The medial temporal lobe (MTL) has been studied extensively at all levels of analysis, yet its function remains unclear. Theory regarding the cognitive function of the MTL has centered along 3 themes. Different authors have emphasized the role of the MTL in episodic recall, spatial navigation, or relational memory. Starting with the temporal context model (M.W. Howard and M. J. Kahana, 2002), a distributed memory model that has been applied to benchmark data from episodic recall tasks, the authors propose that the entorhinal cortex supports a gradually changing representation of temporal context and the hippocampus proper enables retrieval of these contextual states. Simulation studies show this hypothesis explains the firing of place cells in the entorhinal cortex and the behavioral effects of hippocampal lesion in relational memory tasks. These results constitute a first step towards a unified computational theory of MTL function that integrates neurophysiological, neuropsychological and cognitive findings.

The authors model the neural mechanisms underlying spatial cognition, integrating neuronal systems and behavioral data, and address the relationships between long-term memory, short-term memory, and imagery, and between egocentric and allocentric and visual and ideothetic representations. Long-term spatial memory is modeled as attractor dynamics within medial–temporal allocentric representations, and short-term memory is modeled as egocentric parietal representations driven by perception, retrieval, and imagery and modulated by directed attention. Both encoding and retrieval/imagery require translation between egocentric and allocentric representations, which are mediated by posterior parietal and retrosplenial areas and the use of head direction representations in Papez’s circuit. Thus, the hippocampus effectively indexes information by real or imagined location, whereas Papez’s circuit translates to imagery or from perception according to the direction of view. Modulation of this translation by motor efference allows spatial updating of representations, whereas prefrontal simulated motor efference allows mental exploration. The alternating temporal–parietal flows of information are organized by the theta rhythm. Simulations demonstrate the retrieval and updating of familiar spatial scenes, hemispatial neglect in memory, and the effects on hippocampal place cell firing of lesioned head direction representations and of conflicting visual and ideothetic inputs.

A computational model of how single neurons in and around the rat hippocampus support spatial navigation is reviewed. The extension of this model, to include the retrieval from human longterm memory of spatial scenes and the spatial context of events is discussed. The model explores the link between spatial and mnemonic functions by supposing that retrieval of spatial information from long-term storage requires the imposition of a particular viewpoint. It is consistent with data relating to representational hemispatial neglect and the involvement of the mammillary bodies, anterior thalamus, and hippocampal formation in supporting both episodic recall and the representation of head direction. Some recent behavioural, neuropsychological, and functional neuroimaging experiments are reviewed, in which virtual reality is used to allow controlled study of navigation and memory for events set within a rich large-scale spatial context. These studies provide convergent evidence that the human hippocampus is involved in both tasks, with some lateralization of function (navigation on the right and episodic memory on the left). A further experiment indicates hippocampal involvement in retrieval of spatial information from a shifted viewpoint. I speculate that the hippocampal role in episodic recollection relates to its ability to represent a viewpoint moving within a spatial framework.

Geometric alterations to the boundaries of a virtual environment were used to investigate the representations underlying human spatial memory. Subjects encountered a cue object in a simple rectangular enclosure, with distant landmarks for orientation. After a brief delay, during which they were removed from the arena, subjects were returned to it at a new location and orientation and asked to mark the place where the cue had been. On some trials the geometry (size, aspect ratio) of the arena was varied between presentation and testing. Responses tended to lie somewhere between a location that maintained fixed distances from nearby walls and a location that maintained fixed ratios of the distances between opposing walls. The former were more common after expansions and for cued locations nearer to the edge while the latter were more common after contractions and for locations nearer to the center. The spatial distributions of responses predicted by various simple geometric models were compared to the data. The best fitting model was one derived from the response properties of `place cells' in the rat hippocampus, which matches the `proximities' c of the cue to the four walls of the arena, where d is the distance to a wall and c is a global constant. Subjects also tended to adopt the same orientation at presentation and testing, although this was not due to using a view matching strategy, which could be ruled out in 50% of responses. Disoriented responses were most often seen where the cued location was near the center of the arena or where the long axis of a rectangular arena was changed between presentation and testing, suggesting that the geometry of the arena acts as a weak cue to orientation. Overall, the results suggest a process of visual landmark matching to det...

