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Computational dynamics in neural populations of freely foraging vs. restrained monkeys

自由觅食与受限制猴子神经群体的计算动力学

基本信息

批准号：
10447347
负责人：
Dora Angelaki
金额：
$ 282.8万
依托单位：
NEW YORK 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：
2022-04-15 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10447347
关键词：
3-Dimensional Address Algorithms Animals Area Artificial Intelligence BRAIN initiative Behavior Behavioral Behavioral Model Belief Brain Code Communication Complex Data Decision Making Dimensions Environment Eye Eye Movements Food Future Goals Head Hippocampal Formation Hippocampus (Brain)Joystick Laboratories Learning Macaca Maintenance Mediating Memory Modeling Monitor Monkeys Neurons Neurosciences Parietal Parietal Lobe Pattern Population Prefrontal Cortex Process Psychiatry Psychological reinforcement Recurrence Resources Rewards Role Sensory Solid Strategic Planning System Testing Time Training Uncertainty Visual Work base computerized tools cost entorhinal cortex experimental study eye center flexibility free behavior frontal lobe gaze innovation neurophysiology relating to nervous system response restraint sensory input spatial memory theories tool virtual reality virtual reality environment way finding wireless

项目摘要

Summary This proposal will investigate the neural dynamics underlying three-dimensional foraging behavior, with three overarching goals. The first is to evaluate the neural computations of foraging in dynamic environments in naturalistic settings. The second is to compare the algorithmic behavioral computations and their neural substrates under naturalistic versus traditional laboratory settings. Most neuroscience studies assume that laboratory behavior has real-world implications, so any differences we observe would have remarkable consequences for the future of neuroscience. The third goal is to test the role of hippocampal formation, frontal, and parietal areas in the different components of foraging. We will compare three behaviors in two experimental setups. The behaviors are free-foraging for unpredictable, random rewards, a goal-driven foraging task with navigation among three resource patches under visual uncertainty and stochastic reward presentation, and foraging among three resource patches without navigation. The latter two tasks involve the formation and maintenance of internal models, memories, time-dependent sensory and reward contingencies, the costs of an animal’s own actions, and dynamically changing beliefs about the state of the world. The former two tasks will be performed during head-free navigation in a foraging room, and during head-fixed navigation in virtual reality. In both environments, we will record simultaneously from several mutually interconnected areas involved in visual navigation, spatial memory, path integration, and decision-making. Target areas include posterior parietal cortex, prefrontal cortex, retrosplenial cortex, entorhinal cortex, and hippocampus. We will use advanced behavioral models and theory to infer internal states and to identify their neural representation and interactions across a broad network of interconnected brain areas. In addition, we will regress neuronal activity against task-relevant variables to identify neural subspaces that encode them. Collectively, we expect that these experiments will rigorously illuminate the neural dynamics of foraging and spatial navigation behaviors and critically interrogate whether and how constrained laboratory conditions with head-fixed, restrained animals differ from ecological and naturalistic environments—a critical but still untested assumption of contemporary systems neuroscience.

摘要这项提议将研究三维觅食行为背后的神经动力学，有三个首要目标。第一个是评估在动态环境中觅食的神经计算自然主义的背景。第二个是比较算法行为计算和它们的神经自然主义与传统实验室环境下的基质。大多数神经科学研究都认为实验室行为具有现实意义，因此我们观察到的任何差异都将具有显著的意义。对神经科学未来的影响。第三个目标是测试海马体结构、额叶、和顶区在觅食的不同成分中。我们将在两个实验中比较三种行为设置。这些行为是免费寻找不可预测的随机回报，这是一种目标驱动的觅食任务，具有在视觉不确定性和随机奖励呈现下的三个资源块之间的导航在没有导航的情况下在三个资源补丁之间觅食。后两项任务涉及组建和维护内部模型、记忆、依赖时间的感觉和奖赏意外情况、动物自身的行为，以及关于世界状态的动态变化的信念。前两项任务将在觅食房间中的无头导航和在虚拟现实中的固定头部导航时都可以执行。在这两种环境中，我们将同时从几个相互关联的区域进行记录导航、空间记忆、路径整合和决策。目标区域包括后顶叶皮质，前额叶皮质、脾后皮质、内嗅皮层和海马体。我们将使用高级行为用于推断内部状态并确定其神经表示和相互作用的模型和理论由相互连接的大脑区域组成的广泛网络。此外，我们还将使神经元活动回归与任务相关的状态变量来识别编码它们的神经子空间。总体而言，我们预计这些实验将严格阐明觅食和空间导航行为的神经动力学，并批判性地询问头固定、受限的动物的实验室条件是否以及如何与生态和自然主义环境--当代系统神经科学的一个关键但仍未经检验的假设。