Impaired Spatial Reorientation in the 3xTg-AD Mouse Model of Alzheimer's Disease.

In early Alzheimer's disease (AD) spatial navigation is impaired; however, the precise cause of this impairment is unclear. Recent evidence suggests that getting lost is one of the first impairments to emerge in AD. It is possible that getting lost represents a failure to use distal cues to get oriented in space. Therefore, we set out to look for impaired use of distal cues for spatial orientation in a mouse model of amyloidosis (3xTg-AD). To do this, we trained mice to shuttle to the end of a track and back to an enclosed start box to receive a water reward. Then, mice were trained to stop in an unmarked reward zone to receive a brain stimulation reward. The time required to remain in the zone for a reward was increased across training, and the track was positioned in a random start location for each trial. We found that 6-month female, but not 3-month female, 6-month male, or 12-month male, 3xTg-AD mice were impaired. 6-month male and female mice had only intracellular pathology and male mice had less pathology, particularly in the dorsal hippocampus. Thus, AD may cause spatial disorientation as a result of impaired use of landmarks

Individual differences in human path integration abilities correlate with gray matter volume in retrosplenial cortex, hippocampus, and medial prefrontal cortex

Humans differ in their individual navigational abilities. These individual differences may exist in part because successful navigation relies on several disparate abilities, which rely on different brain structures. One such navigational capability is path integration, the updating of position and orientation, in which navigators track distances, directions, and locations in space during movement. Although structural differences related to landmark-based navigation have been examined, gray matter volume related to path integration ability has not yet been tested. Here, we examined individual differences in two path integration paradigms: (1) a location tracking task and (2) a task tracking translational and rotational self-motion. Using voxel-based morphometry, we related differences in performance in these path integration tasks to variation in brain morphology in 26 healthy young adults. Performance in the location tracking task positively correlated with individual differences in gray matter volume in three areas critical for path integration: the hippocampus, the retrosplenial cortex, and the medial prefrontal cortex. These regions are consistent with the path integration system known from computational and animal models and provide novel evidence that morphological variability in retrosplenial and medial prefrontal cortices underlies individual differences in human path integration ability. The results for tracking rotational self-motion-but not translation or location-demonstrated that cerebellum gray matter volume correlated with individual performance. Our findings also suggest that these three aspects of path integration are largely independent. Together, the results of this study provide a link between individual abilities and the functional correlates, computational models, and animal models of path integration

Neuronal vector coding in spatial cognition

Several types of neurons involved in spatial navigation and memory encode the distance and direction (that is, the vector) between an agent and items in its environment. Such vectorial information provides a powerful basis for spatial cognition by representing the geometric relationships between the self and the external world. Here, we review the explicit encoding of vectorial information by neurons in and around the hippocampal formation, far from the sensory periphery. The parahippocampal, retrosplenial and parietal cortices, as well as the hippocampal formation and striatum, provide a plethora of examples of vector coding at the single neuron level. We provide a functional taxonomy of cells with vectorial receptive fields as reported in experiments and proposed in theoretical work. The responses of these neurons may provide the fundamental neural basis for the (bottom-up) representation of environmental layout and (top-down) memory-guided generation of visuospatial imagery and navigational planning

Neural Representations of a Real-World Environment

The ability to represent the spatial structure of the environment is critical for successful navigation. Extensive research using animal models has revealed the existence of specialized neurons that appear to code for spatial information in their firing patterns. However, little is known about which regions of the human brain support representations of large-scale space. To address this gap in the literature, we performed three functional magnetic resonance imaging (fMRI) experiments aimed at characterizing the representations of locations, headings, landmarks, and distances in a large environment for which our subjects had extensive real-world navigation experience: their college campus. We scanned University of Pennsylvania students while they made decisions about places on campus and then tested for spatial representations using multivoxel pattern analysis and fMRI adaptation. In Chapter 2, we tested for representations of the navigator\u27s current location and heading, information necessary for self-localization. In Chapter 3, we tested whether these location and heading representations were consistent across perception and spatial imagery. Finally, in Chapter 4, we tested for representations of landmark identity and the distances between landmarks. Across the three experiments, we observed that specific regions of medial temporal and medial parietal cortex supported long-term memory representations of navigationally-relevant spatial information. These results serve to elucidate the functions of these regions and offer a framework for understanding the relationship between spatial representations in the medial temporal lobe and in high-level visual regions. We discuss our findings in the context of the broader spatial cognition literature, including implications for studies of both humans and animal models

