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Grid cells - Reading the neural code for space

Martin Stemmler (LMU), Alexander Mathis (Harvard) and Andreas V.M. Herz (GSN Faculty member) propose a comprehensive mathematical theory in grid cell research


(source: LMU press releases)

The cognitive map for spatial navigation is thought to rely on grid cells. Scientists at LMU and Harvard University have now put forward a mathematical theory that explains key grid-cell features and how these give rise to a neural metric for space.

The theory proposed by Stemmler and colleagues goes far beyond previous schemes in that the decoded quantity – the animal’s position – is not a circular variable. “Animals move on two-dimensional surfaces or in three-dimensional spaces, so their position is not a one-dimensional variable either. In addition, population-vector averages across different grid scales need to be combined,” explains Andreas Herz. Yet, the overall conceptual similarity of the new scheme to conventional population-vector decoding suggests that there exist overarching computational principles that operate throughout the brain. “This raises hopes that, in spite of the brain’s complexity, a thorough understanding of the neural basis of many cognitive processes is possible.”

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