A model of magnetic stimulation of neocortical neurons

Kamitani, Yukiyasu; Bhalodia, Vidya M.; Kubota, Yoshihisa; Shimojo, Shinsuke

doi:10.1016/s0925-2312(01)00447-7

Cited by 51 publications

(54 citation statements)

References 9 publications

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“…With respect to SP duration, the computational method for modeling TMS first proposed by Kamitani et al is in agreement with sEMG data from pilot studies within our lab and can possibly be attributed to intracellular calcium dynamics [1,2]. Results obtained following the incorporation of [4] suggest that the silent period observed with sEMG may not be a single neuron phenomenon, but possibly a population response as described in [6].…”

Section: Resultssupporting

confidence: 80%

“…In the presence of volitional motor activity, a TMS pulse delivered to a targeted brain region evokes an sEMG waveform that sequentially depicts an onset latency, a multiphasic spike, and a refractory period referred to as the silent period (SP). The relationship between the activity of individual cortical neurons and the peripherally recorded SP is currently undefined, but has been explored [1,2].…”

Section: Introductionmentioning

confidence: 99%

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Investigating the interaction of transcranial magnetic stimulation with a model cortical neuron

et al. 2008

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IntroductionTranscranial magnetic stimulation (TMS) is a noninvasive technique that induces neuronal discharge in response to a rapidly changing magnetic field (B-field) directed through the scalp. However, the interaction between cortical tissue and the electric field (E-field) induced by the changing B-field remains unclear. A realistic multi-compartment model of a layer V pyramidal neuron receiving a simulated TMS pulse provides a means to characterize the influence of numerous parameters on cell discharge. BackgroundSurface electromyography (sEMG) is widely used to measure the electrophysiological response of muscle to TMS. In the presence of volitional motor activity, a TMS pulse delivered to a targeted brain region evokes an sEMG waveform that sequentially depicts an onset latency, a multiphasic spike, and a refractory period referred to as the silent period (SP). The relationship between the activity of individual cortical neurons and the peripherally recorded SP is currently undefined, but has been explored [1,2]. Model and methodsWe replicated a compartmental layer V neuron model and delivery of simulated TMS as described elsewhere [2,3]. Computer simulation was used to predict both the discharge response of the cortical neuron to different E-field magnitudes and the duration of the subsequent SP. To better understand the role of the TMS induced E-field, we replaced the stimulus described in [2] with a representation of E-field measurements obtained within our lab [4]. ResultsSimulations utilizing the stimulus set forth in [2] verified that the SP duration increased with stimulus strength [5], where the respective durations were most sensitive to alterations in calcium-dependent potassium conductance [3]. Simulations utilizing the pulse reported in [4] produced similar effects, however, SP duration showed decreased dependence on stimulus strength. ConclusionWith respect to SP duration, the computational method for modeling TMS first proposed by Kamitani et al is in agreement with sEMG data from pilot studies within our lab and can possibly be attributed to intracellular calcium dynamics [1,2]. Results obtained following the incorporation of [4] suggest that the silent period observed with sEMG may not be a single neuron phenomenon, but possibly a population response as described in [6].

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Section: Resultssupporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Investigating the interaction of transcranial magnetic stimulation with a model cortical neuron

et al. 2008

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“…Thereafter, researchers have established models with cell morphologies and membrane properties mimicking the real neurons. In addition to the confirmation of former conclusions, new observations have been madethe polarization at the cell body and axonal terminals were compared (Arlotti et al 2012), a possible mechanism for the silence period following the stimulation (Inghilleri et al 1993) was proposed (Kamitani et al 2001), the hindering effects of both the dendritic components and the heterogeneity in tissue were assessed, while the potency of different pulse waveforms were compared (Salvador et al 2011;Pashut et al 2011). Making use of the strategically simplified cell models, these previous simulation works have offered insights into the evoked cell activation.…”

Section: Introductionmentioning

confidence: 87%

Cortical neuron activation induced by electromagnetic stimulation: a quantitative analysis via modelling and simulation

