How the brain tissue shapes the electric field induced by transcranial magnetic stimulation

Does Resting Motor Threshold Predict Motor Hand Recovery After Stroke?

Background: Resting Motor threshold (rMT) is one of the measurement obtained by Transcranial Magnetic Stimulation (TMS) that reflects corticospinal excitability. As a functional marker of the corticospinal pathway, the question arises whether rMT is a suitable biomarker for predicting post-stroke upper limb function. To that aim, we conducted a systematic review of relevant studies that investigated the clinical significance of rMT in stroke survivors by using correlations between upper limb motor scores and rMT. Methods: Studies that reported correlations between upper limb motor function and rMT as a measure of corticospinal excitability in distal arm muscle were identified via a literature search in stroke patients. Two authors extracted the data using a home-made specific form. Subgroup analyses were carried out with patients classified with respect to time post-stroke onset (early vs. chronic stage) and stroke location (cortical, subcortical, or cortico-subcortical). Methodological quality of the study was also evaluated by a published checklist. Results: Eighteen studies with 22 groups (n = 508 stroke patients) were included in this systematic review. Mean methodological quality score was 14.75/24. rMT was often correlated with motor function or hand dexterity (n = 15/22, 68%), explaining on average 31% of the variance of the motor score. Moreover, the results did not seem impacted if patients were examined at the early or chronic stages of stroke. Two findings could not be properly interpreted: (i) the fact that the rMT is an independent predictor of motor function as several confounding factors are well-established, and, (ii) whether the stroke location impacts this prediction. Conclusion: Most of the studies found a correlation between rMT and upper limb motor function after stroke. However, it is still unclear if rMT is an independent predictor of upper limb motor function when taking into account for age, time post stroke onset and level of corticospinal tract damage as confounding factors. Clear-cut conclusions could not be drawn at that time but our results suggest that rMT could be a suitable candidate although future investigations are needed. Systematic Review Registration Number: (https://www.crd.york.ac.uk/prospero/): ID 114317.

Cortical representation of auricular muscles in humans: A robot-controlled TMS mapping and fMRI study

BACKGROUND

Most humans have the ability to activate the auricular muscles. Although (intentional) control suggests an involvement of higher cortical centers underlying posterior auricular muscle (PAM) activation, the cortical representation of the auricular muscles is still unknown.

METHODS

With the purpose of identifying a possible cortical representation area we performed automated robotic and image-guided transcranial magnetic stimulation (TMS) mapping (n = 8) and functional magnetic resonance imaging (fMRI) (n = 13). For topographical comparison, a similar experimental protocol was applied for the first dorsal interosseus muscle (FDI) of the hand.

RESULTS

The calculated centers of gravity (COGs) of both muscles were located on the precentral gyrus with the PAM COGs located more laterally compared to the FDI. The distance between the mean PAM and mean FDI COG was 26.3 mm. The TMS mapping results were confirmed by fMRI, which showed a dominance of cortical activation within the precentral gyrus during the corresponding motor tasks. The correspondence of TMS and fMRI results was high.

CONCLUSION

The involvement of the primary motor cortex in PAM activation might point to an evolved function of the auricular muscles in humans and/or the ability of intentional (and selective) muscle activation.

Numerical evaluation of the skull for human neuromodulation with transcranial focused ultrasound

OBJECTIVE

Transcranial focused ultrasound is an emerging field for human non-invasive neuromodulation, but its dosing in humans is difficult to know due to the skull. The objective of the present study was to establish modeling methods based on medical images to assess skull differences between individuals on the wave propagation of ultrasound.

APPROACH

Computational models of transcranial focused ultrasound were constructed using CT and MR scans to solve for intracranial pressure. We explored the effect of including the skull base in models, different transducer placements on the head, and differences between 250 kHz or 500 kHz acoustic frequency for both female and male models. We further tested these features using linear, nonlinear, and elastic simulations. To better understand inter-subject skull thickness and composition effects we evaluated the intracranial pressure maps between twelve individuals at two different skull sites.

MAIN RESULTS

Nonlinear acoustic simulations resulted in virtually identical intracranial pressure maps with linear acoustic simulations. Elastic simulations showed a difference in max pressures and full width half maximum volumes of 15% at most. Ultrasound at an acoustic frequency of 250 kHz resulted in the creation of more prominent intracranial standing waves compared to 500 kHz. Finally, across twelve model human skulls, a significant linear relationship to characterize intracranial pressure maps was not found.

SIGNIFICANCE

Despite its appeal, an inherent problem with the use of a noninvasive transcranial ultrasound method is the difficulty of knowing intracranial effects because of the skull. Here we develop detailed computational models derived from medical images of individuals to simulate the propagation of neuromodulatory ultrasound across the skull and solve for intracranial pressure maps. These methods allow for a much better understanding of the intracranial effects of ultrasound for an individual in order to ensure proper targeting and more tightly control dosing.

Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline

OBJECTIVE

To investigate inter-subject variability with respect to cerebrospinal fluid thickness and brain-scalp distance, and to investigate intra-subject variability with different coil orientations.

METHODS

Simulations of the induced electric field (E-Field) using a figure-8 coil over the vertex were conducted on 50 unique head models and varying orientations on 25 models. Metrics exploring stimulation intensity, spread, and localization were used to describe inter-subject variability and effects of non-brain anatomy.

RESULTS

Both brain-scalp distance and CSF thickness were correlated with weaker stimulation intensity and greater spread. Coil rotations show that for the dorsal portion of the stimulated brain, E-Field intensities are highest when the anterior-posterior axis of the coil is perpendicular to the longitudinal fissure, but highest for the medial portion of the stimulated brain when the coil is oriented parallel to the longitudinal fissure.

CONCLUSIONS

Normal anatomical variation in healthy individuals leads to significant differences in the site of TMS, the intensity, and the spread. These variables are generally neglected but could explain significant variability in basic and clinical studies.

SIGNIFICANCE

This is the first work to show how brain-scalp distance and cerebrospinal fluid thickness influence focality, and to show the disassociation between dorsal and medial TMS.

Modeling Transcranial Direct-Current Stimulation-Induced Electric Fields in Children and Adults

Transcranial direct-current stimulation (tDCS) is a form of non-invasive brain stimulation that induces electric fields in neuronal tissue, modulating cortical excitability. Therapeutic applications of tDCS are rapidly expanding, and are being investigated in pediatrics for various clinical conditions. Anatomical variations are among a host of factors that influence the effects of tDCS, and pronounced anatomical differences between children and adults suggest that induced electric fields may be substantially different across development. The aim of this study was to determine the strength and distribution of tDCS-induced electric fields across development. Typically developing children, adolescents, and adults were recruited. Individualized finite-element method modeling of primary motor cortex (M1) targeting tDCS was performed. In the largest pediatric sample to date, we found significantly higher peak and mean M1 electric field strength, and more expansive electric field spread for children compared to adults. Electric fields were often comparable between adolescents and adults. Our results suggest that these differences may be associated with age-related differences in skull and extra-axial space thickness, as well as developmental changes occurring in gray and white matter. Individualized current modeling may be a valuable tool for personalizing effective doses of tDCS in future pediatric clinical trials.

Where does TMS Stimulate the Motor Cortex? Combining Electrophysiological Measurements and Realistic Field Estimates to Reveal the Affected Cortex Position

Much of our knowledge on the physiological mechanisms of transcranial magnetic stimulation (TMS) stems from studies which targeted the human motor cortex. However, it is still unclear which part of the motor cortex is predominantly affected by TMS. Considering that the motor cortex consists of functionally and histologically distinct subareas, this also renders the hypotheses on the physiological TMS effects uncertain. We use the finite element method (FEM) and magnetic resonance image-based individual head models to get realistic estimates of the electric field induced by TMS. The field changes in different subparts of the motor cortex are compared with electrophysiological threshold changes of 2 hand muscles when systematically varying the coil orientation in measurements. We demonstrate that TMS stimulates the region around the gyral crown and that the maximal electric field strength in this region is significantly related to the electrophysiological response. Our study is one of the most extensive comparisons between FEM-based field calculations and physiological TMS effects so far, being based on data for 2 hand muscles in 9 subjects. The results help to improve our understanding of the basic mechanisms of TMS. They also pave the way for a systematic exploration of realistic field estimates for dosage control in TMS.

Design of transcranial magnetic stimulation coils with optimal trade-off between depth, focality, and energy

OBJECTIVE

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique used for research and clinical applications. Existent TMS coils are limited in their precision of spatial targeting (focality), especially for deeper targets. This paper presents a methodology for designing TMS coils to achieve optimal trade-off between the depth and focality of the induced electric field (E-field), as well as the energy required by the coil.

APPROACH

A multi-objective optimization technique is used for computationally designing TMS coils that achieve optimal trade-offs between E-field focality, depth, and energy (fdTMS coils). The fdTMS coil winding(s) maximize focality (minimize the volume of the brain region with E-field above a given threshold) while reaching a target at a specified depth and not exceeding predefined peak E-field strength and required coil energy. Spherical and MRI-derived head models are used to compute the fundamental depth-focality trade-off as well as focality-energy trade-offs for specific target depths.

MAIN RESULTS

Across stimulation target depths of 1.0-3.4 cm from the brain surface, the suprathreshold volume can be theoretically decreased by 42%-55% compared to existing TMS coil designs. The suprathreshold volume of a figure-8 coil can be decreased by 36%, 44%, or 46%, for matched, doubled, or quadrupled energy. For matched focality and energy, the depth of a figure-8 coil can be increased by 22%.

