ArticleScientific reports2016
Cable energy function of cortical axons.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Energy dependence of synchronization mode transitions in the delay-coupled FitzHugh-Nagumo system driven by chaotic activity.Cognitive neurodynamics · 2024Article
- Long-range white matter fibres and post-stroke verbal and non-verbal cognition.Brain communications · 2024Article
- Long-range connections damage in white matter hyperintensities affects information processing speed.Brain communications · 2024Article
- Thalamic Neuron Resilience during Osmotic Demyelination Syndrome (ODS) Is Revealed by Primary Cilium Outgrowth and ADP-ribosylation factor-like protein 13B Labeling in Axon Initial Segment.International journal of molecular sciences · 2023Article
- Axonal energy metabolism, and the effects in aging and neurodegenerative diseases.Molecular neurodegeneration · 2023Review
- Diabetes, brain health, and treatment gains in post-stroke aphasia.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Resilience of compound action potential peaks to high-frequency firing in the mouse optic nerve.Physiological reports · 2023Article
- Comparing the brain-behaviour relationship in acute and chronic stroke aphasia.Brain communications · 2023Article
- A frequency-amplitude coordinator and its optimal energy consumption for biological oscillators.Nature communications · 2021Article
- Article
- Intermittent Failure of Spike Propagation in Primary Afferent Neurons during Tactile Stimulation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Long-range fibre damage in small vessel brain disease affects aphasia severity.Brain : a journal of neurology · 2019Article
- Automated 3D Axonal Morphometry of White Matter.Scientific reports · 2019Article
- Function and energy consumption constrain neuronal biophysics in a canonical computation: Coincidence detection.PLoS computational biology · 2018Article
- Synaptic E-I Balance Underlies Efficient Neural Coding.Frontiers in neuroscience · 2018Review
- Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network.Frontiers in cellular neuroscience · 2018Article
- Branching morphology determines signal propagation dynamics in neurons.Scientific reports · 2017Article
- Dendritic Properties Control Energy Efficiency of Action Potentials in Cortical Pyramidal Cells.Frontiers in cellular neuroscience · 2017Article
- Metabolic Energy of Action Potentials Modulated by Spike Frequency Adaptation.Frontiers in neuroscience · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
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