Volume 128, Number 6, December 2019
|Number of page(s)||7|
|Published online||04 February 2020|
Information retrieval from modified Kuramoto network by resonant synchronization
School of Physics and Information Technology, Shaanxi Normal University - Xi'an 710061, PRC
Received: 9 July 2019
Accepted: 3 January 2020
A collective behavior of resonant synchronization (RS) in an inhomogeneous network is investigated and its function to retrieve information from encoding networks is proposed based on the RS mechanism. We use modified Kuramoto phase oscillators to simulate normal neurons in self-oscillation state, and investigate the collective responses of a fully connected neuronal network to the stimulus signals when the network is in a critical state just below the synchronization threshold. The stimulus driving on one node at resonant frequencies can stimulate the unsynchronized rotators across the network into collective synchronized states locked to similar frequencies, and thus recover the memorized locations through the synchronized patterns related to the predetermined frequency distributions among the oscillators. This model suggests a potential mechanism to explain how brain stores and retrieves information from resonant synchronization patterns emerging from an inhomogeneous critical neuronal network stimulated by the resonant external driving.
PACS: 05.45.Xt – Synchronization; coupled oscillators / 05.45.-a – Nonlinear dynamics and chaos
© EPLA, 2020
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