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).
