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      A multi-scale computational model of the effects of TMS on motor cortex

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          Abstract

          The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different pyramidal cell types in motor cortex due to TMS. Our model determines precise electric fields based on an individual head model derived from magnetic resonance imaging and calculates how these electric fields activate morphologically detailed models of different neuron types. We predict neural activation patterns for different coil orientations consistent with experimental findings. Beyond this, our model allows us to calculate activation thresholds for individual neurons and precise initiation sites of individual action potentials on the neurons’ complex morphologies. Specifically, our model predicts that cortical layer 3 pyramidal neurons are generally easier to stimulate than layer 5 pyramidal neurons, thereby explaining the lower stimulation thresholds observed for I-waves compared to D-waves. It also shows differences in the regions of activated cortical layer 5 and layer 3 pyramidal cells depending on coil orientation. Finally, it predicts that under standard stimulation conditions, action potentials are mostly generated at the axon initial segment of cortical pyramidal cells, with a much less important activation site being the part of a layer 5 pyramidal cell axon where it crosses the boundary between grey matter and white matter. In conclusion, our computational model offers a detailed account of the mechanisms through which TMS activates different cortical pyramidal cell types, paving the way for more targeted application of TMS based on individual brain morphology in clinical and basic research settings.

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          Most cited references57

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          NON-INVASIVE MAGNETIC STIMULATION OF HUMAN MOTOR CORTEX

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            Influence of dendritic structure on firing pattern in model neocortical neurons.

            Neocortical neurons display a wide range of dendritic morphologies, ranging from compact arborizations to highly elaborate branching patterns. In vitro electrical recordings from these neurons have revealed a correspondingly diverse range of intrinsic firing patterns, including non-adapting, adapting and bursting types. This heterogeneity of electrical responsivity has generally been attributed to variability in the types and densities of ionic channels. We show here, using compartmental models of reconstructed cortical neurons, that an entire spectrum of firing patterns can be reproduced in a set of neurons that share a common distribution of ion channels and differ only in their dendritic geometry. The essential behaviour of the model depends on partial electrical coupling of fast active conductances localized to the soma and axon and slow active currents located throughout the dendrites, and can be reproduced in a two-compartment model. The results suggest a causal relationship for the observed correlations between dendritic structure and firing properties and emphasize the importance of active dendritic conductances in neuronal function.
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              Role of cortical cell type and morphology in subthreshold and suprathreshold uniform electric field stimulation in vitro.

              The neocortex is the most common target of subdural electrotherapy and noninvasive brain stimulation modalities, including transcranial magnetic stimulation (TMS) and transcranial current simulation (TCS). Specific neuronal elements targeted by cortical stimulation are considered to underlie therapeutic effects, but the exact cell type(s) affected by these methods remains poorly understood. We determined whether neuronal morphology or cell type predicted responses to subthreshold and suprathreshold uniform electric fields. We characterized the effects of subthreshold and suprathreshold electrical stimulation on identified cortical neurons in vitro. Uniform electric fields were applied to rat motor cortex brain slices, while recording from interneurons and pyramidal cells across cortical layers, using a whole-cell patch clamp. Neuron morphology was reconstructed after intracellular dialysis of biocytin. Based solely on volume-weighted morphology, we developed a parsimonious model of neuronal soma polarization by subthreshold electric fields. We found that neuronal morphology correlated with somatic subthreshold polarization. Based on neuronal morphology, we predict layer V pyramidal neuronal soma to be individually the most sensitive to polarization by optimally oriented subthreshold fields. Suprathreshold electric field action potential threshold was shown to reflect both direct cell polarization and synaptic (network) activation. Layer V/VI neuron absolute electric field action potential thresholds were lower than layer II/III pyramidal neurons and interneurons. Compared with somatic current injection, electric fields promoted burst firing and modulated action potential firing times. We present experimental data indicating that cortical neuron morphology relative to electric fields and cortical cell type are factors in determining sensitivity to sub- and supra-threshold brain stimulation.
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                Author and article information

                Journal
                F1000Res
                F1000Res
                F1000Research
                F1000Research
                F1000Research (London, UK )
                2046-1402
                17 February 2017
                2016
                : 5
                : 1945
                Affiliations
                [1 ]School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Korea, South
                [2 ]Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany
                [1 ]Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
                [1 ]Graduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia
                [1 ]Graduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW, Australia
                Gwangju Institute of Science and Technology, Korea, South
                [1 ]Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
                Gwangju Institute of Science and Technology, Korea, South
                Author notes

                JT, HS and NS designed the study. HS and NS implemented the model. HS, SCJ and JT analyzed the data. HS and JT wrote the manuscript and all authors were involved in the revision of the manuscript and have agreed to the final content.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Author information
                http://orcid.org/0000-0001-8166-2441
                Article
                10.12688/f1000research.9277.2
                5373428
                f30c103c-cbb7-4ee5-a211-92eb0a209338
                Copyright: © 2017 Seo H et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 3 February 2017
                Funding
                Funded by: National Research Foundation of Korea
                Award ID: NRF-2016R1A2B4010897
                This work was supported by grant (NRF-2016R1A2B4010897) from the National Research Foundation of Korea. The Lab of JT is supported by a gift from the Quandt foundation.
                The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Articles
                Theoretical & Computational Neuroscience

                transcranial magnetic stimulation,computational model,compartmental neuron model,brain stimulation,multi-scale modeling,motor cortex,d-wave,i-wave

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