SIGNIFICANCE

Computational design of TMS coils could enable more selective targeting of the induced E-field. The presented results appear to be the first significant advancement in the depth-focality trade-off of TMS coils since the introduction of the figure-8 coil three decades ago, and likely represent the fundamental physical limit.

Combined rTMS/fMRI Studies: An Overlooked Resource in Animal Models

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technique, which has brain network-level effects in healthy individuals and is also used to treat many neurological and psychiatric conditions in which brain connectivity is believed to be abnormal. Despite the fact that rTMS is being used in a clinical setting and animal studies are increasingly identifying potential cellular and molecular mechanisms, little is known about how these mechanisms relate to clinical changes. This knowledge gap is amplified by non-overlapping approaches used in preclinical and clinical rTMS studies: preclinical studies are mostly invasive, using cellular and molecular approaches, while clinical studies are non-invasive, including functional magnetic resonance imaging (fMRI), TMS electroencephalography (EEG), positron emission tomography (PET), and behavioral measures. A non-invasive method is therefore needed in rodents to link our understanding of cellular and molecular changes to functional connectivity changes that are clinically relevant. fMRI is the technique of choice for examining both short and long term functional connectivity changes in large-scale networks and is becoming increasingly popular in animal research because of its high translatability, but, to date, there have been no reports of animal rTMS studies using this technique. This review summarizes the main studies combining different rTMS protocols with fMRI in humans, in both healthy and patient populations, providing a foundation for the design of equivalent studies in animals. We discuss the challenges of combining these two methods in animals and highlight considerations important for acquiring clinically-relevant information from combined rTMS/fMRI studies in animals. We believe that combining rTMS and fMRI in animal models will generate new knowledge in the following ways: functional connectivity changes can be explored in greater detail through complementary invasive procedures, clarifying mechanism and improving the therapeutic application of rTMS, as well as improving interpretation of fMRI data. And, in a more general context, a robust comparative approach will refine the use of animal models of specific neuropsychiatric conditions.

A high-resolution computational localization method for transcranial magnetic stimulation mapping

BACKGROUND

Transcranial magnetic stimulation (TMS) is used for the mapping of brain motor functions. The complexity of the brain deters determining the exact localization of the stimulation site using simplified methods (e.g., the region below the center of the TMS coil) or conventional computational approaches.

OBJECTIVE

This study aimed to present a high-precision localization method for a specific motor area by synthesizing computed non-uniform current distributions in the brain for multiple sessions of TMS.

METHODS

Peritumoral mapping by TMS was conducted on patients who had intra-axial brain neoplasms located within or close to the motor speech area. The electric field induced by TMS was computed using realistic head models constructed from magnetic resonance images of patients. A post-processing method was implemented to determine a TMS hotspot by combining the computed electric fields for the coil orientations and positions that delivered high motor-evoked potentials during peritumoral mapping. The method was compared to the stimulation site localized via intraoperative direct brain stimulation and navigated TMS.

RESULTS

Four main results were obtained: 1) the dependence of the computed hotspot area on the number of peritumoral measurements was evaluated; 2) the estimated localization of the hand motor area in eight non-affected hemispheres was in good agreement with the position of a so-called "hand-knob"; 3) the estimated hotspot areas were not sensitive to variations in tissue conductivity; and 4) the hand motor areas estimated by this proposal and direct electric stimulation (DES) were in good agreement in the ipsilateral hemisphere of four glioma patients.

CONCLUSION(S)

The TMS localization method was validated by well-known positions of the "hand-knob" in brains for the non-affected hemisphere, and by a hotspot localized via DES during awake craniotomy for the tumor-containing hemisphere.

TMS of primary motor cortex with a biphasic pulse activates two independent sets of excitable neurones

Background

Biphasic pulses produced by most commercially available TMS machines have a cosine waveform, which makes it difficult to study the interaction between the two phases of stimulation.

Objective

We used a controllable pulse TMS (cTMS) device delivering quasi-rectangular pulse outputs to investigate whether monophasic are more effective than biphasic pulses.

Methods

Temporally symmetric (“biphasic”) or highly asymmetric (“monophasic”) charge-balanced biphasic stimuli were used to target the hand area of motor cortex in the anterior-posterior (AP) or posterior-anterior (PA) initial current direction.

Results

We observed the lowest motor thresholds and shortest motor evoked potential (MEP) latencies with initial PA pulses, and highest thresholds and longest latencies with AP pulses. Increasing pulse symmetry tended to increase threshold with a PA direction whereas it lowered thresholds and shortened latencies with an AP direction. Furthermore, it steepened the MEP input-output curve with both directions.

