title: Cable energy function of cortical axons.
abstract: Accurate estimation of action potential (AP)-related metabolic cost is essential for understanding energetic constraints on brain connections and signaling processes. Most previous energy estimates of the AP were obtained using the Na(+)-counting method, which seriously limits accurate assessment of metabolic cost of ionic currents that underlie AP conduction along the axon. Here, we first derive a full cable energy function for cortical axons based on classic Hodgkin-Huxley (HH) neuronal equations and then apply the cable energy function to precisely estimate the energy consumption of AP conduction along axons with different geometric shapes. Our analytical approach predicts an inhomogeneous distribution of metabolic cost along an axon with either uniformly or nonuniformly distributed ion channels. The results show that the Na(+)-counting method severely underestimates energy cost in the cable model by 20-70%. AP propagation along axons that differ in length may require over 15% more energy per unit of axon area than that required by a point model. However, actual energy cost can vary greatly depending on axonal branching complexity, ion channel density distributions, and AP conduction states. We also infer that the metabolic rate (i.e. energy consumption rate) of cortical axonal branches as a function of spatial volume exhibits a 3/4 power law relationship.
authors.affiliation: School of Life Science and the Collaborative Innovation Center for Brain Science, Center for Computational Systems Biology, Fudan University, Shanghai 200433, China.
authors.forename: Huiwen
authors.initials: H
authors.lastname: Ju
authors.affiliation: Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA.
authors.forename: Michael L
authors.initials: ML
authors.lastname: Hines
authors.affiliation: School of Life Science and the Collaborative Innovation Center for Brain Science, Center for Computational Systems Biology, Fudan University, Shanghai 200433, China.
authors.forename: Yuguo
authors.initials: Y
authors.lastname: Yu
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D001369:Axons / Q000502:physiology*; D002540:Cerebral Cortex / Q000166:cytology; D003198:Computer Simulation; D004734:Energy Metabolism; D008959:Models, Neurological