US-German Collaboration: Toward a quantitative understanding of navigational deficits in aging humans

该项目的目标是将计算建模与行为和神经成像研究相结合，以表征人类导航能力的机制，并了解它们如何随着年龄的增长而下降。PI将专注于哺乳动物的一个重要的导航回路，它由海马体和相关区域组成，包括内嗅皮层的网格细胞以及位置细胞。位置细胞具有高度位置特异性的反应，在环境中的一个位置打开，在其他地方很少激发；相比之下，网格细胞在环境中的多个位置开火，周期性分离的活动斑点呈惊人的三角形格子图案。对啮齿动物的研究已经详细地描述了网格和位置细胞的特性，并导致了神经网络模型，其额外的预测经常被单个神经元的记录所证实。然而，对人类体内的网格细胞和定位细胞的了解要少得多，在啮齿类动物和人类中，导航回路不同部分之间相互作用的性质也尚不清楚。在这个项目中，PI采用了基于虚拟现实的行为实验、虚拟导航过程中的超高分辨率fMRI记录和神经网络建模，以更好地了解人类空间导航的电路。私人投资促进机构计划从三个方面解决这些问题。首先是通过有和没有准确的外部地标线索的导航环境，以及在其他外部变化的条件下，从现象学的角度表征人类在老年和非老年受试者中所犯的特征错误。第二种是利用网格细胞的神经网络模型，对可能导致观察到的缺陷的网络参数进行建模，然后用神经成像实验来检验这些模型的预测。该实验装置将允许系统地改变外部感官信号的保真度，以探索航位推算(路径积分)与基于地标的导航的互补计算的相对贡献，并揭示它们在人类中的潜在神经基础。这一结果将有助于建立模型，说明平行的空间信息流是如何跨大脑区域组合和处理的，以帮助导航。第三个组成部分是开发准确的算法，从高分辨率的fMRI数据中提取内嗅觉-海马体复合体的区域和子区域的空间信息。其目的是绘制位置信息在不同地区的分布图，并了解老年时位置信息最容易受到影响的地方。该奖项由美国国家科学基金会国际科学与工程主任办公室共同资助。德国教育和研究部(BMBF)正在资助一个配套项目。

The goal of this project is to combine computational modeling with behavioral and neuroimaging studies to characterize the mechanisms of navigational abilities in humans and understand how they decline with age. The PIs will focus on an important navigational circuit in mammals, which consists of the hippocampus and associated areas, and includes grid cells of the entorhinal cortex as well as place cells. Place cells have highly location-specific responses, turning on at one location in an environment and firing little elsewhere; grid cells by contrast fire at multiple locations within an environment, with periodically separated activity blobs in a striking triangular lattice pattern. Studies in rodents have detailed the properties of grid and place cells, and led to neural network models whose additional predictions have often been borne out by single-unit neuron recordings. However, much less is known about grid cells and place cells in humans, and the nature of interactions between different parts of the navigation circuit remains unclear, in rodents and humans. In this project, the PIs bring to bear virtual-reality-based behavioral experiments, ultra-high-resolution fMRI recordings during virtual navigation, and neural network modeling, to better understand the circuit for spatial navigation in humans. The PIs plan a three-pronged approach to these questions. The first is to characterize phenomenologically the characteristic errors made by humans, through navigation environments with and without accurate external landmark cues, and under other externally varying conditions, in aged and non-aged subjects. The second is to employ neural network models of grid cells, to model the network parameters that could give rise to the observed deficits, and in turn test the predictions of these models with the neuroimaging experiments. The experimental setup will permit systematic variation in the fidelity of external sensory cues, to probe the relative contributions of the complementary computations of dead-reckoning (path integration) versus landmark-based navigation, and uncover their potential neural substrates in humans. The results will help to develop models of how parallel streams of spatial information are combined and processed across brain areas to aid in navigation. The third component is to develop accurate algorithms for extracting spatial information from high-resolution fMRI data from regions and sub-regions of the entorhinal-hippocampal complex. The aim is to map the distribution of location information across areas and learn where it is most compromised in old age.This award is being co-funded by NSF's Office of the Director, International Science and Engineering. A companion project is being funded by the German Ministry of Education and Research (BMBF).