NDLI: Formation and variability of orientation preference maps in visual cortex: an approach based on normalized Gaussian arrays

Content Provider	IEEE Xplore Digital Library
Author	Jiann-Ming Wu Zheng-Han Lin Cheng-Yuang Liou
Copyright Year	2005
Description	Author affiliation: Dept. of Appl. Math., National Dong Hwa Univ., Hualien, Taiwan (Jiann-Ming Wu; Zheng-Han Lin)
Abstract	This work explores formation and variability of orientation preference maps in visual cortex based on normalized Gaussian arrays. An orientation preference map, which has been measured to sketch the orientation preference of neighboring neurons in visual cortex, is emulated by a network of weighted normalized Gaussian arrays. Here the orientation preference map is represented by a set of paired data, each comprising a relative neuron location and the relevant orientation preference, and the mapping structure from the location on a two-dimensional lattice to the orientation preference is then realized by learning a network of normalized Gaussian arrays subject to the paired data. As a result, varieties of mapping structures of different species are essentially characterized by the array number in a network. For example, the icecube structure can be well emulated by using one Gaussian array, the pinwheels structure, that looks like a superposition of two cross icecubes, can be characterized by a network of two Gaussian arrays, and the salt&pepper structure is simply a result of a null Gaussian array, of which the width of each Gaussian unit is set sufficiently large.
Sponsorship	Nat. Sci. Council, Taiwan Minist. of Educ., Taiwan IEEE Circuits and Syst. Soc. IEEE, Taipei Chapter IEEE Circuits and Syst. Soc., Taipei and Tainan Chapters IEEE Computational Intelligence Soc., Taipei Chapter Nat. Chiao Tung Univ., Taiwan The Pazmany Peter Catholic Univ., Budapest
Starting Page	5
Ending Page	8
File Size	1356153
Page Count	4
File Format	PDF
ISBN	0780391853
DOI	10.1109/CNNA.2005.1543147
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-05-28
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Lattices Cats Size measurement Mathematics Optical imaging Rats Computer science Data engineering Supervised learning
Content Type	Text
Resource Type	Article

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