Spatial Cognition and the Brain
Article first published online: 3 APR 2008
DOI: 10.1196/annals.1440.002
2008 New York Academy of Sciences
Issue

Annals of the New York Academy of Sciences
Volume 1124, The Year in Cognitive Neuroscience 2008 pages 77–97, March 2008
Additional Information
How to Cite
Burgess, N. (2008), Spatial Cognition and the Brain. Annals of the New York Academy of Sciences, 1124: 77–97. doi: 10.1196/annals.1440.002
Publication History
- Issue published online: 3 APR 2008
- Article first published online: 3 APR 2008
- Abstract
- Article
- References
- Cited By
Keywords:
- parietal;
- hippocampal;
- striatal;
- fMRI;
- place cells;
- grid cells;
- allocentric;
- egocentric;
- computational modeling
Recent advances in the understanding of spatial cognition are reviewed, focusing on memory for locations in large-scale space and on those advances inspired by single-unit recording and lesion studies in animals. Spatial memory appears to be supported by multiple parallel representations, including egocentric and allocentric representations, and those updated to accommodate self-motion. The effects of these representations can be dissociated behaviorally, developmentally, and in terms of their neural bases. It is now becoming possible to construct a mechanistic neural-level model of at least some aspects of spatial memory and imagery, with the hippocampus and medial temporal lobe providing allocentric environmental representations, the parietal lobe egocentric representations, and the retrosplenial cortex and parieto-occipital sulcus allowing both types of representation to interact. Insights from this model include a common mechanism for the construction of spatial scenes in the service of both imagery and episodic retrieval and a role for the remainder of Papez's circuit in orienting the viewpoint used. In addition, it appears that hippocampal and striatal systems process different aspects of environmental layout (boundaries and local landmarks, respectively) and do so using different learning rules (incidental learning and associative reinforcement, respectively).

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