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A Computational Model of Neuro-Glio-Vascular Loop Interactions

We present a computational, biophysical model of neuron-astrocyte-vessel interaction. Unlike other cells, neurons convey “hunger” signals to the vascular network via an intervening layer of glial cells (astrocytes); vessels dilate and release glucose which fuels neuronal firing. Existing computation...

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Detalles Bibliográficos
Autores principales: Chander, Bankim Subhash, Chakravarthy, V. Srinivasa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502400/
https://www.ncbi.nlm.nih.gov/pubmed/23185276
http://dx.doi.org/10.1371/journal.pone.0048802
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author Chander, Bankim Subhash
Chakravarthy, V. Srinivasa
author_facet Chander, Bankim Subhash
Chakravarthy, V. Srinivasa
author_sort Chander, Bankim Subhash
collection PubMed
description We present a computational, biophysical model of neuron-astrocyte-vessel interaction. Unlike other cells, neurons convey “hunger” signals to the vascular network via an intervening layer of glial cells (astrocytes); vessels dilate and release glucose which fuels neuronal firing. Existing computational models focus on only parts of this loop (neuron→astrocyte→vessel→neuron), whereas the proposed model describes the entire loop. Neuronal firing causes release of a neurotransmitter like glutamate which triggers release of vasodilator by astrocytes via a cascade of biochemical events. Vasodilators released from astrocytic endfeet cause blood vessels to dilate and release glucose into the interstitium, part of which is taken up by the astrocyticendfeet. Glucose is converted into lactate in the astrocyte and transported into the neuron. Glucose from the interstitium and lactate (produced from glucose) influx from astrocyte are converted into ATP in the neuron. Neuronal ATP is used to drive the Na(+)/K(+)ATPase pumps, which maintain ionic gradients necessary for neuronal firing. When placed in the metabolic loop, the neuron exhibits sustained firing only when the stimulation current is more than a minimum threshold. For various combinations of initial neuronal [ATP] and external current, the neuron exhibits a variety of firing patterns including sustained firing, firing after an initial pause, burst firing etc. Neurovascular interactions under conditions of constricted vessels are also studied. Most models of cerebral circulation describe neurovascular interactions exclusively in the “forward” neuron→vessel direction. The proposed model indicates possibility of “reverse” influence also, with vasomotion rhythms influencing neural firing patterns. Another idea that emerges out of the proposed work is that brain's computations may be more comprehensively understood in terms of neuro-glial-vascular dynamics and not in terms of neural firing alone.
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spelling pubmed-35024002012-11-26 A Computational Model of Neuro-Glio-Vascular Loop Interactions Chander, Bankim Subhash Chakravarthy, V. Srinivasa PLoS One Research Article We present a computational, biophysical model of neuron-astrocyte-vessel interaction. Unlike other cells, neurons convey “hunger” signals to the vascular network via an intervening layer of glial cells (astrocytes); vessels dilate and release glucose which fuels neuronal firing. Existing computational models focus on only parts of this loop (neuron→astrocyte→vessel→neuron), whereas the proposed model describes the entire loop. Neuronal firing causes release of a neurotransmitter like glutamate which triggers release of vasodilator by astrocytes via a cascade of biochemical events. Vasodilators released from astrocytic endfeet cause blood vessels to dilate and release glucose into the interstitium, part of which is taken up by the astrocyticendfeet. Glucose is converted into lactate in the astrocyte and transported into the neuron. Glucose from the interstitium and lactate (produced from glucose) influx from astrocyte are converted into ATP in the neuron. Neuronal ATP is used to drive the Na(+)/K(+)ATPase pumps, which maintain ionic gradients necessary for neuronal firing. When placed in the metabolic loop, the neuron exhibits sustained firing only when the stimulation current is more than a minimum threshold. For various combinations of initial neuronal [ATP] and external current, the neuron exhibits a variety of firing patterns including sustained firing, firing after an initial pause, burst firing etc. Neurovascular interactions under conditions of constricted vessels are also studied. Most models of cerebral circulation describe neurovascular interactions exclusively in the “forward” neuron→vessel direction. The proposed model indicates possibility of “reverse” influence also, with vasomotion rhythms influencing neural firing patterns. Another idea that emerges out of the proposed work is that brain's computations may be more comprehensively understood in terms of neuro-glial-vascular dynamics and not in terms of neural firing alone. Public Library of Science 2012-11-20 /pmc/articles/PMC3502400/ /pubmed/23185276 http://dx.doi.org/10.1371/journal.pone.0048802 Text en © 2012 Chander, Chakravarthy http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Chander, Bankim Subhash
Chakravarthy, V. Srinivasa
A Computational Model of Neuro-Glio-Vascular Loop Interactions
title A Computational Model of Neuro-Glio-Vascular Loop Interactions
title_full A Computational Model of Neuro-Glio-Vascular Loop Interactions
title_fullStr A Computational Model of Neuro-Glio-Vascular Loop Interactions
title_full_unstemmed A Computational Model of Neuro-Glio-Vascular Loop Interactions
title_short A Computational Model of Neuro-Glio-Vascular Loop Interactions
title_sort computational model of neuro-glio-vascular loop interactions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502400/
https://www.ncbi.nlm.nih.gov/pubmed/23185276
http://dx.doi.org/10.1371/journal.pone.0048802
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