Response of an Excitatory-Inhibitory Neural Network to External Stimulation: An Application to Image Segmentation

Details Response of an Excitatory-Inhibitory Neural Network to External Stimulation: An Application to Image Segmentation Response of an Excitatory-Inhibitory Neural Network to External Stimulation: An Application to Image Segmentation

1998-11-29

arxiv.org/abs/cond-mat/9811403v1

revised version in Phys. Rev. E 65 (2002) 046112.

Physics

Condensed Matter

Disordered Systems and Neural Networks

8 pages, latex, 5 figures

Scientific paper

10.1103/PhysRevE.65.046112

Neural network models comprising elements which have exclusively excitatory or inhibitory synapses are capable of a wide range of dynamic behavior, including chaos. In this paper, a simple excitatory-inhibitory neural pair, which forms the building block of larger networks, is subjected to external stimulation. The response shows transition between various types of dynamics, depending upon the magnitude of the stimulus. Coupling such pairs over a local neighborhood in a two-dimensional plane, the resultant network can achieve a satisfactory segmentation of an image into ``object'' and ``background''. Results for synthetic and and ``real-life'' images are given.

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