Neural signatures of virtual and real-world navigation and spatial learning

项目总结 导航是我们最基本的行为能力之一，也是使用啮齿动物模型进行的大量工作 已经确定海马体是这种复杂行为的关键贡献者。然而，建立模型的努力 这些对人类的影响在范围和概括性上都是有限的。很少有工作探索过 导航和基础非导航学习过程在海马区的相互作用，如 统计学习，因此仍不清楚导航过程如何与以及可能是 在这些学习机制的支持下。此外，对人类的研究主要包括虚拟 导航，限制了已建立的神经信号与真实世界导航的适用性和相关性 行为。理解导航和统计学习如何在人类中竞争或合作 海马体将为记忆系统和巩固的模型提供重要信息，并解决这些问题 现实世界范式中的问题将弥合我们对人类导航的理解上的巨大差距。这 需要多模式方法，结合高时间和空间分辨率的颅内EEG(IEEG) 用人类导航和学习的量化行为测量癫痫患者。在我的博士学位上 到目前为止，我已经使用了行为、计算和iEEG方法来测试假设 人类海马区统计学习与空间导航的相互作用及相关研究 结构。我的工作通过新颖的计算建模技术和 创新的多变量iEEG分析。在我提议的研究和培训计划中，我将使用尖端技术 收集人类慢性脑植入物的直接神经记录的研究方法 在真实世界中进行身体活动。通过我的多学科研究导师，这一经历将 为我提供新的研究方法和生态有效的实验设计培训，以及 治疗癫痫患者的临床观点、考虑和实践。在我的建议中 博士后培养阶段，我会追求更多的临床重点，回到有多现代化的问题上来 认知神经科学可以指导对海马区疾病的评估和治疗。我会得到理论上的 海马区萎缩的高分辨率成像和数据收集的实践经验 人口，包括癫痫和阿尔茨海默氏症患者。这项研究计划有可能告知和 通过探索多种信息的交集，极大地扩展了人类导航和记忆模型 作为共享神经资源的海马体的处理需求，以及这些过程如何在 真实的世界。这项工作代表了关于海马体功能的不同文献的汇聚，以及 为海马区患者的诊断和治疗提供信息。这一计划将使我不仅拥有以下方面的专业知识 行为、计算和神经科学方法，但基础和临床理论敏锐 作为跨学科的首席调查员进行独立调查是必要的。

PROJECT SUMMARY Navigation is one of our most foundational behavioral capacities, and substantial work using rodent models has established the hippocampus as a critical contributor to this complex behavior. However, efforts to model these effects in humans have been limited, both in scope and generalizability. Little work has explored the interaction in the hippocampus between navigation and foundational non-navigation learning processes, like statistical learning, and it therefore remains unclear how navigation processes are integrated with and may be supported by these learning mechanisms. Further, studies in humans have primarily consisted of virtual navigation, limiting applicability and relevance of the established neural signals to real-world navigation behavior. Understanding how navigation and statistical learning compete or cooperate in the human hippocampus will significantly inform models of memory systems and consolidation, and addressing these questions in a real-world paradigm will close a wide gap in our understanding of human navigation. This requires a multimodal approach, coupling the high temporal and spatial resolution of intracranial EEG (iEEG) in epilepsy patients with quantitative behavioral measures of human navigation and learning. In my doctoral dissertation work thus far, I have used behavioral, computational, and iEEG methods to test hypotheses about the interaction between statistical learning and spatial navigation in the human hippocampus and related structures. My work has produced impactful findings via novel computational modeling techniques and innovative multivariate iEEG analyses. In my proposed research and training program, I will use a cutting-edge research method to collect direct neural recordings from chronic brain implants in human participants as they physically ambulate in the real world. Through my multidisciplinary research mentors, this experience will provide me training with novel research methodology and ecologically valid experiment design, as well as clinical perspectives, considerations, and practices for working with patients with epilepsy. In my proposed postdoctoral training phase, I will pursue a more clinical focus, returning to the question of how modern cognitive neuroscience can guide assessments and therapies for hippocampal disease. I will gain theoretical and practical experience with high-resolution imaging and data collection with hippocampal atrophy populations, including epilepsy and Alzheimer’s patients. This research program has the potential to inform and substantially extend models of human navigation and memory by exploring the intersection of multiple processing demands on the hippocampus as a shared neural resource, and how these processes operate in the real world. This work represents the convergence of disparate literatures on hippocampal function, and informs diagnosis and treatment of hippocampal patients. This program will equip me not only with expertise in behavioral, computational, and neuroscientific methodologies, but the basic and clinical theoretical acumen necessary to conduct independent investigation as a principal investigator across disciplines.