predicted by these models. This has led to assumptions that the computations are similar to those in rodents, yet rodents have very different real-world behaviors from primates. We propose to check these assumptions and extend and/or revise the theory, by recording wirelessly in macaques who learn rules about objects in an immersive, real-world enclosure. We will use high- density, multi-site recordings in and around the hippocampus to test two major aspects of memory theory in need of resolution. First, we ask if there are differences in the two main hippocampal-CA1 inputs in supporting episodic and category learning. This question derives from an untested prediction of our expanded CLS model. We will record wirelessly as macaques make decisions about the assignment of object exemplars (‘FauXna’) on displays set up in their environment. The model predicts that CA3-CA1 inputs are particularly supportive of the arbitrary mappings required for episodic memory, whereas layer III entorhinal cortex ‘direct’ inputs are more involved in integrating information across trials, affording object category learning. Using high-definition linear arrays, we can resolve CA1 dendritic field currents as well as multi-site ensemble unit activity, allowing us to test our prediction for the first time. Second, we ask if the hippocampal and connected neocortical dynamics play a role in memory retrieval as a function of either memory age or of the episodic/semantic nature of the task. We will use closed-loop stimulation to interrogate the necessity of each region during recall, and the role of coordinated activity between hippocampus and neocortex for recall, across memory age and type. From these experiments we will (1) disambiguate several competing theories of the division of labor across nodes in the memory network, (2) create the first conceptual microcircuit model of these memory systems in the primate brain, and (3) contrast with our expanded computational model.

项目概要/摘要当在复杂的、现实的、甚至真实的世界中学习时，我们可以使用不同的方法来受益。自适应策略。对于大多数灵长类动物的大脑来说，适应性意味着根据我们所处的位置进行调整我们是谁，我们和谁在一起，以及我们可以看到或触手可及的有用的东西。学习理论如补充学习系统（CLS）最初认为海马体和新皮质结构贡献了不同的计算来表示不同类型的内存。这个理论依赖于很大程度上基于对这些区域神经元更精细结构的假设，这些结构主要是由了解大鼠以及某种程度上小鼠的这些结构。方法学上的限制阻碍了灵长类动物（人类或猴子）精细回路的测量这些模型预测的计算。这导致了计算的假设与啮齿类动物相似，但啮齿类动物在现实世界中的行为与灵长类动物截然不同。我们建议通过无线记录来检查这些假设并扩展和/或修改理论猕猴在身临其境的现实世界中学习物体的规则。我们将使用高密度，海马体内部和周围的多点记录，以测试记忆的两个主要方面需要解决的理论。首先，我们询问两个主要的海马 CA1 输入在支持情景方面是否存在差异。和类别学习。这个问题源自我们扩展的 CLS 模型的未经测试的预测。我们将无线记录猕猴做出关于对象样本分配的决定（“FauXna”）在其环境中设置的显示器上。该模型预测 CA3-CA1 输入是特别支持情景记忆所需的任意映射，而第三层内嗅皮层“直接”输入更多地涉及跨试验的信息整合，提供对象类别学习。利用高清线阵，我们可以解析CA1树突场电流以及多站点集合单元的活动，使我们能够第一次测试我们的预测。其次，我们询问海马体和相连的新皮质动力学是否在记忆中发挥作用检索作为记忆年龄或任务的情景/语义性质的函数。我们将使用闭环刺激来询问回忆过程中每个区域的必要性，以及协调海马体和新皮质之间的记忆活动，跨越记忆年龄和类型。从这些实验中，我们将（1）消除几种相互竞争的劳动分工理论的歧义跨存储网络中的节点，(2) 创建这些的第一个概念微电路模型灵长类动物大脑中的记忆系统，以及（3）与我们扩展的计算模型对比。