INTRODUCTION The hippocampus is the most-studied part of the brain, attracting interest due to its position many synapses removed from sensory transducers or motor-e#ectors, its role in human amnesia and Alzheimer's disease, and the discovery of long term potentiation (LTP, see SYNAPTIC PLASTICITY) and of spatially coded cell firing. Bilateral damage to the hippocampus and nearby structures in patient H.M., as treatment for epilepsy, produced a profound retrograde and anterograde amnesia, prompting extensive cross-species research to uncover the specific memory deficit that results from hippocampal damage (the most prominent of which, in the rat, appears to be a deficit in spatial navigation). In short, the hippocampus has become the primary region in the mammalian brain for the study of the synaptic basis of memory and learning. Structurally, it is the simplest form of cortex. It contains one projection cell type, whose cell bodies are confined to a single layer, and receives inputs

A computational model of the hippocampal function in spatial learning is presented. A spatial representation is incrementally acquired during exploration. Visual and self-motion information is fed into a network of rate-coded neurons. A consistent and stable place code emerges by unsupervised Hebbian learning between place- and head direction cells. Based on this representation, goal-oriented navigation is learnt by applying a reward-based learning mechanism between the hippocampus and nucleus accumbens. The model, validated on a real and simulated robot, successfully localises itself by recalibrating its path integrator using visual input. A navigation map is learnt after about 20 trials, comparable to rats in the water maze. In contrast to previous works, this system processes realistic visual input. No compass is needed for localisation and the reward-based learning mechanism extends discrete navigation models to continuous space. The model reproduces experimental findings and suggests several neurophysiological and behavioural predictions in the rat. 1

Modern psychological theories of spatial cognition postulate the existence of a ‘geometric module ’ for reorientation. This concept is derived from experimental data showing that in rectangular arenas with distinct landmarks in the corners, disoriented rats often make diagonal errors, suggesting their preference for the geometric (arena shape) over the non-geometric (landmarks) cues. Moreover, experimentally observed sensitivity of hippocampal cell firing to the changes in the environment layout was taken in support of the geometric module hypothesis. Using a computational model of rat navigation, we propose and test the alternative hypothesis that the influence of spatial geometry on both behavioral and neuronal levels can be explained by the properties of visual features that constitute local views of the environment. Our modeling results suggest that the pattern of diagonal errors observed in the reorientation task can be understood by the analysis of sensory information processing that underlies the navigation strategy employed

The geometric arrangement of surfaces in an environment plays an important role in navigation in vertebrate animals. In this line of research, an animal is typically disoriented and then presented the task of relocating a previously encountered goal. Aside from the geometric shape of the enclosure, other non-geometric (featural) cues are typically available, including colours of walls, objects serving as landmarks, or smells. Animals use both geometric and featural cues, but mammals sometimes rely solely on geometric cues. This has led to views that the processing of geometric information is modular, being the work of a geometric module. Recent work has started to address just what geometric properties are encoded. These current issues are commented on in this paper, and a tentative picture is drawn that both global and local geometry, each in limited ways, are used for navigation. A view of modularity is also presented in which spatial information is stored together (in non-modular fashion), but some computational processes are modular and operate on limited kinds of information.

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ABSTRACT: To investigate conjoint stimulus control over place cells, Fenton et al. (J Gen Physiol 116:191–209, 2000a) recorded while rats foraged in a cylinder with 45 ° black and white cue cards on the wall. Card centers were 135 ° apart. In probe trials, the cards were rotated together or apart by 25°. Firing field centers shifted during these trials, stretching and shrinking the cognitive map. Fenton et al. (2000b) described this deformation with an ad hoc vector field equation. We consider what sorts of neural network mechanisms might be capable of accounting for their observations. In an abstract, maximum likelihood formulation, the rat’s location is estimated by a conjoint probability density function of landmark positions. In an attractor neural network model, recurrent connections produce a bump of activity over a two-dimensional array of cells; the bump’s position is influenced by landmark features such as distances or bearings. If features are chosen with appropriate care, the attractor network and maximum likelihood models yield similar results, in accord with previous demonstrations that recurrent neural networks can efficiently implement maximum likelihood computations (Pouget et al. Neural