Conclusions

“Biphasic” TMS pulses can be viewed as two monophasic pulses of opposite directions, each stimulating a different set of interneurons with different thresholds (PA < AP). At threshold, the reverse phase of an initially PA pulse increases threshold compared with “monophasic” stimulation. At higher intensities, the reverse phase begins to activate AP-sensitive neurones and increase the effectiveness of stimulation above that of a “monophasic” PA pulse. “Biphasic” stimulation with initially AP pulses is dominated at threshold by activation produced by the lower threshold reverse (PA) phase.

Significance

The effects of biphasic stimulation are best understood as the summed output of two independent sets of directionally selective neural populations.

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Controllable pulse parameter TMS device was used to systematically modulate pulse shape.

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Pulse shape influenced primary motor cortex thresholds and input-output curves.

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Increasing pulse symmetry increased threshold with PA but lowered it with AP direction.

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Biphasic stimuli yield the summed output of directionally selective neural populations.

Redesigning existing transcranial magnetic stimulation coils to reduce energy: application to low field magnetic stimulation

OBJECTIVE

To present a systematic framework and exemplar for the development of a compact and energy-efficient coil that replicates the electric field (E-field) distribution induced by an existing transcranial magnetic stimulation coil.

APPROACH

The E-field generated by a conventional low field magnetic stimulation (LFMS) coil was measured for a spherical head model and simulated in both spherical and realistic head models. Then, using a spherical head model and spatial harmonic decomposition, a spherical-shaped cap coil was synthesized such that its windings conformed to a spherical surface and replicated the E-field on the cortical surface while requiring less energy. A prototype coil was built and electrically characterized. The effect of constraining the windings to the upper half of the head was also explored via an alternative coil design.

MAIN RESULTS

The LFMS E-field distribution resembled that of a large double-cone coil, with a peak field strength around 350 mV m^-1 in the cortex. The E-field distributions of the cap coil designs were validated against the original coil, with mean errors of 1%-3%. The cap coil required as little as 2% of the original coil energy and was significantly smaller in size.

SIGNIFICANCE

The redesigned LFMS coil is substantially smaller and more energy-efficient than the original, improving cost, power consumption, and portability. These improvements could facilitate deployment of LFMS in the clinic and potentially at home. This coil redesign approach can also be applied to other magnetic stimulation paradigms. Finally, the anatomically-accurate E-field simulation of LFMS can be used to interpret clinical LFMS data.

Human in-vivo brain magnetic resonance current density imaging (MRCDI)

Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are two emerging modalities, which combine weak time-varying currents injected via surface electrodes with magnetic resonance imaging (MRI) to acquire information about the current flow and ohmic conductivity distribution at high spatial resolution. The injected current flow creates a magnetic field in the head, and the component of the induced magnetic field ΔB_z,c parallel to the main scanner field causes small shifts in the precession frequency of the magnetization. The measured MRI signal is modulated by these shifts, allowing to determine ΔB_z,c for the reconstruction of the current flow and ohmic conductivity. Here, we demonstrate reliable ΔB_z,c measurements in-vivo in the human brain based on multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. In a series of experiments, we optimize their robustness for in-vivo measurements while maintaining a good sensitivity to the current-induced fields. We validate both methods by assessing the linearity of the measured ΔB_z,c with respect to the current strength. For the more efficient SSFP-FID measurements, we demonstrate a strong influence of magnetic stray fields on the ΔB_z,c images, caused by non-ideal paths of the electrode cables, and validate a correction method. Finally, we perform measurements with two different current injection profiles in five subjects. We demonstrate reliable recordings of ΔB_z,c fields as weak as 1 nT, caused by currents of 1 mA strength. Comparison of the ΔB_z,c measurements with simulated ΔB_z,c images based on FEM calculations and individualized head models reveals significant linear correlations in all subjects, but only for the stray field-corrected data. As final step, we reconstruct current density distributions from the measured and simulated ΔB_z,c data. Reconstructions from non-corrected ΔB_z,c measurements systematically overestimate the current densities. Comparing the current densities reconstructed from corrected ΔB_z,c measurements and from simulated ΔB_z,c images reveals an average coefficient of determination R² of 71%. In addition, it shows that the simulations underestimated the current strength on average by 24%. Our results open up the possibility of using MRI to systematically validate and optimize numerical field simulations that play an important role in several neuroscience applications, such as transcranial brain stimulation, and electro- and magnetoencephalography.

Perturbation of theta-gamma coupling at the temporal lobe hinders verbal declarative memory

BACKGROUND

Phase-amplitude cross-frequency coupling (PAC) is characterized by the modulation of the power of a fast brain oscillation (e.g., gamma) by the phase of a slow rhythm (e.g., theta). PAC in different sub- and neocortical regions is known to underlie effective neural communication and correlates with successful long-term memory formation.

