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Journal of Vibration Testing and System Dynamics

C. Steve Suh (editor), Pawel Olejnik (editor),

Xianguo Tuo (editor)

Pawel Olejnik (editor)

Lodz University of Technology, Poland


C. Steve Suh (editor)

Texas A&M University, USA


Xiangguo Tuo (editor)

Sichuan University of Science and Engineering, China


An Energy Based Description of Complex Brain Network Dynamics

Journal of Vibration Testing and System Dynamics 8(2) (2024) 235--248 | DOI:10.5890/JVTSD.2024.06.006

Chun-Lin Yang, Nandan Shettigar, C. Steve Suh

Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123, USA

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Biophysiological measurements are inadequate in making explicit the various properties of the brain at the network level for the reasons that these properties are complex functions of the electrochemical gradient and the cumulative area of triggered ion channels. Neuron dynamics, synaptic dynamics, and neural electrophysiological coupling have been considered in [1].~This study continues the work presented in [1] and considers biophysiological (local) and brain network (global) dynamics. The general framework for dynamic complex networks [2] is followed to describe brain network dynamics in this study. At the local level, individual neuron dynamics is defined using energy by considering each neuron as a type of biological battery. The potential energy is the charge of ions a neuron holds which is the membrane potential. The kinetic energy is the change of ion charge in time introduced by the ion flux across the membrane that induces the change of membrane potential. Degree-of-couplings, DOC k and DOC J, are indicators of the coupling strength of connected neurons. Since the energies of individual neurons in the network are normally distributed, brain network dynamics can be described by information entropy as a function of the probability of the individual neuron energies at the global level. Information entropy is also used to measure the degree of synchronization of the firing of action potential.


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