Navigation is an inherently dynamic and multimodal process, making isolation of the unique cognitive components underlying it challenging. The assumptions of much of the literature on human spatial navigation are that 1) spatial navigation involves modality independent, discrete metric representations (i.e., egocentric vs. allocentric), 2) such representations can be further distilled to elemental cognitive processes, and 3) these cognitive processes can be ascribed to unique brain regions. We argue that modality-independent spatial representations, instead of providing exact metrics about our surrounding environment, more often involve heuristics for estimating spatial topology useful to the current task at hand. We also argue that egocentric (body centered) and allocentric (world centered) representations are better conceptualized as involving a continuum rather than as discrete. We propose a neural model to accommodate these ideas, arguing that such representations also involve a continuum of network interactions centered on retrosplenial and posterior parietal cortex, respectively. Our model thus helps explain both behavioral and neural findings otherwise difficult to account for with classic models of spatial navigation and memory, providing a testable framework for novel experiments.

Accurate memory for discrete events is thought to rely on pattern separation to orthogonalize the representations of similar events. Previously, we reported that a behavioral index of pattern separation was correlated with activity in the hippocampus (dentate gyrus, CA3) and with integrity of the perforant path, which provides input to the hippocampus. If the hippocampus operates as part of a broader neural network, however, pattern separation would likely also relate to integrity of limbic tracts (fornix, cingulum bundle, and uncinate fasciculus) that connect the hippocampus to distributed brain regions. In this study, healthy adults (20-89 years) underwent diffusion tensor imaging and completed the Behavioral Pattern Separation Task-Object Version (BPS-O) and Rey Auditory Verbal Learning Test (RAVLT). After controlling for global effects of brain aging, exploratory skeleton-wise and targeted tractography analyses revealed that fornix integrity (fractional anisotropy, mean diffusivity, and radial diffusivity; but not mode) was significantly related to pattern separation (measured using BPS-O and RAVLT tasks), but not to recognition memory. These data suggest that hippocampal disconnection, via individual- and age-related differences in limbic tract integrity, contributes to pattern separation performance. Extending our earlier work, these results also support the notion that pattern separation relies on broad neural networks interconnecting the hippocampus.

Previous studies from our lab have indicated that healthy older adults are impaired in their ability to mnemonically discriminate between previously viewed objects and similar lure objects in the Mnemonic Similarity Task (MST). These studies have used either old/similar/new or old/new test formats. The forced-choice test format (e.g., “Did you see object A or object A’ during the encoding phase?”) relies on different assumptions than the old/new test format (e.g., “Did you see this object during the encoding phase?”); hence, converging evidence from these approaches would bolster the conclusion that healthy aging is accompanied by impaired performance on the MST. Consistent with our hypothesis, healthy older adults exhibited impaired performance on a forced-choice test format that required discriminating between a target and a similar lure. We also tested the hypothesis that age-related impairments on the MST could be modeled within a global matching computational framework. We found that decreasing the probability of successful feature encoding in the models caused changes that were similar to the empirical data in healthy older adults. Collectively, our behavioral results extend to the forced-choice test format the finding that healthy aging is accompanied by an impaired ability to discriminate between targets and similar lures, and our modeling results suggest that a diminished probability of encoding stimulus features is a candidate mechanism for memory changes in healthy aging. We also discuss the ability of global matching models to account for findings in other studies that have used variants on mnemonic similarity tasks.

In humans, the extent to which body-based cues, such as vestibular, somatosensory, and motoric cues, are necessary for normal expression of spatial representations remains unclear. Recent breakthroughs in immersive virtual reality technology allowed us to test how body-based cues influence spatial representations of large-scale environments in humans. Specifically, we manipulated the availability of body-based cues during navigation using an omnidirectional treadmill and a head-mounted display, investigating brain differences in levels of activation (i.e., univariate analysis), patterns of activity (i.e., multivariate pattern analysis), and putative network interactions between spatial retrieval tasks using fMRI. Our behavioral and neuroimaging results support the idea that there is a core, modality-independent network supporting spatial memory retrieval in the human brain. Thus, for well-learned spatial environments, at least in humans, primarily visual input may be sufficient for expression of complex representations of spatial environments.

Contemporary theories of the medial temporal lobe (MTL) suggest that there are functional differences between the MTL cortex and the hippocampus. High-resolution functional magnetic resonance imaging and multivariate pattern analysis were utilized to study whether MTL subregions could classify categories of images, with the hypothesis that the hippocampus would be less representationally categorical than the MTL cortex. Results revealed significant classification accuracy for faces versus objects and faces versus scenes in MTL cortical regions—parahippocampal cortex and perirhinal cortex—with little evidence for category discrimination in the hippocampus. MTL cortical regions showed significantly greater classification accuracy than the hippocampus. The hippocampus showed significant classification accuracy for images compared to a non-mnemonic baseline task, suggesting that it responded to the images. Classification accuracy in a region of interest encompassing retrosplenial cortex and the posterior cingulate cortex posterior to retrosplenial cortex (RSC/PCC), showed a similar pattern of results to parahippocampal cortex, supporting the hypothesis that these regions are functionally related. The results suggest that parahippocampal cortex, perirhinal cortex, and RSC/PCC are representationally categorical and the hippocampus is more representationally agnostic, which is concordant with the hypothesis of the role of the hippocampus in pattern separation.