Neuroimaging of dynamic navigational codes

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Project Summary: Spatial navigation is a challenge that must be met by all mobile organisms. Although much is known about the neural mechanisms that underlie spatial navigation in animals, the neurocognitive basis of spatial navigation in humans is much less clear. This is partly because of technical limitations: the best tool currently available for noninvasive measurement of brain activity is functional magnetic resonance imaging (fMRI), but traditional fMRI analysis methods are not well-suited for identifying representations elicited in dynamic, naturalistic situations such as unconstrained navigational episodes. The current project will attempt to overcome this limitation by using a recent technical innovation in fMRI analysis—voxel-wise encoding modeling—to identify the neural representations that mediate active navigation. Specifically, we will model the fMRI response during navigation within a virtual-reality city in terms of the spatial variables that are known to have known cellular coordinates correlates in rodents and non-human primates, and we will then evaluate the model by testing whether it predicts fMRI response in a held-out dataset not used to train the model. Additionally, we will explore whether the representations thus revealed suffice to solve the problem of simultaneous localization and mapping (SLAM); that is, whether they allow one to keep track of one's position during exploration of a novel environment while simultaneously learning its layout. Aim 1 is to build the voxel-wise encoding model and to use it to identify the neural representations within specific brain regions that mediate dynamic navigation. Aim 2 is to examine generalization across environments by testing whether a model trained in one virtual environment suffices to solve the problem of SLAM in another. If successful, we anticipate that this project will have a major and sustained impact on the field by achieving a quantitative description of how spatial information is encoded in multiple regions of the human brain during dynamic real-time navigation. This will allow us to test specific hypotheses about spatial representations developed from the animal literature, and potentially allow this literature to be leveraged to better understand multiple cognitive functions that rely on the same underlying neural architecture, including spatial cognition, episodic memory, and imagination. Moreover, this project will provide the essential technical foundation for future tests of novel hypotheses about the physiological basis of navigation.