OBJECTIVE/HYPOTHESIS

The present work aims to extend earlier observational data, by probing the functional role of theta-gamma PAC in the left temporal cortex in humans during verbal long-term memory encoding.

METHODS

In three double-blinded, placebo-controlled experiments (n = 72), we employed cross-frequency transcranial alternating current stimulation (tACS) to externally modulate ongoing PAC during a verbal-associative learning task. Three types of cross-frequency tACS protocols were used: bursts of high gamma tACS were coupled to the peak or trough of the theta tACS cycle, and a control condition where gamma tACS was continuously superimposed at theta tACS cycles.

RESULTS

Gamma bursts coupled to the trough of theta tACS induced robust behavioral impairment in memory performance (p < .01), whereas gamma burst coupled to the peak or continuously superimposed with theta tACS had no significant behavioral effects.

CONCLUSIONS

Our results demonstrate direct evidence regarding the importance of theta-gamma coupling in verbal long-term memory formation.

Multi-Scale Computational Models for Electrical Brain Stimulation

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed.

Rehabilitating the addicted brain with transcranial magnetic stimulation

Substance use disorders (SUDs) are one of the leading causes of morbidity and mortality worldwide. In spite of considerable advances in understanding the neural underpinnings of SUDs, therapeutic options remain limited. Recent studies have highlighted the potential of transcranial magnetic stimulation (TMS) as an innovative, safe and cost-effective treatment for some SUDs. Repetitive TMS (rTMS) influences neural activity in the short and long term by mechanisms involving neuroplasticity both locally, under the stimulating coil, and at the network level, throughout the brain. The long-term neurophysiological changes induced by rTMS have the potential to affect behaviours relating to drug craving, intake and relapse. Here, we review TMS mechanisms and evidence that rTMS is opening new avenues in addiction treatments.

How much detail is needed in modeling a transcranial magnetic stimulation figure-8 coil: Measurements and brain simulations

Background

Despite TMS wide adoption, its spatial and temporal patterns of neuronal effects are not well understood. Although progress has been made in predicting induced currents in the brain using realistic finite element models (FEM), there is little consensus on how a magnetic field of a typical TMS coil should be modeled. Empirical validation of such models is limited and subject to several limitations.

Methods

We evaluate and empirically validate models of a figure-of-eight TMS coil that are commonly used in published modeling studies, of increasing complexity: simple circular coil model; coil with in-plane spiral winding turns; and finally one with stacked spiral winding turns. We will assess the electric fields induced by all 3 coil models in the motor cortex using a computer FEM model. Biot-Savart models of discretized wires were used to approximate the 3 coil models of increasing complexity. We use a tailored MR based phase mapping technique to get a full 3D validation of the incident magnetic field induced in a cylindrical phantom by our TMS coil. FEM based simulations on a meshed 3D brain model consisting of five tissues types were performed, using two orthogonal coil orientations.

Results

Substantial differences in the induced currents are observed, both theoretically and empirically, between highly idealized coils and coils with correctly modeled spiral winding turns. Thickness of the coil winding turns affect minimally the induced electric field, and it does not influence the predicted activation.

Conclusion

TMS coil models used in FEM simulations should include in-plane coil geometry in order to make reliable predictions of the incident field. Modeling the in-plane coil geometry is important to correctly simulate the induced electric field and to correctly make reliable predictions of neuronal activation

Anatomical and functional correlates of cortical motor threshold of the dominant hand

BACKGROUND

Resting Motor threshold (rMT) provides information about cortical motor excitability. Interestingly, the influences of the structural or functional variability of the motor system on the rMT inter-individual variability have been poorly investigated.

OBJECTIVE/HYPOTHESIS

To investigate relationships between rMT and measures of brain structures and function of the motor system. The hypothesis is that cortical excitability not only depends on the primary motor cortex (M1) but also on the integration of information originating from its vicinity such as premotor (PMd and SMA) and post-central (S1) cortices.

METHODS

We measured brain structures, including grey and white matter properties (cortical volume and fiber coherence respectively), and functional interaction (resting-state functional connectivity-FC) in areas contributing to the corticospinal tract axons, i. e, M1, S1, SMA and PMd in the dominant hemisphere of 21 healthy subjects.

RESULTS

The rMT was inversely correlated with the FC between PMd and M1 (r = -0.496, 95%CI: -0.764; -0.081; p = 0.02) and the grey matter volume of the dominant hemisphere (r = -0.463, 95%CI: -0.746; -0.039; p = 0.03). The multiple regression analysis model retained the FC between M1 and PMd (coefficient: -25 ± 9) as well as the grey matter volume of the dominant hemisphere (coefficient: -0.15 ± 0.06) explaining 44% of the variance of the rMT (p: 0.005). When adding age and coil-to-cortex distance, two factors known to influence rMT, the model reached a R2 of 75% (p: 0.0001).

