ArticleFrontiers in neuroinformatics2020
Finite Element Simulation of Ionic Electrodiffusion in Cellular Geometries.
Article in Frontiers in neuroinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Accurate computation of ionic concentrations in the synaptic cleft requires the full Poisson-Nernst-Planck (PNP) equations.PLoS computational biology · 2026Article
- Extracellular stimulation and ephaptic coupling of neurons in a fully coupled finite element-based Extracellular-Membrane-Intracellular (EMI) model.Frontiers in computational neuroscience · 2026Article
- Calcium dynamics in small spaces: Lessons learned from modeling in dendritic spines.Biophysical journal · 2025Review
- Electrodiffusion dynamics in the cardiomyocyte dyad at nano-scale resolution using the Poisson-Nernst-Planck (PNP) equations.PLoS computational biology · 2025Article
- Article
- An electrodiffusive network model with multicompartmental neurons and synaptic connections.PLoS computational biology · 2024Article
- Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue.Scientific reports · 2024Article
- The simplified Kirchhoff network model (SKNM): a cell-based reaction-diffusion model of excitable tissue.Scientific reports · 2023Article
- Nano-scale solution of the Poisson-Nernst-Planck (PNP) equations in a fraction of two neighboring cells reveals the magnitude of intercellular electrochemical waves.PLoS computational biology · 2023Article
- Article
- Membrane electrical properties of mouse hippocampal CA1 pyramidal neurons during strong inputs.Biophysical journal · 2022Article
- Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks.Frontiers in neuroinformatics · 2022Article
- Computing Extracellular Electric Potentials from Neuronal Simulations.Advances in experimental medicine and biology · 2022Article
- An electrodiffusive neuron-extracellular-glia model for exploring the genesis of slow potentials in the brain.PLoS computational biology · 2021Article
- From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology.Frontiers in physiology · 2021Article
- An electrodiffusive, ion conserving Pinsky-Rinzel model with homeostatic mechanisms.PLoS computational biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mathematical models for excitable cells are commonly based on cable theory, which considers a homogenized domain and spatially constant ionic concentrations. Although such models provide valuable insight, the effect of altered ion concentrations or detailed cell morphology on the electrical potentials cannot be captured. In this paper, we discuss an alternative approach to detailed modeling of electrodiffusion in neural tissue. The mathematical model describes the distribution and evolution of ion concentrations in a geometrically-explicit representation of the intra- and extracellular domains. As a combination of the electroneutral Kirchhoff-Nernst-Planck (KNP) model and the Extracellular-Membrane-Intracellular (EMI) framework, we refer to this model as the KNP-EMI model. Here, we introduce and numerically evaluate a new, finite element-based numerical scheme for the KNP-EMI model, capable of efficiently and flexibly handling geometries of arbitrary dimension and arbitrary polynomial degree. Moreover, we compare the electrical potentials predicted by the KNP-EMI and EMI models. Finally, we study ephaptic coupling induced in an unmyelinated axon bundle and demonstrate how the KNP-EMI framework can give new insights in this setting.
Indexed as
Identifiers
What OpenQuestion holds
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.