A Boundary Element Method of Bidomain Modeling for Predicting Cellular Responses to

bioRxiv [Preprint] · 2023 · Unclear · Insufficient evidence

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The proposed bidomain boundary element method produced accurate simulation results for both electric and magnetic stimulation in comparison studies, and avoids the need for multi-scale volume meshes, making embedded microscale-in-macroscale modeling computati…

Study snapshot

PublicationbioRxiv [Preprint] · 2023
Study typeengineering
Reported directionUnclear
Evidence ratingInsufficient

Abstract

A Boundary Element Method of Bidomain Modeling for Predicting Cellular Responses to Electromagnetic Fields Czerwonky DM, Aberra AS, Gomez LJ. A Boundary Element Method of Bidomain Modeling for Predicting Cellular Responses to Electromagnetic Fields. bioRxiv [Preprint]. 2023 Dec 16:2023.12.15.571917. doi: 10.1101/2023.12.15.571917. (preprint, not peer-reviewed) Abstract Objective: Commonly used cable equation-based approaches for determining the effects of electromagnetic fields on excitable cells make several simplifying assumptions that could limit their predictive power. Bidomain or "whole" finite element methods have been developed to fully couple cells and electric fields for more realistic neuron modeling. Here, we introduce a novel bidomain integral equation designed for determining the full electromagnetic coupling between stimulation devices and the intracellular, membrane, and extracellular regions of neurons. Methods: Our proposed boundary element formulation offers a solution to an integral equation that connects the device, tissue inhomogeneity, and cell membrane-induced E-fields. We solve this integral equation using first-order nodal elements and an unconditionally stable Crank-Nicholson time-stepping scheme. To validate and demonstrate our approach, we simulated cylindrical Hodgkin-Huxley axons and spherical cells in multiple brain stimulation scenarios. Main results: Comparison studies show that a boundary element approach produces accurate results for both electric and magnetic stimulation. Unlike bidomain finite element methods, the bidomain boundary element method does not require volume meshes containing features at multiple scales. As a result, modeling cells, or tightly packed populations of cells, with microscale features embedded in a macroscale head model, is made computationally tractable, and the relative placement of devices and cells can be varied without the need to generate a new mesh. Significance: Device-induced electromagnetic fields are commonly used to modulate brain activity for research and therapeutic applications. Bidomain solvers allow for the full incorporation of realistic cell geometries, device E-fields, and neuron populations. Thus, multi-cell studies of advanced neuronal mechanisms would greatly benefit from the development of fast-bidomain solvers to ensure scalability and the practical execution of neural network simulations with realistic neuron morphologies. Open access paper: biorxiv.org

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AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeengineering
Effect directionunclear
PopulationNot supplied
Sample sizeNot supplied
ExposureNot supplied
Evidence strengthInsufficientConfidence: 74% · Peer reviewed: no

Main findings

The proposed bidomain boundary element method produced accurate simulation results for both electric and magnetic stimulation in comparison studies, and avoids the need for multi-scale volume meshes, making embedded microscale-in-macroscale modeling computationally tractable and allowing device/cell placement changes without generating a new mesh.

Outcomes measured

  • Modeling accuracy for electric stimulation
  • Modeling accuracy for magnetic stimulation
  • Computational tractability/scalability of bidomain boundary element method
  • Ability to model microscale cellular features embedded in macroscale head models without remeshing

Limitations

  • Preprint; explicitly noted as not peer-reviewed
  • Simulation/modeling study (no empirical biological/clinical outcomes reported in abstract)
  • Specific validation details and quantitative performance metrics are not provided in the abstract
View raw extracted JSON
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    "source": "brain stimulation devices (electric and magnetic stimulation)",
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    "duration": null
  },
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  "sample_size": null,
  "outcomes": [
    "Modeling accuracy for electric stimulation",
    "Modeling accuracy for magnetic stimulation",
    "Computational tractability/scalability of bidomain boundary element method",
    "Ability to model microscale cellular features embedded in macroscale head models without remeshing"
  ],
  "main_findings": "The proposed bidomain boundary element method produced accurate simulation results for both electric and magnetic stimulation in comparison studies, and avoids the need for multi-scale volume meshes, making embedded microscale-in-macroscale modeling computationally tractable and allowing device/cell placement changes without generating a new mesh.",
  "effect_direction": "unclear",
  "limitations": [
    "Preprint; explicitly noted as not peer-reviewed",
    "Simulation/modeling study (no empirical biological/clinical outcomes reported in abstract)",
    "Specific validation details and quantitative performance metrics are not provided in the abstract"
  ],
  "evidence_strength": "insufficient",
  "confidence": 0.74,
  "peer_reviewed_likely": "no",
  "keywords": [
    "boundary element method",
    "bidomain modeling",
    "integral equation",
    "electromagnetic coupling",
    "electric stimulation",
    "magnetic stimulation",
    "Hodgkin-Huxley axon",
    "brain stimulation",
    "computational modeling"
  ],
  "suggested_hubs": [
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}
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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1101/2023.12.15.571917
PubMed: Not supplied

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