Where and what TMS activates: Experiments and modeling

Laakso, Ilkka; Murakami, Takenobu; Hirata, Akimasa; Ugawa, Yoshikazu

doi:10.1016/j.brs.2017.09.011

Cited by 107 publications

(134 citation statements)

References 35 publications

Supporting

Mentioning

125

Contrasting

Order By: Relevance

“…Neural activation is therefore more likely to occur in the gyral crown and lip, which are exposed to larger E-field magnitudes, than the sulcal wall. These results provide a clear mechanistic explanation of recent studies relating MTs for a range of TMS coil orientations and positions with E-field distributions calculated in subject-specific head models 6,7 .…”

Section: Discussionsupporting

confidence: 69%

“…Computational modeling is a powerful tool for investigating the mechanisms of TMS as well as for choosing stimulation parameters for more selective target engagement. Prior modeling efforts focused on calculating the spatial distribution of the induced E-field by TMS-typically using the finite element method (FEM) in head models derived from magnetic resonance imaging (MRI) data 6,7 . However, the spatial distribution of the E-field alone cannot predict the physiological effects of stimulation, and TMS can recruit distinct neural populations or elements based on different temporal dynamics of the E-field waveform (e.g.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simulation of transcranial magnetic stimulation in head model with morphologically-realistic cortical neurons

Aberra

Wang

Grill

et al. 2018

Preprint

View full text Add to dashboard Cite

Transcranial magnetic stimulation (TMS) enables non-invasive modulation of brain activity with both clinical and research applications, but fundamental questions remain about the neural types and elements it activates and how stimulation parameters affect the neural response. We integrated detailed neuronal models with TMSinduced electric fields in the human head to quantify the effects of TMS on cortical neurons. TMS activated with lowest intensity layer 5 pyramidal cells at their intracortical axonal terminations in the superficial gyral crown and lip regions. Layer 2/3 pyramidal cells and inhibitory basket cells may be activated too, whereas direct activation of layers 1 and 6 was unlikely. Neural activation was largely driven by the field magnitude, contrary to theories implicating the field component normal to the cortical surface. Varying the induced current's direction caused a waveform-dependent shift in the activation site and provided a mechanistic explanation for experimentally observed differences in thresholds and latencies of muscle responses. This biophysically-based simulation provides a novel method to elucidate mechanisms and inform parameter selection of TMS and other forms of cortical stimulation.

show abstract

Section: Discussionsupporting

confidence: 69%

Section: Introductionmentioning

confidence: 99%

Simulation of transcranial magnetic stimulation in head model with morphologically-realistic cortical neurons

Aberra

Wang

Grill

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…This study adopted the EF strength to describe regions with a high possibility of stimulation. The rationale is that even in the cerebral cortex where there is a highly uniform orientation of the pyramidal neurons relative to the cortical surface, a consensus of the most appropriate EF direction has not been established (Fox et al 2004;Bungert et al 2016;Laakso et al 2017). In the case of the deep brain regions, the orientation of the majority of the neurons, which is important to determine the most effective EF direction, is not clear except for hippocampus.…”

Section: Group-level Ef Characterizationmentioning

confidence: 99%

Group-Level Analysis of Induced Electric Field in Deep Brain Regions by Different TMS Coils

Gómez-Tames¹,

Hamasaka²,

Hirata³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Deep transcranial magnetic stimulation (dTMS) is a non-invasive technique used in treating depression. In this study, we computationally evaluate group-level dosage during dTMS with the aim of characterizing targeted deep brain regions to overcome the limitation of using individualized head models to characterize coil performance in a population.We use an inter-subject registration method adapted to deep brain regions that enable projection of computed electric fields (EFs) from individual realistic head models (n = 18) to the average space of deep brain regions. The computational results showed consistent group-level hotspots of the EF in deep brain region with intensities between 20%-50% of the maximum EF in the cortex. Large co-activation in other brain regions was confirmed while half-value penetration depth from the cortical surface was smaller than 2 cm. The halo figure-8 assembly and halo circular assembly coils induced the highest EFs for caudate, putamen, and hippocampus.Generalized induced EF maps of deep regions show target regions despite inter-individual difference. This is the first study that visualizes generalized target regions during dTMS and provides a method for making informed decisions during dTMS interventions in clinical practice.

