Optimizing Cortical Mappings

Geoffrey J. Goodhill; Steven Finch; Terrence J. Sejnowski

Optimizing Cortical Mappings

Geoffrey J. Goodhill, Steven Finch, Terrence J. Sejnowski

Research output: Contribution to conference › Paper › peer-review

Abstract

"Topographic" mappings occur frequently in the brain. A popular approach to understanding the structure of such mappings is to map points representing input features in a space of a few dimensions to points in a 2 dimensional space using some selforganizing algorithm. We argue that a more general approach may be useful, where simUarities between features are not constrained to be geometric distances, and the objective function for topographic matching is chosen explicitly rather than being specified implicitly by the self-organizing algorithm. We investigate analytically an example of this more general approach applied to the structure of interdigitated mappings, such as the pattern of ocular dorninance columns in primary visual cortex.

Original language	English
Pages	330-336
Number of pages	7
State	Published - 1995
Event	8th International Conference on Neural Information Processing Systems, NIPS 1995 - Denver, United States Duration: Nov 27 1995 → Dec 2 1995

Conference

Conference	8th International Conference on Neural Information Processing Systems, NIPS 1995
Country/Territory	United States
City	Denver
Period	11/27/95 → 12/2/95

Cite this

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title = "Optimizing Cortical Mappings",

abstract = "{"}Topographic{"} mappings occur frequently in the brain. A popular approach to understanding the structure of such mappings is to map points representing input features in a space of a few dimensions to points in a 2 dimensional space using some selforganizing algorithm. We argue that a more general approach may be useful, where simUarities between features are not constrained to be geometric distances, and the objective function for topographic matching is chosen explicitly rather than being specified implicitly by the self-organizing algorithm. We investigate analytically an example of this more general approach applied to the structure of interdigitated mappings, such as the pattern of ocular dorninance columns in primary visual cortex.",

author = "Goodhill, {Geoffrey J.} and Steven Finch and Sejnowski, {Terrence J.}",

note = "Funding Information: We thank Gary Blasdel, Peter Dayan and Paul Viola for stimulating discussions. Publisher Copyright: {\textcopyright} NIPS 1995: Proceedings of the 8th International Conference on Neural Information Processing Systems. All rights reserved.; 8th International Conference on Neural Information Processing Systems, NIPS 1995 ; Conference date: 27-11-1995 Through 02-12-1995",

year = "1995",

language = "English",

pages = "330--336",

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TY - CONF

T1 - Optimizing Cortical Mappings

AU - Goodhill, Geoffrey J.

AU - Finch, Steven

AU - Sejnowski, Terrence J.

N1 - Funding Information: We thank Gary Blasdel, Peter Dayan and Paul Viola for stimulating discussions. Publisher Copyright: © NIPS 1995: Proceedings of the 8th International Conference on Neural Information Processing Systems. All rights reserved.

PY - 1995

Y1 - 1995

N2 - "Topographic" mappings occur frequently in the brain. A popular approach to understanding the structure of such mappings is to map points representing input features in a space of a few dimensions to points in a 2 dimensional space using some selforganizing algorithm. We argue that a more general approach may be useful, where simUarities between features are not constrained to be geometric distances, and the objective function for topographic matching is chosen explicitly rather than being specified implicitly by the self-organizing algorithm. We investigate analytically an example of this more general approach applied to the structure of interdigitated mappings, such as the pattern of ocular dorninance columns in primary visual cortex.

AB - "Topographic" mappings occur frequently in the brain. A popular approach to understanding the structure of such mappings is to map points representing input features in a space of a few dimensions to points in a 2 dimensional space using some selforganizing algorithm. We argue that a more general approach may be useful, where simUarities between features are not constrained to be geometric distances, and the objective function for topographic matching is chosen explicitly rather than being specified implicitly by the self-organizing algorithm. We investigate analytically an example of this more general approach applied to the structure of interdigitated mappings, such as the pattern of ocular dorninance columns in primary visual cortex.

UR - http://www.scopus.com/inward/record.url?scp=85156226543&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85156226543

SP - 330

EP - 336

T2 - 8th International Conference on Neural Information Processing Systems, NIPS 1995

Y2 - 27 November 1995 through 2 December 1995

ER -

Optimizing Cortical Mappings

Abstract

Conference

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