Self-organized cortical map formation by guiding connections

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Gaussian distribution
neural nets
self-organising feature maps
function maximization
guiding connections
learning modified pattern center location
neural growth cone guidance
neuromorphic silicon systems
self-organized cortical map formation
source neuron Gaussian connection pattern
source/target array self-organizing connections
topographic feature maps
visual cortex
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Lam, Stanley Y.M.
Shi, Bertram E.
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We describe an algorithm for self-organizing connections from a source array to a target array of neurons that is inspired by neural growth cone guidance. Each source neuron projects a Gaussian pattern of connections to the target layer. Learning modifies the pattern center location. The small number of parameters required to specify connectivity has enabled this algorithm's implementation in a neuromorphic silicon system. We demonstrate that this algorithm can lead to topographic feature maps similar to those observed in the visual cortex, and characterize its operation as function maximization, which connects this approach with other models of cortical map formation.

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2005-05-23
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2023-05-17T03:01:23.000
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Copyright IEEE 2005. Reprinted from: Lam, S.Y.M.; Shi, B.E.; Boahen, K.A., "Self-organized cortical map formation by guiding connections," Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on , vol., no., pp. 5230-5233 Vol. 5, 23-26 May 2005 URL: http://proxy.library.upenn.edu:2994/stamp/stamp.jsp?arnumber=1465814&isnumber=31469 This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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