Local Circuit Control of Rapid Plasticity and Tunable Ensemble Formation in the Hippocampus

海马体快速可塑性和可调系综形成的局部电路控制

• 批准号: 10725714
• 负责人: Attila Losonczy
• 金额: $ 255.43万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10725714
• 关键词: 3-Dimensional; Acceleration; Area; Behavior; Behavioral; Biotechnology; CNR1 gene; Calcium; Cells; Cholecystokinin; Cognitive; Computer Models; Data; Development; Electrophysiology (science); Endocannabinoids; Environment; Exhibits; Feedback; Fire - disasters; Generations; Glutamates; Hares; Hippocampus; Image; Individual; Inhibitory Synapse; Interneurons; Knowledge; Learning; Location; Maps; Mediating; Memory; Modeling; Molecular; Molecular Profiling; Mus; Myoepithelial cell; Nature; Neuronal Plasticity; Neurons; Optics; Performance; Pharmacogenetics; Pyramidal Cells; Recurrence; Research; Role; Science; Specificity; Statistical Data Interpretation; Synapses; Techniques; Testing; Virtual and Augmented reality; behavior test; candidate identification; cell type; computational network modeling; endocannabinoid signaling; experimental study; flexibility; genetic signature; improved; in vivo; in vivo calcium imaging; innovation; memory encoding; neural; neurodevelopment; neuromechanism; novel; optogenetics; place fields; postsynaptic; receptive field; sensor; transcriptomics; two-photon; virtual reality environment

Project Summary/Abstract Neural representations supporting spatial and episodic learning form, and transform rapidly in the mammalian hippocampus. Individual hippocampal pyramidal cells each fire at a specific location in an environment and together these place cells provide a striking substrate for a cognitive map. A critical step in achieving a mechanistic understanding of how place cell dynamics support hippocampal learning and memory is to be able to re-create endogenous neuronal representations experimentally, and test their behavioral relevance. However, it has not previously been possible to generate lasting hippocampal place cell maps through controlled manipulations of hippocampal plasticity. Our groups have recently identified key potential controllers of hippocampal ensemble formation, raising the intriguing possibility that stable place cell maps can be synthetically generated and allocated by manipulating these controllers. In particular, we demonstrated that any individual, arbitrarily chosen pyramidal cell in the mouse hippocampal area CA1 can be reliably induced to become lasting place cells, using all-optical plasticity induction. Here, we propose to determine if targeted in vivo manipulations of feedback inhibitory (Aim 1), recurrent excitatory (Aim 2), and cell-intrinsic retrograde (Aim 3) local circuit control mechanisms enable the specific generation and allocation of behaviorally relevant neural representation by scaling single-cell optogenetic place cell induction to multi-cellular ensembles. We will test our hypothesis in the hippocampal area CA1 of mice navigating and learning in a virtual reality environment, utilizing a variety of innovative in vivo calcium-imaging, optogenetic, electrophysiology, statistical data analysis, and modeling approaches. We anticipate that our project will have a significant, potentially translatable impact by overcoming major knowledge gaps about cellular and local circuit determinants of neuronal plasticity, while also supporting rapid induced plasticity of neuronal representations. Our research can thereby accelerate the development of neural modulation strategies to study, modify, or improve memory-related behaviors.

项目摘要/摘要 支持空间和情节学习形式的神经表示，并在哺乳动物中迅速转化 海马。单个海马锥体细胞每个在环境中的特定位置发射 这些位置细胞一起为认知图提供了惊人的底物。实现A的关键一步 对位置动态如何支持海马学习和记忆的机械理解是能够 在实验中重新创建内源性神经元表示，并测试其行为相关性。 但是，以前不可能通过 海马可塑性的受控操作。我们的小组最近确定了关键的潜在控制器 海马合奏的形成，提高了稳定的位置细胞图的有趣可能性 通过操纵这些控制器来合成生成和分配。特别是，我们证明了 小鼠海马区域CA1中任何任意选择的锥体细胞CA1都可以可靠地引起 使用全光塑性诱导成为持久的位置细胞。在这里，我们建议确定是否针对 反馈抑制（AIM 1），复发性兴奋性（AIM 2）和细胞内部逆行（AIM 3）局部电路控制机制使特定的产生和分配行为相关的神经 通过将单细胞光遗传位置细胞诱导缩放到多细胞组合来表示。我们将测试 我们在虚拟现实环境中导航和学习的小鼠海马区域CA1中的假设， 利用各种创新的体内钙成像，光遗传学，电生理学，统计数据分析， 和建模方法。我们预计我们的项目将产生重大的，可能翻译的影响 通过克服有关神经元可塑性的细胞和局部电路决定因素的主要知识差距，而 还支持神经元表示的快速诱导可塑性。我们的研究可以加速 开发研究，修改或改善与记忆相关行为的神经调节策略。