CONCLUSIONS

These results underline the major role of the PMd and the cortico-cortical connections toward M1 in the excitation of the corticospinal fibers likely through trans-synaptic pathways.

Diffusion MRI of the human brain at ultra-high field (UHF): A review

The continued drive towards MRI scanners operating at increasingly higher main magnetic fields is primarily motivated by the maxim that more teslas mean more signal and lead to better images. This promise of increased signal, which cannot easily be achieved in other ways, encourages efforts to overcome the inextricable technical challenges which accompany this endeavor. Unlike for many applications, however, diffusion imaging is not currently able to directly reap these potential signal gains - at the time of writing it seems fair to say that, for matched gradient and RF hardware, the majority of diffusion images acquired at 7T, while comparable in quality to those achievable at 3T, do not demonstrate a clear advantage over what can be obtained at lower field. This does not mean that diffusion imaging at UHF is not a worthwhile pursuit - but more a reflection of the fact that the associated challenges are manifold - and converting the potential of higher field strengths into 'better' diffusion imaging is by no means a straightforward task. This article attempts to summarize the specific reasons that make diffusion imaging at UHF more complicated than one might expect, and to highlight the range of developments that have already been made which have enabled diffusion images of excellent quality to be acquired at 7T.

The development and modelling of devices and paradigms for transcranial magnetic stimulation

Magnetic stimulation is a non-invasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain, as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modelling.

MR-based measurements and simulations of the magnetic field created by a realistic transcranial magnetic stimulation (TMS) coil and stimulator

Transcranial magnetic stimulation (TMS) is an emerging technique that allows non-invasive neurostimulation. However, the correct validation of electromagnetic models of typical TMS coils and the correct assessment of the incident TMS field (B_TMS ) produced by standard TMS stimulators are still lacking. Such a validation can be performed by mapping B_TMS produced by a realistic TMS setup. In this study, we show that MRI can provide precise quantification of the magnetic field produced by a realistic TMS coil and a clinically used TMS stimulator in the region in which neurostimulation occurs. Measurements of the phase accumulation created by TMS pulses applied during a tailored MR sequence were performed in a phantom. Dedicated hardware was developed to synchronize a typical, clinically used, TMS setup with a 3-T MR scanner. For comparison purposes, electromagnetic simulations of B_TMS were performed. MR-based measurements allow the mapping and quantification of B_TMS starting 2.5 cm from the TMS coil. For closer regions, the intra-voxel dephasing induced by B_TMS prohibits TMS field measurements. For 1% TMS output, the maximum measured value was ~0.1 mT. Simulations reflect quantitatively the experimental data. These measurements can be used to validate electromagnetic models of TMS coils, to guide TMS coil positioning, and for dosimetry and quality assessment of concurrent TMS-MRI studies without the need for crude methods, such as motor threshold, for stimulation dose determination.

Results on the spatial resolution of repetitive transcranial magnetic stimulation for cortical language mapping during object naming in healthy subjects

Background

The spatial resolution of repetitive navigated transcranial magnetic stimulation (rTMS) for language mapping is largely unknown. Thus, to determine a minimum spatial resolution of rTMS for language mapping, we evaluated the mapping sessions derived from 19 healthy volunteers for cortical hotspots of no-response errors. Then, the distances between hotspots (stimulation points with a high error rate) and adjacent mapping points (stimulation points with low error rates) were evaluated.

Results

Mean distance values of 13.8 ± 6.4 mm (from hotspots to ventral points, range 0.7–30.7 mm), 10.8 ± 4.8 mm (from hotspots to dorsal points, range 2.0–26.5 mm), 16.6 ± 4.8 mm (from hotspots to apical points, range 0.9–27.5 mm), and 13.8 ± 4.3 mm (from hotspots to caudal points, range 2.0–24.2 mm) were measured.

Conclusions

According to the results, the minimum spatial resolution of rTMS should principally allow for the identification of a particular gyrus, and according to the literature, it is in good accordance with the spatial resolution of direct cortical stimulation (DCS). Since measurement was performed between hotspots and adjacent mapping points and not on a finer-grained basis, we only refer to a minimum spatial resolution. Furthermore, refinement of our results within the scope of a prospective study combining rTMS and DCS for resolution measurement during language mapping should be the next step.

Field modeling for transcranial magnetic stimulation: A useful tool to understand the physiological effects of TMS?

