title: Energy function and energy evolution on neuronal populations.
abstract: Based on the principle of energy coding, an energy function of a variety of electric potentials of a neural population in cerebral cortex is formulated. The energy function is used to describe the energy evolution of the neuronal population with time and the coupled relationship between neurons at the subthreshold and the suprathreshold states. The Hamiltonian motion equation with the membrane potential is obtained from the neuroelectrophysiological data contaminated by Gaussian white noise. The results of this research show that the mean membrane potential is the exact solution of the motion equation of the membrane potential developed in a previously published paper. It also shows that the Hamiltonian energy function derived in this brief is not only correct but also effective. Particularly, based on the principle of energy coding, an interesting finding is that in some subsets of neurons, firing action potentials at the suprathreshold and some others simultaneously perform activities at the subthreshold level in neural ensembles. Notably, this kind of coupling has not been found in other models of biological neural networks.
authors.affiliation: Institute for Brain Information Processing and Cognitive Neurodynamics, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, P R China. rbwang@163.com
authors.forename: Rubin
authors.initials: R
authors.lastname: Wang
authors.forename: Zhikang
authors.initials: Z
authors.lastname: Zhang
authors.forename: Guanrong
authors.initials: G
authors.lastname: Chen
mesh_terms: D000818:Animals; D005075:Biological Evolution; D002540:Cerebral Cortex / Q000166:cytology; D006801:Humans; D008564:Membrane Potentials / Q000502:physiology*; D008959:Models, Neurological; D009474:Neurons / Q000378:metabolism*