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Article overview
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What makes a neural code convex? | Carina Curto
; Elizabeth Gross
; Jack Jeffries
; Katherine Morrison
; Mohamed Omar
; Zvi Rosen
; Anne Shiu
; Nora Youngs
; | Date: |
1 Aug 2015 | Abstract: | Neural codes allow the brain to represent, process, and store information
about the world. Combinatorial codes, comprised of binary patterns of neural
activity, encode information via the collective behavior of populations of
neurons. A code is called convex if its codewords correspond to regions defined
by an arrangement of convex open sets in Euclidean space. Convex codes have
been observed experimentally in many brain areas, including sensory cortices
and the hippocampus, where neurons exhibit convex receptive fields. What makes
a neural code convex? That is, how can we tell from the intrinsic structure of
a code if there exists a corresponding arrangement of convex open sets? Using
tools from combinatorics and commutative algebra, we uncover a variety of
signatures of convex and non-convex codes. In many cases, these features are
sufficient to determine convexity, and reveal bounds on the minimal dimension
of the underlying Euclidean space. | Source: | arXiv, 1508.0150 | Services: | Forum | Review | PDF | Favorites |
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