ArticleFrontiers in neuroscience2022
Dosing Transcranial Magnetic Stimulation of the Primary Motor and Dorsolateral Prefrontal Cortices With Multi-Scale Modeling.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study.NeuroImage · 2023Pooled it
- Integrating Pharmacodynamic Data to Prioritise Candidate Migraine Genes and Pathways Using a Novel Bioinformatics Workflow.Journal of clinical medicine · 2026Article
- Cellular Mechanisms of Transcranial Magnetic Stimulation in Climbing Fibers and Purkinje Neurons in the Cerebellum.bioRxiv : the preprint server for biology · 2026Article
- Simulation of evoked responses to transcranial magnetic stimulation using a multiscale cortical circuit model.bioRxiv : the preprint server for biology · 2025Article
- Enhancing retrieval capacity of the predictive brain through dorsolateral prefrontal cortex intervention.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Efficient prospective electric field-informed localization of motor cortical targets of transcranial magnetic stimulation.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression.Cognitive neurodynamics · 2024Article
- Cellular and Molecular Effects of Magnetic Fields.International journal of molecular sciences · 2024Review
- Axon morphology and intrinsic cellular properties determine repetitive transcranial magnetic stimulation threshold for plasticity.Frontiers in cellular neuroscience · 2024Article
- Toward standardized MEP recording? Exploring the role of electrode configuration in TMS studies.Frontiers in human neuroscience · 2024Article
- Electric-field-based dosing for TMS.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Methodological approach for assessing motor cortical excitability changes with single-pulse transcranial magnetic stimulation.MethodsX · 2023Article
- Repetitive transcranial magnetic stimulation (rTMS) triggers dose-dependent homeostatic rewiring in recurrent neuronal networks.PLoS computational biology · 2023Article
- Simulation of evoked responses to transcranial magnetic stimulation using a multiscale cortical circuit model.Brain stimulationArticle
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcranial magnetic stimulation (TMS) can depolarize cortical neurons through the intact skin and skull. The characteristics of the induced electric field (E-field) have a major impact on specific outcomes of TMS. Using multi-scale computational modeling, we explored whether the stimulation parameters derived from the primary motor cortex (M1) induce comparable macroscopic E-field strengths and subcellular/cellular responses in the dorsolateral prefrontal cortex (DLPFC). To this aim, we calculated the TMS-induced E-field in 16 anatomically realistic head models and simulated the changes in membrane voltage and intracellular calcium levels of morphologically and biophysically realistic human pyramidal cells in the M1 and DLPFC. We found that the conventional intensity selection methods (i.e., motor threshold and fixed intensities) produce variable macroscopic E-fields. Consequently, it was challenging to produce comparable subcellular/cellular responses across cortical regions with distinct folding characteristics. Prospectively, personalized stimulation intensity selection could standardize the E-fields and the subcellular/cellular responses to repetitive TMS across cortical regions and individuals. The suggested computational approach points to the shortcomings of the conventional intensity selection methods used in clinical settings. We propose that multi-scale modeling has the potential to overcome some of these limitations and broaden our understanding of the neuronal mechanisms for TMS.
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