ArticlePLoS computational biology2014
Consequences of converting graded to action potentials upon neural information coding and energy efficiency.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- KThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
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- Ladder-based resistance training with the progression of training load altered the tibial nerve ultrastructure and muscle fiber area without altering the morphology of the postsynaptic compartment.Frontiers in physiology · 2024Article
- A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments.Neuroscience and biobehavioral reviews · 2023Review
- The computational power of the human brain.Frontiers in cellular neuroscience · 2023Review
- The sciatic and radial nerves seem to adapt similarly to different ladder-based resistance training protocols.Experimental brain research · 2022Article
- Review
- Ladder-based resistance training elicited similar ultrastructural adjustments in forelimb and hindlimb peripheral nerves of young adult Wistar rats.Experimental brain research · 2021Article
- High-Frequency Synchronization Improves Firing Rate Contrast and Information Transmission Efficiency in E/I Neuronal Networks.Neural plasticity · 2020Article
- The Relationship between Sparseness and Energy Consumption of Neural Networks.Neural plasticity · 2020Article
- Upper Limit on the Thermodynamic Information Content of an Action Potential.Frontiers in computational neuroscience · 2020Article
- Contrast sensitivity and behavioural evidence for lateral inhibition in octopus.Biology letters · 2019Article
- Modulation of voltage-dependent K+ conductances in photoreceptors trades off investment in contrast gain for bandwidth.PLoS computational biology · 2018Article
- Article
- Dendritic Properties Control Energy Efficiency of Action Potentials in Cortical Pyramidal Cells.Frontiers in cellular neuroscience · 2017Article
- Article
- Determine Neuronal Tuning Curves by Exploring Optimum Firing Rate Distribution for Information Efficiency.Frontiers in computational neuroscience · 2017Article
- A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee.PLoS computational biology · 2016Article
- Metabolic Energy of Action Potentials Modulated by Spike Frequency Adaptation.Frontiers in neuroscience · 2016Article
- Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.eLife · 2015Article
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3 authors.
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Abstract
Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na(+) and K(+) channels, with generator potential and graded potential models lacking voltage-gated Na(+) channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na(+) channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a 'footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by ∼50% in generator potentials, to ∼3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.
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