Development of the Spatial Representation System in the Rat

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Science  18 Jun 2010:
Vol. 328, Issue 5985, pp. 1576-1580
DOI: 10.1126/science.1188210

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The Space in Your Head

Space, and events associated with places and spaces, are represented in the brain by a circuitry made of place cells, head direction cells, grid cells, and border cells. These cell types form a collective dynamic representation of our position as we move through the environment. How this representation is formed has remained a mystery. Is it acquired, or are we born with the ability to represent external space (see the Perspective by Palmer and Lynch)? Langston et al. (p. 1576) and Wills et al. (p. 1573) investigated the early development of spatial activity in the hippocampal formation and the entorhinal cortex of rat pups when they first began to explore their environment. Rudiments of place cells, head direction cells, and grid cells already existed when the pups made their first movements out of the nest. A neural representation of external space at this early time points to strong innate components for perception of space. These findings provide experimental support for Kant's 200-year-old concept of space as an a priori faculty of the mind.


In the adult brain, space and orientation are represented by an elaborate hippocampal-parahippocampal circuit consisting of head-direction cells, place cells, and grid cells. We report that a rudimentary map of space is already present when 2½-week-old rat pups explore an open environment outside the nest for the first time. Head-direction cells in the pre- and parasubiculum have adultlike properties from the beginning. Place and grid cells are also present but evolve more gradually. Grid cells show the slowest development. The gradual refinement of the spatial representation is accompanied by an increase in network synchrony among entorhinal stellate cells. The presence of adultlike directional signals at the onset of navigation raises the possibility that such signals are instrumental in setting up networks for place and grid representation.

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