Resting state connectivity between medial temporal lobe regions and intrinsic cortical networks predicts performance in a path integration task

Humans differ in their individual navigational performance, in part because successful navigation relies on several diverse abilities. One such navigational capability is path integration, the updating of position and orientation during movement, typically in a sparse, landmark-free environment. This study examined the relationship between path integration abilities and functional connectivity to several canonical intrinsic brain networks. Intrinsic networks within the brain reflect past inputs and communication as well as structural architecture. Individual differences in intrinsic connectivity have been observed for common networks, suggesting that these networks can inform our understanding of individual spatial abilities. Here, we examined individual differences in intrinsic connectivity using resting state magnetic resonance imaging (rsMRI). We tested path integration ability using a loop closure task, in which participants viewed a single video of movement in a circle trajectory in a sparse environment, and then indicated whether the video ended in the same location in which it started. To examine intrinsic brain networks, participants underwent a resting state scan. We found that better performance in the loop task was associated with increased connectivity during rest between the central executive network (CEN) and posterior hippocampus, parahippocampal cortex (PHC) and entorhinal cortex. We also found that connectivity between PHC and the default mode network (DMN) during rest was associated with better loop closure performance. The results indicate that interactions between medial temporal lobe (MTL) regions and intrinsic networks that involve prefrontal cortex (PFC) are important for path integration and navigation.This work was supported by the Office of Naval Research (ONR MURI N00014-10-1-0936 and MURI N00014-16-1-2832). fMRI scanning was completed at the Athinoula A. Martinos Center for Biomedical Imaging (Charlestown, MA, USA), which receives support from the National Center for Research Resources (NCRR P41RR14075). (ONR MURI N00014-10-1-0936 - Office of Naval Research; MURI N00014-16-1-2832 - Office of Naval Research; NCRR P41RR14075 - National Center for Research Resources)Published versio

Functional MRI investigations of path integration and goal-directed navigation in humans

Path integration is a navigational process that humans and animals use to track changes in their position and orientation. Animal and computational studies suggest that a spatially-tuned navigation system supports path integration, yet this system is not well understood in humans. Here, the prediction was tested that path integration mechanisms and goal-directed navigation in humans would recruit the same key brain regions within the parietal cortex and medial temporal lobes as predicted by animal and computational models. The three experiments described in this dissertation used behavioral and functional magnetic resonance imaging methods in 131 adults (18-35 years) to examine behavioral and brain correlates of navigation. In a landmark-free environment, path integration mechanisms are utilized to update position and orientation to a goal. Experiment 1 examined neural correlates of these mechanisms in the human brain. The results demonstrated that successful first and third person perspective navigation recruited the anterior hippocampus. The posterior hippocampus was found to track distance and temporal proximity to a goal location. The retrosplenial and posterior parietal cortices were additionally recruited for successful goal-directed navigation. In a landmark-rich environment, humans utilize route-based strategies to triangulate between their position, landmarks, and navigational goal. Experiment 2 contrasted path integration and landmark-based strategies by adding a solitary landmark to a sparse environment. The results demonstrated that successful navigation with and without an orienting landmark recruited the anterior hippocampus. Activity in the bilateral posterior hippocampus was modulated by larger triangulation between current position, landmark, and goal location during first person perspective navigation. The caudate nucleus was additionally recruited for landmark-based navigation. Experiment 3 used functional connectivity methods coupled with two fMRI tasks to determine whether areas responsive to optic flow, specifically V3A, V6, and the human motion complex (hMT+), are functionally connected to brain regions recruited during first person perspective navigation. The results demonstrated a functional relationship between optic flow areas and navigationally responsive regions, including the hippocampus, retrosplenial, posterior parietal, and medial prefrontal cortices. These studies demonstrate that goal-directed navigation is reliant upon a navigational system supported by hippocampal position computations and orientation calculations from the retrosplenial and posterior parietal cortices

Spatial navigation deficits — overlooked cognitive marker for preclinical Alzheimer disease?