show abstract

“…For this, we need a volume conductor model (VCM) that characterizes the conductivity distribution of the head. While simulation and offline TMS studies use realistically-shaped highly detailed VCMs [2,3,4,5], in experimental navigated TMS the head has so far been modeled as a spherically symmetric conductor that is fitted to approximate either the shape of the skull under the coil or the whole skull. Spherical models omit the effects of well-conducting cerebrospinal fluid (CSF) [2,6] and may fail in approximating the effects of skull at regions of changing skull curvature [7].…”

Section: Introductionmentioning

confidence: 99%

“…To optimally benefit from the E-field model in navigation, the E-field should be computed in near real time, so that the operator can see the estimated field pattern while moving the TMS coil. With finite-element methods used for solving realistic VCMs in, for example, [4,5] and recently proposed approaches that apply finite differences [8] and boundary elements [9,10], computation of the E-field takes of the order of tens of seconds to minutes for one coil position.…”

Section: Introductionmentioning

confidence: 99%

Real-time computation of the TMS-induced electric field in a realistic head model

Stenroos

Koponen

2019

Preprint

View full text Add to dashboard Cite

Transcranial magnetic stimulation (TMS) is often targeted using a model of TMS-induced electric field (E). In such navigated TMS, the E-field models have been based on spherical approximation of the head. Such models omit the effects of cerebrospinal fluid (CSF) and gyral folding, leading to potentially large errors in the computed E-field. So far, realistic models have been too slow for interactive TMS navigation. We present computational methods that enable real-time solving of the E-field in a realistic five-compartment (5-C) head model that contains isotropic white matter, gray matter, CSF, skull and scalp.Using reciprocity and Geselowitz integral equation, we separate the computations to coil-dependent and -independent parts. For the Geselowitz integrals, we present a fast numerical quadrature. Further, we present a moment-matching approach for optimizing dipole-based coil models.We verified and benchmarked the new methods using simulations with over 100 coil locations. The new quadrature introduced a relative error (RE) of 0.3-0.6%. For a coil model with 42 dipoles, the total RE of the quadrature and coil model was 0.44-0.72%. Taking also other model errors into account, the contribution of the new approximations to the RE was 0.1%. For comparison, the RE due to omitting the separation of white and gray matter was >11%, and the RE due to omitting also the CSF was >23%.Using a standard PC and basic GPU, our solver computed the full E-field in a 5-C model in 9000 points on the cortex in 27 coil positions per second (cps). When the separation of white and gray matter was omitted, the speed was 43-65 cps. Solving only one component of the E-field tripled the speed.The presented methods enable real-time solving of the TMS-induced E-field in a realistic head model that contains the CSF and gyral folding. The new methodology allows more accurate targeting and precise adjustment of stimulation intensity during experimental or clinical TMS mapping. (Matti Stenroos) 2. Theory Reciprocity relationLet there be a system of conductors. Let primary current distribution J p 1 give rise to electric field E 1 . Correspondingly, J p 2 gives rise to E 2 . Then, assuming the head electrically resistive and small compared to the wavelength of electromagnetic waves, we get the reciprocity relation [10]Letting J p 1 be a dipolar current element Q at r Q , i.e. J p 1 ( r ) = Qδ( r − r Q ), and J p 2 a current loop (coil) with current I flowing in a thin wire c, we get [11]

show abstract

Where and what TMS activates: Experiments and modeling

Cited by 107 publications

References 35 publications

Simulation of transcranial magnetic stimulation in head model with morphologically-realistic cortical neurons

Simulation of transcranial magnetic stimulation in head model with morphologically-realistic cortical neurons

Group-Level Analysis of Induced Electric Field in Deep Brain Regions by Different TMS Coils

Real-time computation of the TMS-induced electric field in a realistic head model

Contact Info

Product

Resources

About