Electric field calculations based on numerical methods and increasingly realistic head models are more and more used in research on Transcranial Magnetic Stimulation (TMS). However, they are still far from being established as standard tools for the planning and analysis in practical applications of TMS. Here, we start by delineating three main challenges that need to be addressed to unravel their full potential. This comprises (i) identifying and dealing with the model uncertainties, (ii) establishing a clear link between the induced fields and the physiological stimulation effects, and (iii) improving the usability of the tools for field calculation to the level that they can be easily used by non-experts. We then introduce a new version of our pipeline for field calculations (www.simnibs.org) that substantially simplifies setting up and running TMS and tDCS simulations based on Finite-Element Methods (FEM). We conclude with a brief outlook on how the new version of SimNIBS can help to target the above identified challenges.

In-vivo measurements of human brain tissue conductivity using focal electrical current injection through intracerebral multicontact electrodes

In-vivo measurements of human brain tissue conductivity at body temperature were conducted using focal electrical currents injected through intracerebral multicontact electrodes. A total of 1,421 measurements in 15 epileptic patients (age: 28 ± 10) using a radiofrequency generator (50 kHz current injection) were analyzed. Each contact pair was classified as being from healthy (gray matter, n = 696; white matter, n = 530) or pathological (epileptogenic zone, n = 195) tissue using neuroimaging analysis of the local tissue environment and intracerebral EEG recordings. Brain tissue conductivities were obtained using numerical simulations based on conductivity estimates that accounted for the current flow in the local brain volume around the contact pairs (a cube with a side length of 13 mm). Conductivity values were 0.26 S/m for gray matter and 0.17 S/m for white matter. Healthy gray and white matter had statistically different median impedances (P < 0.0001). White matter conductivity was found to be homogeneous as normality tests did not find evidence of multiple subgroups. Gray matter had lower conductivity in healthy tissue than in the epileptogenic zone (0.26 vs. 0.29 S/m; P = 0.012), even when the epileptogenic zone was not visible in the magnetic resonance image (MRI) (P = 0.005). The present in-vivo conductivity values could serve to create more accurate volume conduction models and could help to refine the identification of relevant intracerebral contacts, especially when located within the epileptogenic zone of an MRI-invisible lesion. Hum Brain Mapp 38:974-986, 2017. © 2016 Wiley Periodicals, Inc.

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

Enhancing Predicted Efficacy of Tumor Treating Fields Therapy of Glioblastoma Using Targeted Surgical Craniectomy: A Computer Modeling Study

Objective

The present work proposes a new clinical approach to TTFields therapy of glioblastoma. The approach combines targeted surgical skull removal (craniectomy) with TTFields therapy to enhance the induced electrical field in the underlying tumor tissue. Using computer simulations, we explore the potential of the intervention to improve the clinical efficacy of TTFields therapy of brain cancer.

Methods

We used finite element analysis to calculate the electrical field distribution in realistic head models based on MRI data from two patients: One with left cortical/subcortical glioblastoma and one with deeply seated right thalamic anaplastic astrocytoma. Field strength was assessed in the tumor regions before and after virtual removal of bone areas of varying shape and size (10 to 100 mm) immediately above the tumor. Field strength was evaluated before and after tumor resection to assess realistic clinical scenarios.

Results

For the superficial tumor, removal of a standard craniotomy bone flap increased the electrical field strength by 60–70% in the tumor. The percentage of tissue in expected growth arrest or regression was increased from negligible values to 30–50%. The observed effects were highly focal and targeted at the regions of pathology underlying the craniectomy. No significant changes were observed in surrounding healthy tissues. Median field strengths in tumor tissue increased with increasing craniectomy diameter up to 50–70 mm. Multiple smaller burr holes were more efficient than single craniectomies of equivalent area. Craniectomy caused no significant field enhancement in the deeply seated tumor, but rather a focal enhancement in the brain tissue underlying the skull defect.

Conclusions

Our results provide theoretical evidence that small and clinically feasible craniectomies may provide significant enhancement of TTFields intensity in cerebral hemispheric tumors without severely compromising brain protection or causing unacceptable heating in healthy tissues. A clinical trial is being planned to validate safety and efficacy.

Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography

The concurrent combination of transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is a powerful technology for characterizing and modulating brain networks across developmental, behavioral, and disease states. Given the global initiatives in mapping the human brain, recognition of the utility of this technique is growing across neuroscience disciplines. Importantly, TMS-EEG offers translational biomarkers that can be applied in health and disease, across the lifespan, and in humans and animals, bridging the gap between animal models and human studies. However, to utilize the full potential of TMS-EEG methodology, standardization of TMS-EEG study protocols is needed. In this article, we review the principles of TMS-EEG methodology, factors impacting TMS-EEG outcome measures, and the techniques for preventing and correcting artifacts in TMS-EEG data. To promote the standardization of this technique, we provide comprehensive guides for designing TMS-EEG studies and conducting TMS-EEG experiments. We conclude by reviewing the application of TMS-EEG in basic, cognitive and clinical neurosciences, and evaluate the potential of this emerging technology in brain research.

