Neural and Computational Architecture for Complex Navigation and Subjective Self-Location

用于复杂导航和主观自定位的神经和计算架构

• 批准号: 10664227
• 负责人: Jean-Paul Noel
• 金额: $ 12.69万
• 依托单位: NEW YORK UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10664227
• 关键词: Accounting; Adaptive Behaviors; Animals; Architecture; Area; Award; Behavior; Behavioral; Belief; Biological; Biological Psychiatry; Brain; Cells; Code; Cognition; Cognitive; Cognitive Science; Communication; Complement; Complex; Coupling; Darkness; Data Collection; Data Science; Development Plans; Disease; Disparity; Environment; Feedback; Fireflies; Foundations; Genetic Variation; Goals; Grant; Health; Hippocampal Formation; Hippocampus; Human; Human Resources; Illusions; Institution; International; Knowledge; Link; Location; Maps; Measures; Mediating; Mentors; Modeling; Motion; Motor; Movement; Mus; Neurons; Neurosciences; Personal Space; Phase; Photons; Physiology; Positioning Attribute; Prize; Process; Research; Retina; Rodent; Rodent Model; Schizophrenia; Scientist; Sensory; Signal Transduction; System; Techniques; Technology; Testing; Training; Visual Motion; Work; Writing; autism spectrum disorder; career; career development; cranium; design; experience; member; mouse model; multisensory; neglect; neural; neural circuit; neurophysiology; nonhuman primate; novel; novel therapeutics; object motion; optic flow; phenomenological models; place fields; preference; receptive field; skills; virtual; virtual reality; visual motor; way finding

Project Summary Candidate and Career Goals: I intend to become an independent scientist at a research-first academic institution, bridging across levels of description (i.e., from computations to neurons) and furthering our understanding of how the brain infers the world around us, as well as ourselves within it. I trained as a cognitive scientist (winning the Glushko Prize for best dissertation in Cognitive Science, worldwide), with a focus on understanding our sense of self-location; where am “I” located in space. I am now training in systems neuroscience, developing expertise in large-scale rodent neurophysiology and with a focus on the dynamic aspects of self-location; spatial navigation. These experiences complement each other; from behavioral computations to single-units, and from static to dynamic self-location. Environment and Career Development Plan: I am mentored by Dr. Dora Angelaki (NYU, expertise in navigation) and co-mentored by Drs. David Schneider (NYU, rodent self-generated actions) and Cristina Savin (NYU, data science). Further, I am a scientist member of the International Brain Lab, allowing me the opportunity to leverage world-class expertise (22 labs) in rodent neurophysiology. My training during the K99 will focus on model-based analyses of behavior and neurons during continuous and complex naturalistic tasks, as well as lab management skills (i.e., personnel, grant-writing, communication). Research Plan: Spatial navigation is central to adaptive behavior, underlying our ability to trade-off the exploitation of our current location with the exploration of novel ones. Beautiful work has detailed a number of spatial codes (e.g., place and grid cells) in the hippocampal formation, yet we (1) lack a normative framework accounting for the complexities of natural navigation, (2) do not understand how spatial codes from the hippocampal formation interact with cortex, and (3) have focused on understanding how we build internal models of the world around us, while neglecting its starting point – ourselves. During the K99 phase of the award, I will develop a naturalistic navigation task in virtual reality where rodents will be required to disambiguate complex signals. These animals will be trained to integrate velocity signals derived from motion across their retina (i.e., optic flow) into a position estimate, in order to path integrate to the location of a latent target. Then, they will be tested in a novel situation, one where optic flow may be caused by self- and/or target-motion. I expect animals to behave in line with Bayesian Causal Inference (BCI) – a canonical computation wherein estimation biases emerge during small, but not large, signal disparities (i.e., when observers operate under the incorrect internal model). Further, I will broadly map neural activity throughout the rodent’s brain during BCI by leveraging novel large-scale neurophysiology techniques. During the R00 phase of the award, I will directly manipulate the subjective sense of self-location – the initial condition for navigation - and measure this phenomenology in rodents via the task developed during the K99. Beyond establishing BCI as a fundamental computation guiding naturalistic navigation, I expect the proposed project to inform next-generation therapeutics for disorders of inference, such as Autism and Schizophrenia.

项目摘要 候选人和职业目标：我打算成为一名独立的科学家在一个研究第一的学术机构， 跨描述级别的桥接（即，从计算到神经元），并进一步加深我们对 大脑如何推断我们周围的世界，以及我们自己在其中。 Glushko奖认知科学最佳论文，全球），重点是理解我们的感觉 自我定位;我在空间中的位置。我现在正在接受系统神经科学的培训， 在大规模的啮齿动物神经生理学和自我定位的动态方面的重点;空间 导航这些经验相互补充;从行为计算到单个单元， 静态到动态的自我定位。环境和职业发展计划：我的导师是Dora Angelaki博士 (NYU大卫施耐德博士（纽约大学，啮齿动物自发行动） Cristina Savin（纽约大学，数据科学）。此外，我是国际大脑实验室的科学家成员， 我有机会利用啮齿动物神经生理学的世界级专业知识（22个实验室）。我的训练在 K99将专注于在连续和复杂的自然过程中对行为和神经元进行基于模型的分析。 任务，以及实验室管理技能（即，人事、赠款书写、通信）。研究计划：空间 导航是适应性行为的核心，是我们权衡利用当前位置的能力的基础 探索新奇的事物。美丽的工作详细介绍了一些空间代码（例如，地点和网格 细胞）在海马结构，但我们（1）缺乏一个规范的框架，占的复杂性， 自然导航，（2）不了解海马结构的空间代码如何与皮质相互作用， （3）专注于理解我们如何建立周围世界的内部模型，而忽视了 它的起点--我们自己。在K99阶段的奖励，我将开发一个自然的导航任务， 在虚拟现实中，啮齿动物将被要求消除复杂信号的歧义。这些动物将被训练成 积分从视网膜上的运动导出的速度信号（即，光流）转换为位置估计，以便 以路径整合到潜在目标的位置。然后，他们将在一个新的情况下进行测试， 流动可以由自身运动和/或目标运动引起。我希望动物的行为符合贝叶斯因果关系 推理（BCI）-一种典型的计算，其中估计偏差出现在小，但不是大，信号 不一致（即，当观察者在不正确的内部模型下操作时）。此外，我将广泛地映射神经 通过利用新的大规模神经生理学技术，在BCI期间观察啮齿动物大脑的活动。 在R 00阶段的奖励，我将直接操纵自我定位的主观感觉-初始 导航条件-并通过K99期间开发的任务测量啮齿动物中的这种现象。 除了将BCI建立为指导自然主义导航的基本计算之外，我希望提出的 该项目旨在为下一代推理障碍（如自闭症和精神分裂症）的治疗提供信息。