ArticlePLoS computational biology2010
Action potential energy efficiency varies among neuron types in vertebrates and invertebrates.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers.
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Who cites it
123 citing papers in PubMed, 275 citations in OpenAlex.
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- Predictive coding is a consequence of energy efficiency in recurrent neural networks.Patterns (New York, N.Y.) · 2022Article
- Energy-efficient network activity from disparate circuit parameters.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
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- Morphological Determinants of Cell-to-Cell Variations in Action Potential Dynamics in Substantia Nigra Dopaminergic Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
63 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
Abstract
The initiation and propagation of action potentials (APs) places high demands on the energetic resources of neural tissue. Each AP forces ATP-driven ion pumps to work harder to restore the ionic concentration gradients, thus consuming more energy. Here, we ask whether the ionic currents underlying the AP can be predicted theoretically from the principle of minimum energy consumption. A long-held supposition that APs are energetically wasteful, based on theoretical analysis of the squid giant axon AP, has recently been overturned by studies that measured the currents contributing to the AP in several mammalian neurons. In the single compartment models studied here, AP energy consumption varies greatly among vertebrate and invertebrate neurons, with several mammalian neuron models using close to the capacitive minimum of energy needed. Strikingly, energy consumption can increase by more than ten-fold simply by changing the overlap of the Na(+) and K(+) currents during the AP without changing the APs shape. As a consequence, the height and width of the AP are poor predictors of energy consumption. In the Hodgkin-Huxley model of the squid axon, optimizing the kinetics or number of Na(+) and K(+) channels can whittle down the number of ATP molecules needed for each AP by a factor of four. In contrast to the squid AP, the temporal profile of the currents underlying APs of some mammalian neurons are nearly perfectly matched to the optimized properties of ionic conductances so as to minimize the ATP cost.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.