Fan

Lee

et al. 2015

J Comput Neurosci

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Previous simulation works concerned with the mechanism of non-invasive neuromodulation has isolated many of the factors that can influence stimulation potency, but an inclusive account of the interplay between these factors on realistic neurons is still lacking. To give a comprehensive investigation on the stimulation-evoked neuronal activation, we developed a simulation scheme which incorporates highly detailed physiological and morphological properties of pyramidal cells. The model was implemented on a multitude of neurons; their thresholds and corresponding activation points with respect to various field directions and pulse waveforms were recorded. The results showed that the simulated thresholds had a minor anisotropy and reached minimum when the field direction was parallel to the dendritic-somatic axis; the layer 5 pyramidal cells always had lower thresholds but substantial variances were also observed within layers; reducing pulse length could magnify the threshold values as well as the variance; tortuosity and arborization of axonal segments could obstruct action potential initiation. The dependence of the initiation sites on both the orientation and the duration of the stimulus implies that the cellular excitability might represent the result of the competition between various firing-capable axonal components, each with a unique susceptibility determined by the local geometry. Moreover, the measurements obtained in simulation intimately resemble recordings in physiological and clinical studies, which seems to suggest that, with minimum simplification of the neuron model, the cable theory-based simulation approach can have sufficient verisimilitude to give quantitatively accurate evaluation of cell activities in response to the externally applied field.

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“…Some neurons have multiple axons and one axon features different diameters along its pathway. In the future, more realistic neuronal morphologies, as in (Kamitani et al 2001) and (Pashut et al 2011), should be incorporated. A distinction should also be made between the different types of neurons, such as the sensory neurons, the interneurons and pyramidal neurons.…”

Section: Discussionmentioning

confidence: 99%

Modeling transcranial magnetic stimulation from the induced electric fields to the membrane potentials along tractography-based white matter fiber tracts

Geeter

Dupré²,

Crevecoeur³

2016

J. Neural Eng.

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Objective. Transcranial magnetic stimulation (TMS) is a promising non-invasive tool for modulating the brain activity. Despite the widespread therapeutic and diagnostic use of TMS in neurology and psychiatry, its observed response remains hard to predict, limiting its further development and applications. Although the stimulation intensity is always maximum at the cortical surface near the coil, experiments reveal that TMS can affect deeper brain regions as well. Approach. The explanation of this spread might be found in the white matter fiber tracts, connecting cortical and subcortical structures. When applying an electric field on neurons, their membrane potential is altered. If this change is significant, more likely near the TMS coil, action potentials might be initiated and propagated along the fiber tracts towards deeper regions. In order to understand and apply TMS more effectively, it is important to capture and account for this interaction as accurately as possible. Therefore, we compute, next to the induced electric fields in the brain, the spatial distribution of the membrane potentials along the fiber tracts and its temporal dynamics. Main results. This paper introduces a computational TMS model in which electromagnetism and neurophysiology are combined. Realistic geometry and tissue anisotropy are included using magnetic resonance imaging and targeted white matter fiber tracts are traced using tractography based on diffusion tensor imaging. The position and orientation of the coil can directly be retrieved from the neuronavigation system. Incorporating these features warrants both patient-and case-specific results. Significance. The presented model gives insight in the activity propagation through the brain and can therefore explain the observed clinical responses to TMS and their inter-and/or intra-subject variability. We aspire to advance towards an accurate, flexible and personalized TMS model that helps to understand stimulation in the connected brain and to target more focused and deeper brain regions.S Online supplementary data available from stacks.iop.org/jne/13/026028/mmedia

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A model of magnetic stimulation of neocortical neurons

Cited by 51 publications

References 9 publications

Investigating the interaction of transcranial magnetic stimulation with a model cortical neuron

Investigating the interaction of transcranial magnetic stimulation with a model cortical neuron

Cortical neuron activation induced by electromagnetic stimulation: a quantitative analysis via modelling and simulation

Modeling transcranial magnetic stimulation from the induced electric fields to the membrane potentials along tractography-based white matter fiber tracts

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