Spatial modeling algorithms for reactions and transport in biological cells DOI Creative Commons
Emmet A. Francis, Justin G. Laughlin, Jørgen S. Dokken

et al.

Nature Computational Science, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 19, 2024

Language: Английский

A Splitting, Discontinuous Galerkin Solver for the Cell-by-Cell Electroneutral Nernst–Planck Framework DOI
Ada J. Ellingsrud, Pietro Benedusi, Miroslav Kuchta

et al.

SIAM Journal on Scientific Computing, Journal Year: 2025, Volume and Issue: 47(2), P. B477 - B504

Published: April 1, 2025

Language: Английский

Citations

1
Scalable Approximation and Solvers for Ionic Electrodiffusion in Cellular Geometries DOI
Pietro Benedusi, Ada J. Ellingsrud, Halvor Herlyng

et al.

SIAM Journal on Scientific Computing, Journal Year: 2024, Volume and Issue: 46(5), P. B725 - B751

Published: Oct. 16, 2024

Language: Английский

Citations

4
An electrodiffusive network model with multicompartmental neurons and synaptic connections DOI Creative Commons
Marte J. Sætra, Yoichiro Mori

PLoS Computational Biology, Journal Year: 2024, Volume and Issue: 20(11), P. e1012114 - e1012114

Published: Nov. 12, 2024

Most computational models of neurons assume constant ion concentrations, disregarding the effects changing concentrations on neuronal activity. Among that do incorporate concentration dynamics, simplifications are often made sacrifice biophysical consistency, such as neglecting ionic diffusion electrical potentials or electric drift concentrations. A subset with referred to electrodiffusive models, account for dynamics in a way ensures consistent relationship between charge, and potentials. These include compartmental single-cell geometrically explicit domain-type but none model network dynamics. To address this gap, we present an multicompartmental synaptic connections, which believe is first compartmentalized intra- extracellular biophysically way. The comprises arbitrary number “units,” each divided into three domains representing neuron, glia, space. Each domain further subdivided somatic dendritic layer. Unlike conventional focus primarily spiking patterns, our predicts (Na + , K Cl − Ca 2+ ), potentials, volume fractions. unique feature it captures ephaptic effects, both ionic. In paper, show how leads interesting behavior network. First, demonstrate can affect strengths. Then, coupling lead spontaneous firing not receive any external input. Lastly, explore having glia strongly coupled glial syncytium prevent depolarization blocks.

Language: Английский

Citations

1
Spatial modeling algorithms for reactions and transport in biological cells DOI Creative Commons
Emmet A. Francis, Justin G. Laughlin, Jørgen S. Dokken

et al.

Nature Computational Science, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 19, 2024

Language: Английский

Citations

1