Abstract | ||
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In this paper, the intrinsic relationship between energy consumption and neural information coding in local neural networks of the cerebral cortex is studied. The energy functions of a variety of membrane potential are obtained under some conditions of mutual coupling at both the supra-threshold and the sub-threshold states in a neural population. These energy functions can accurately reproduce excitatory postsynaptic potentials (EPSP), inhibitory postsynaptic potentials (IPSP), as well as an action potential, found in the experiments of neuro-electrophysiology. Recently, it has been proved that signal transmission and neuronal energetic demands are tightly coupled to information coding in the cerebral cortex in functional magnetic resonance imaging (fMRI) experiments. Therefore, the analytic results obtained in this paper show that the principle of energy coding is quite fundamental and is beneficial to the study of the important scientific problem as how the brain performs coding at the level of local neural networks. |
Year | DOI | Venue |
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2009 | 10.1016/j.neucom.2009.02.022 | Neurocomputing |
Keywords | Field | DocType |
coupling of neural energy,energy consumption,neural information,local neural network,energy coding,excitatory postsynaptic potential,action potential,neural oscillator,local activity,energy function,cerebral cortex,hamiltonian function,inhibitory postsynaptic potential,neural population,membrane potential,neural network | Population,Transmission (telecommunications),Biological system,Pattern recognition,Functional magnetic resonance imaging,Neural coding,Postsynaptic potential,Excitatory postsynaptic potential,Inhibitory postsynaptic potential,Artificial intelligence,Neural decoding,Mathematics | Journal |
Volume | Issue | ISSN |
73 | 1-3 | Neurocomputing |
Citations | PageRank | References |
7 | 0.78 | 5 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Rubin Wang | 1 | 141 | 25.54 |
Zhikang Zhang | 2 | 66 | 11.91 |
Guanrong Chen | 3 | 12378 | 1130.81 |