caa a22 4500 445294787 CHVBK 20180317142538.0 cr unu---uuuuu 170323e20100301xx s 000 0 eng 10.1007/s11571-009-9100-6 doi (NATIONALLICENCE)springer-10.1007/s11571-009-9100-6 Analysis of stability of neural network with inhibitory neurons [Elektronische Daten] [Yan Liu, Rubin Wang, Zhikang Zhang, Xianfa Jiao] Phase coding in a neural network composed of neural oscillators with inhibitory neurons was studied based on the theory of stochastic phase dynamics. We found that with increasing the coupling coefficients of inhibitory neural oscillators, the firing density in excitatory population transits to a critical state. In this case, when we increase the inhibitory coupling, the firing density will come into dynamic balance again and tend to a fixed value gradually. According to the phenomenon, in the paper we found parameter regions to exhibit those different population states, called dividing zones including flat fading zone, rapid fading zone and critical zone. Based on the dividing zones we can choose the number ratio between inhibitory neurons and excitatory neurons in the neural network, and estimate the coupling action of inhibitory population and excitatory population. Our research also shows that the balance value, enabling the firing density to reach the dynamic balance, does not depend on initial conditions. In addition, the critical value in critical state is only related to the number ratio between inhibitory neurons and excitatory neurons, but is independent of inhibitory coupling and excitatory coupling. Springer Science+Business Media B.V., 2009 Inhibitory neural population nationallicence Excitatory neural population nationallicence Average number density nationallicence Critical state nationallicence Liu Yan Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut Wang Rubin Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut Zhang Zhikang Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut Jiao Xianfa Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut Cognitive Neurodynamics Springer Netherlands 4/1(2010-03-01), 61-68 1871-4080 4:1<61 2010 4 11571 https://doi.org/10.1007/s11571-009-9100-6 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11571-009-9100-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Liu Yan Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Wang Rubin Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Zhang Zhikang Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Jiao Xianfa Institute for Cognitive Neurodynamics, East China University of Science and Technology, 200237, Shanghai, People's Republic of China aut NATIONALLICENCE 773 0- Cognitive Neurodynamics Springer Netherlands 4/1(2010-03-01), 61-68 1871-4080 4:1<61 2010 4 11571 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer