We review evidence for the boundary vector cell model of the environmental determinants of the firing of hippocampal place cells. Preliminary experimental results are presented concerning the effects of addition or removal of environmental boundaries on place cell firing and evidence that boundary vector cells may exist in the subiculum. We review and update computational simulations predicting the location of human search within a virtual environment of variable geometry, assuming that boundary vector cells provide one of the input representations of location used in mammalian spatial memory. Finally, we extend the model to include experiencedependent modification of connection strengths through a BCM-like learning rule, and compare the effects to experimental data on the firing of place cells under geometrical manipulations to their environment. The relationship between neurophysiological results in rats and spatial behaviour in humans is discussed.

Over the past four decades, research has revealed that cells in the hippocampal formation provide an exquisitely detailed representation of an animal's current location and heading. These findings have provided the foundations for a growing understanding of the mechanisms of spatial cognition in mammals, including humans. We describe the key properties of the major categories of spatial cells: place cells, head direction cells, grid cells and boundary cells, each of which has a characteristic firing pattern that encodes spatial parameters relating to the animal's current position and orientation. These properties also include the theta oscillation, which appears to play a functional role in the representation and processing of spatial information. Reviewing recent work, we identify some themes of current research and introduce approaches to computational modelling that have helped to bridge the different levels of description at which these mechanisms have been investigated. These range from the level of molecular biology and genetics to the behaviour and brain activity of entire organisms. We argue that the neuroscience of spatial cognition is emerging as an exceptionally integrative field which provides an ideal test-bed for theories linking neural coding, learning, memory and cognition.

ABSTRACT:The hippocampus plays a crucial role within the neural systems for long-term memory, but little if any role in the short-term retention of some types of stimuli. Nonetheless, the hippocampus may be specialized for allocentric topographical processing, which impacts on short-term memory or even perception. To investigate this we developed performance-matched tests of perception (match-to-sample) and shortterm memory (2 s delayed-match-to-sample) for the topography and for the nonspatial aspects of visual scenes. Four patients with focal hippocampal damage and one with more extensive damage, including right parahippocampal gyrus, were tested. All five patients showed impaired topographical memory and spared nonspatial processing in both memory and perception. Topographical perception was profoundly impaired in the patient with parahippocampal damage, mildly impaired in two of the hippocampal cases, and clearly preserved in the other two hippocampal cases (including one with dense amnesia). Our results suggest that the hippocampus supports allocentric topographical processing that is indispensable when appropriately tested after even very short delays, while the presence of the sample scene can allow successful topographical perception without it, possibly via a less flexible parahippocampal representation. V V C 2006 Wiley-Liss, Inc.

A model of place‐cell firing is presented that makes quantitative predictions about specific place cells' spatial receptive fields following changes to the rat's environment. A place cell's firing rate is modeled as a function of the rat's location by the thresholded sum of the firing rates of a number of putative cortical inputs. These inputs are tuned to respond whenever an environmental boundary is at a particular distance and allocentric direction from the rat. The initial behavior of a place cell in any environment is simply determined by its set of inputs and its threshold; learning is not necessary. The model is shown to produce a good fit to the firing of individual place cells, and populations of place cells across environments of differing shape. The cells' behavior can be predicted for novel environments of arbitrary size and shape, or for manipulations such as introducing a barrier. The model can be extended to make behavioral predictions regarding spatial memory. Hippocampus 10:369–379, 2000 © 2000 Wiley‐Liss, Inc.

Detection of coherent motion versus noise is widely used as a measure of global visual-motion processing. To localise the human brain mechanisms involved in this performance, functional magnetic resonance imaging (fMRI) was used to compare brain activation during viewing of coherently moving random dots with that during viewing spatially and temporally comparable dynamic noise. Rates of reversal of coherent motion and coherent-motion velocities (5 versus 20 deg s-1) were also compared. Differences in local activation between conditions were analysed by statistical parametric mapping. Greater activation by coherent motion compared to noise was found in V5 and putative V3A, but not in V1. In addition there were foci of activation on the occipital ventral surface, the intraparietal sulcus, and superior temporal sulcus. Thus, coherent-motion information has distinctive effects in a number of extrastriate visual brain areas. The rate of motion reversal showed only weak effects in motion-sensitive areas. V1 was better activated by noise than by coherent motion, possibly reflecting activation of neurons with a wider range of motion selectivities. This activation was at a more anterior location in the comparison of noise with the faster velocity, suggesting that 20 deg s-1 is beyond the velocity range of the V1 representation of central visual field. These results support the use of motion-coherence tests for extrastriate as opposed to V1 function. However, sensitivity to motion coherence is not confined to V5, and may extend beyond the classically defined dorsal stream.

Virtual reality was used to sequentially present objects within a town square and to test recognition of object locations from the same viewpoint as presentation, or from a shifted viewpoint. A developmental amnesic case with focal bilateral hippocampal pathology showed a massive additional impairment when tested from the shifted viewpoint compared with a mild, list length-dependent, impairment when tested from the same viewpoint. While the same-view condition could be solved by visual pattern matching, the shifted-view condition requires a viewpoint independent representation or an equivalent mechanism for translating or rotating viewpoints in memory. The latter mechanism was indicated by control subjects' response latencies in the shifted-view condition, although the amnesic case is not impaired in tests of mental rotation of single objects. These results show that the human hippocampus supports viewpoint independence in spatial memory, and suggest that it does so by providing a mechanism for viewpoint manipulation in memory. In addition, they suggest an extremely sensitive test for human hippocampal damage, and hint at the nature of the hippocampal role in episodic recollection.

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First impressions of social traits, such as trustworthiness or dominance, are reliably perceived in faces, and despite their questionable validity they can have considerable real-world consequences. We sought to uncover the information driving such judgments, using an attribute-based approach. Attributes (physical facial features) were objectively measured from feature positions and colors in a database of highly variable "ambient" face photographs, and then used as input for a neural network to model factor dimensions (approachability, youthful-attractiveness, and dominance) thought to underlie social attributions. A linear model based on this approach was able to account for 58% of the variance in raters' impressions of previously unseen faces, and factor-attribute correlations could be used to rank attributes by their importance to each factor. Reversing this process, neural networks were then used to predict facial attributes and corresponding image properties from specific combinations of factor scores. In this way, the factors driving social trait impressions could be visualized as a series of computer-generated cartoon face-like images, depicting how attributes change along each dimension. This study shows that despite enormous variation in ambient images of faces, a substantial proportion of the variance in first impressions can be accounted for through linear changes in objectively defined features.