title: Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population.
abstract: This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance.
authors: Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors: Xile
authors: X
authors: Wei
authors: Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors: Danhong
authors: D
authors: Zhang
authors: School of Informational Technology and Engineering, Tianjin University of Technology and Education, Tianjin 300222, China.
authors: Meili
authors: M
authors: Lu
authors: Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors: Jiang
authors: J
authors: Wang
authors: Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
authors: Haitao
authors: H
authors: Yu
authors: School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222, China.
authors: Yanqiu
authors: Y
authors: Che
mesh_terms: D000818:Animals; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*