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Function of biological asymmetrical neural networks

Authors: Naohiro Ishii; Ken-ichi Naka;

Function of biological asymmetrical neural networks

Abstract

Nonlinearity is an important factor in the biological neural networks. The motion perception and learning in them have been studied on the simplest type of nonlinearity, multiplication. In this paper, asymmetrical neural networks with nonlinear function, are studied in the biological neural networks. Then, the nonlinear higher-order system is discussed in the neural networks. The second-order system in the nonlinear biological system is shown to play an important role in the movement detection. From the theoretical analysis, it is shown that the third-order one does not contribute to the detection and the fourth-order one becomes to the second-order in the movement detection function. Hassenstein and Reichardt network(1956) and Barlow and Levick network(1965) of movements are similar to the asymmetrical network developed here. To make clear the difference among these asymmetrical networks, we derive α-equation of movement, which shows the detection of movement. During the movement, we also can derive the movement equation, which implies the movement direction regardless of the parameter α.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
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