Detection of incipient Alzheimer disease (AD) pathophysiology is critical to identify preclinical individuals and target potentially disease-modifying therapies towards them. Current neuroimaging and biomarker research is strongly focused in this direction, with the aim of establishing AD fingerprints to identify individuals at high risk of developing this disease. By contrast, cognitive fingerprints for incipient AD are virtually non-existent as diagnostics and outcomes measures are still focused on episodic memory deficits as the gold standard for AD, despite their low sensitivity and specificity for identifying at-risk individuals. This Review highlights a novel feature of cognitive evaluation for incipient AD by focusing on spatial navigation and orientation deficits, which are increasingly shown to be present in at-risk individuals. Importantly, the navigation system in the brain overlaps substantially with the regions affected by AD in both animal models and humans. Notably, spatial navigation has fewer verbal, cultural and educational biases than current cognitive tests and could enable a more uniform, global approach towards cognitive fingerprints of AD and better cognitive treatment outcome measures in future multicentre trials. The current Review appraises the available evidence for spatial navigation and/or orientation deficits in preclinical, prodromal and confirmed AD and identifies research gaps and future research priorities

Decision in space

Human navigation is generally believed to rely on two types of strategy adoption, route- based and map-based strategies. Both types of navigation require making spatial decisions along the traversed way. Nevertheless, formal computational and neural links between navigational strategies and mechanisms of value based decision making have so far been underexplored in humans. Here, we employed functional magnetic resonance imaging (fMRI) while subjects located different target objects in a virtual environment. We then modelled their paths using reinforcement learning (RL) algorithms, which successfully explain decision behaviour and its neural correlates. Our results show that subjects used a mixture of route and map-based navigation, and their paths could be well explained by the model-free and model-based RL algorithms. Furthermore, the value signals of model-free choices during route-based navigation modulated the BOLD signals in the ventro-medial prefrontal cortex (vmPFC). On the contrary, the BOLD signals in parahippocampal and medial temporal lobe (MTL) regions pertained to model- based value signals during map-based navigation. Our findings suggest that the brain might share computational mechanisms and neural substrates for navigation and value- based decisions, such that model-free choice guides route-based navigation and model- based choice directs map-based navigation. These findings open new avenues for computational modelling of wayfinding by directing attention to value-based decision, differing from common direction and distances approaches. The ability to find one’s way in a complex environment is crucial to everyday functioning. This navigational ability relies on the integrity of several cognitive functions and different strategies, route and map-based navigation, that individuals may adopt while navigating in the environment. As the integrity of these cognitive functions often decline with age, navigational abilities show marked changes in both normal aging and dementia. Combining a wayfinding task in a virtual reality (VR) environment and modeling technique based on reinforcement learning (RL) algorithms, we investigated the effects of cognitive aging on the selection and adoption of navigation strategies in human. The older participants performed the wayfinding task while undergoing functional Magnetic Resonance Imaging (fMRI), and the younger participants performed the same task outside the MRI machine. Compared with younger participants, older participants traversed a longer distance. They also exhibited a higher tendency to repeat previously established routes to locate the target objects. Despite these differences, the traversed paths in both groups could be well explained by the model-free and model-based RL algorithms. Furthermore, neuroimaging results from the older participants show that BOLD signal in the ventromedial prefrontal cortex (vmPFC) pertained to model-free value signals. This result provide evidence on the utility of the RL algorithms to explain how the aging brain computationally prefer to rely more on the route-based navigation

Single‐trial regression of spatial exploration behavior indicates posterior EEG alpha modulation to reflect egocentric coding

Learning to navigate uncharted terrain is a key cognitive ability that emerges as a deeply embodied process, with eye movements and locomotion proving most useful to sample the environment. We studied healthy human participants during active spatial learning of room-scale virtual reality (VR) mazes. In the invisible maze task, participants wearing a wireless electroencephalography (EEG) headset were free to explore their surroundings, only given the objective to build and foster a mental spatial representation of their environment. Spatial uncertainty was resolved by touching otherwise invisible walls that were briefly rendered visible inside VR, similar to finding your way in the dark. We showcase the capabilities of mobile brain/body imaging using VR, demonstrating several analysis approaches based on general linear models (GLMs) to reveal behavior-dependent brain dynamics. Confirming spatial learning via drawn sketch maps, we employed motion capture to image spatial exploration behavior describing a shift from initial exploration to subsequent exploitation of the mental representation. Using independent component analysis, the current work specifically targeted oscillations in response to wall touches reflecting isolated spatial learning events arising in deep posterior EEG sources located in the retrosplenial complex. Single-trial regression identified significant modulation of alpha oscillations by the immediate, egocentric, exploration behavior. When encountering novel walls, as well as with increasing walking distance between subsequent touches when encountering novel walls, alpha power decreased. We conclude that these oscillations play a prominent role during egocentric evidencing of allocentric spatial hypotheses