Numerical Analysis of FitzHugh-Nagumo Neurons on Random Networks | Zendy

Yoshihito Oyama | Zendy; Tatsuo Yanagita | Zendy; Takashi Ichinomiya | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Numerical Analysis of FitzHugh-Nagumo Neurons on Random Networks

Author(s) -

Yoshihito Oyama,

Tatsuo Yanagita,

Takashi Ichinomiya

Publication year - 2006

Publication title -

progress of theoretical physics supplement

Language(s) - English

Resource type - Journals

ISSN - 0375-9687

DOI - 10.1143/ptps.161.389

Subject(s) - excitatory postsynaptic potential , inhibitory postsynaptic potential , statistical physics , rest (music) , physics , critical point (mathematics) , transition point , phase transition , mathematics , state (computer science) , neuroscience , computer science , mathematical analysis , algorithm , biology , mechanics , quantum mechanics , acoustics

We investigate a model of randomly copuled neurons. The elements are FitzHgh-Nagumo excitable neurons. The interactions between them are the mixture of excitatory and inhibitory. When all interactions are excitatory, a rest state is globally stable due to the excitability of neurons. Increasing the number of inhibitory connections, we observe the phase transition from the rest state to an oscillatory state. An analytical description for the critical point of the transition is obtained by means of random matrix theories for an infinite number of neurons, and the result is in good agreement with numerical simulation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research