A generative modeling approach to connectivity-Electrical conduction in vascular networks

Research output: Contribution to journalJournal article

Standard

A generative modeling approach to connectivity-Electrical conduction in vascular networks. / Hald, Bjørn Olav.

In: Journal of Theoretical Biology, Vol. 399, 21.06.2016, p. 1-12.

Research output: Contribution to journalJournal article

Harvard

Hald, BO 2016, 'A generative modeling approach to connectivity-Electrical conduction in vascular networks', Journal of Theoretical Biology, vol. 399, pp. 1-12. https://doi.org/10.1016/j.jtbi.2016.03.032

APA

Hald, B. O. (2016). A generative modeling approach to connectivity-Electrical conduction in vascular networks. Journal of Theoretical Biology, 399, 1-12. https://doi.org/10.1016/j.jtbi.2016.03.032

Vancouver

Hald BO. A generative modeling approach to connectivity-Electrical conduction in vascular networks. Journal of Theoretical Biology. 2016 Jun 21;399:1-12. https://doi.org/10.1016/j.jtbi.2016.03.032

Author

Hald, Bjørn Olav. / A generative modeling approach to connectivity-Electrical conduction in vascular networks. In: Journal of Theoretical Biology. 2016 ; Vol. 399. pp. 1-12.

Bibtex

@article{0107161bbf1243d2acb18fa638857d96,
title = "A generative modeling approach to connectivity-Electrical conduction in vascular networks",
abstract = "The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel generative approach to connectivity based on the observation that biological organization is hierarchical and composed of a limited set of building blocks, i.e. a vascular network consists of blood vessels which in turn are composed by one or more cell types. Fast electrical communication is crucial to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub-networks are more sensitive to electrical perturbations. In summary, the capacity for electrical signaling in microvascular networks is strongly shaped by the morphology and connectivity of vascular (particularly endothelial) cells. While the presented software can be used by itself or as a starting point for more sophisticated models of vascular dynamics, the generative approach can be applied to other biological systems, e.g. nervous tissue, the lymphatics, or the biliary system.",
keywords = "Faculty of Health and Medical Sciences, Vascular Resistance, conducted vasomotor responses, Computational Biology",
author = "Hald, {Bj{\o}rn Olav}",
year = "2016",
month = "6",
day = "21",
doi = "10.1016/j.jtbi.2016.03.032",
language = "English",
volume = "399",
pages = "1--12",
journal = "Journal of Theoretical Biology",
issn = "0022-5193",
publisher = "Academic Press",

}

RIS

TY - JOUR

T1 - A generative modeling approach to connectivity-Electrical conduction in vascular networks

AU - Hald, Bjørn Olav

PY - 2016/6/21

Y1 - 2016/6/21

N2 - The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel generative approach to connectivity based on the observation that biological organization is hierarchical and composed of a limited set of building blocks, i.e. a vascular network consists of blood vessels which in turn are composed by one or more cell types. Fast electrical communication is crucial to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub-networks are more sensitive to electrical perturbations. In summary, the capacity for electrical signaling in microvascular networks is strongly shaped by the morphology and connectivity of vascular (particularly endothelial) cells. While the presented software can be used by itself or as a starting point for more sophisticated models of vascular dynamics, the generative approach can be applied to other biological systems, e.g. nervous tissue, the lymphatics, or the biliary system.

AB - The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel generative approach to connectivity based on the observation that biological organization is hierarchical and composed of a limited set of building blocks, i.e. a vascular network consists of blood vessels which in turn are composed by one or more cell types. Fast electrical communication is crucial to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub-networks are more sensitive to electrical perturbations. In summary, the capacity for electrical signaling in microvascular networks is strongly shaped by the morphology and connectivity of vascular (particularly endothelial) cells. While the presented software can be used by itself or as a starting point for more sophisticated models of vascular dynamics, the generative approach can be applied to other biological systems, e.g. nervous tissue, the lymphatics, or the biliary system.

KW - Faculty of Health and Medical Sciences

KW - Vascular Resistance

KW - conducted vasomotor responses

KW - Computational Biology

U2 - 10.1016/j.jtbi.2016.03.032

DO - 10.1016/j.jtbi.2016.03.032

M3 - Journal article

VL - 399

SP - 1

EP - 12

JO - Journal of Theoretical Biology

JF - Journal of Theoretical Biology

SN - 0022-5193

ER -

ID: 164160878