ReviewJournal of neural engineering2024
Quasistatic approximation in neuromodulation.
Review in Journal of neural engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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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.
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Who cites it
19 citing papers in PubMed.
- Mechanisms of transcranial magnetic brain stimulation.Physiological reviews · 2026Review
- Conductivity Deviations as Virtual Sources in Magnetoencephalography.Brain topography · 2026Article
- The optimization of neuroprosthetic interfaces relying on biophysical and surrogate digital twins.npj biomedical innovations · 2026Review
- Optimization, implementation, and performance of TMS coils with maximum focality and various stimulation depths.Journal of neural engineering · 2026Article
- Roadmap towards personalized approaches and safety considerations in non-ionizing radiation: from dosimetry to therapeutic and diagnostic applications.Physics in medicine and biology · 2026Review
- Inferring neural sources from electroencephalography: foundations and frontiers.Journal of neural engineering · 2026Review
- PyFibers: An open-source NEURON-Python package to simulate responses of model nerve fibers to electrical stimulation.PLoS computational biology · 2025Article
- Wearable disposable electrotherapy.Nature communications · 2025Article
- Computational Optimization of Spinal Cord Stimulation for Dorsal Horn Interneuron Polarization.Neuromodulation : journal of the International Neuromodulation Society · 2025Article
- Role of frequency-dependent and capacitive tissue properties in spinal cord stimulation models.Journal of neural engineering · 2025Article
- Biophysical characterization of the recording of unmyelinated and myelinated fiber activity with peripheral interfaces.iScience · 2025Article
- Statistical method accounts for microscopic electric field distortions around neurons when simulating activation thresholds.bioRxiv : the preprint server for biology · 2025Article
- Characterization of Machine Learning-Based Surrogate Models of Neural Activation Under Electrical Stimulation.Bioelectromagnetics · 2025Article
- Real-time computation of brain E-field for enhanced transcranial magnetic stimulation neuronavigation and optimization.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- On assumptions and key issues in electric field modeling for ECT.Molecular psychiatry · 2024Article
- Article
- Statistical method accounts for microscopic electric field distortions around neurons when simulating activation thresholds.Brain stimulationArticle
- Optimal asymmetric electric field pulses for selective transcranial magnetic stimulation with minimised power and coil heating.Brain stimulationArticle
- Transcranial electric stimulation modulates firing rate at clinically relevant intensities.Brain stimulationArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuromodulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue. As a consequence of these assumptions, each tissue is assigned a fixed conductivity, and the simplified equations (e.g. Laplace's equation) are solved for the spatial distribution of the field, which is separated from the field's temporal waveform. Recognizing that electrical tissue properties may be more complex, we explain how QSA can be embedded in parallel or iterative pipelines to model frequency dependence or nonlinearity of conductivity. We survey the history and validity of QSA across specific applications, such as microstimulation, deep brain stimulation, spinal cord stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. The precise definition and explanation of QSA in neuromodulation are essential for rigor when using QSA models or testing their limits.
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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.