Noninvasive Electric Current Induction for Low-Frequency Tissue Conductivity Reconstruction: Is It Feasible With a TMS-MRI Setup?

Noninvasive quantification of subject-specific low-frequency brain tissue conductivity ( σLF ) will be valuable in different fields, for example, neuroscience. Magnetic resonance (MR)-electrical impedance tomography allows measurements of σLF . However, the required high level of direct current injection leads to an undesirable pain sensation. Following the same principles, but avoiding pain sensation, we evaluate the feasibility of inductively inducing currents using a transcranial magnetic stimulation (TMS) device and recording the magnetic field variations arising from the induced tissue eddy currents using a standard 3 T MR scanner. Using simulations, we characterize the strength of the incident TMS magnetic field arising from the current running in the TMS coil, the strength of the induced magnetic field arising from the induced currents in tissues by TMS pulses, and the MR phase accuracy required to measure this latter magnetic field containing information about σLF . Then, using TMS-MRI measurements, we evaluate the achievable phase accuracy for a typical TMS-MRI setup. From measurements and simulations, it is crucial to discriminate the incident from the induced magnetic field. The incident TMS magnetic field range is ±10^-4 T, measurable with standard MR scanners. In contrast, the induced TMS magnetic field is much weaker (±10^-8 T), leading to an MR phase contribution of ∼10^-4 rad. This phase range is too small to be measured, as the phase accuracy for TMS-MRI experiments is ∼10^-2 rads. Thus, although highly attractive, noninvasive measurements of the induced TMS magnetic field, and therefore estimations of σLF , are experimentally not feasible.

Neuromuscular Plasticity: Disentangling Stable and Variable Motor Maps in the Human Sensorimotor Cortex

Motor maps acquired with transcranial magnetic stimulation (TMS) are evolving as a biomarker for monitoring disease progression or the effects of therapeutic interventions. High test-retest reliability of this technique for long observation periods is therefore required to differentiate daily or weekly fluctuations from stable plastic reorganization of corticospinal connectivity. In this study, a novel projection, interpolation, and coregistration technique, which considers the individual gyral anatomy, was applied in healthy subjects for biweekly acquired TMS motor maps over a period of twelve weeks. The intraclass correlation coefficient revealed long-term reliability of motor maps with relevant interhemispheric differences. The sensorimotor cortex and nonprimary motor areas of the dominant hemisphere showed more extended and more stable corticospinal connectivity. Long-term correlations of the MEP amplitudes at each stimulation site revealed mosaic-like clusters of consistent corticospinal excitability. The resting motor threshold, centre of gravity, and mean MEPs across all TMS sites, as highly reliable cortical map parameters, could be disentangled from more variable parameters such as MEP area and volume. Cortical TMS motor maps provide high test-retest reliability for long-term monitoring when analyzed with refined techniques. They may guide restorative interventions which target dormant corticospinal connectivity for neurorehabilitation.

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

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.

Computational exploration of wave propagation and heating from transcranial focused ultrasound for neuromodulation

OBJECTIVE

While ultrasound is largely established for use in diagnostic imaging, its application for neuromodulation is relatively new and crudely understood. The objective of the present study was to investigate the effects of tissue properties and geometry on the wave propagation and heating in the context of transcranial neuromodulation.

APPROACH

A computational model of transcranial-focused ultrasound was constructed and validated against empirical data. The models were then incrementally extended to investigate a number of issues related to the use of ultrasound for neuromodulation, including the effect on wave propagation of variations in geometry of skull and gyral anatomy as well as the effect of multiple tissue and media layers, including scalp, skull, CSF, and gray/white matter. In addition, a sensitivity analysis was run to characterize the influence of acoustic properties of intracranial tissues. Finally, the heating associated with ultrasonic stimulation waveforms designed for neuromodulation was modeled.

MAIN RESULTS

The wave propagation of a transcranially focused ultrasound beam is significantly influenced by the cranial domain. The half maximum acoustic beam intensity profiles are insensitive overall to small changes in material properties, though the inclusion of sulci in models results in greater peak intensity values compared to a model without sulci (1%-30% greater). Finally, heating using currently employed stimulation parameters in humans is highest in bone (0.16 °C) and is negligible in brain (4.27 × 10(-3) °C) for a 0.5 s exposure.

SIGNIFICANCE

Ultrasound for noninvasive neuromodulation holds great promise and appeal for its non-invasiveness, high spatial resolution and deep focal lengths. Here we show gross brain anatomy and biological material properties to have limited effect on ultrasound wave propagation and to result in safe heating levels in the skull and brain.

Construction and Evaluation of Rodent-Specific rTMS Coils

Rodent models of transcranial magnetic stimulation (TMS) play a crucial role in aiding the understanding of the cellular and molecular mechanisms underlying TMS induced plasticity. Rodent-specific TMS have previously been used to deliver focal stimulation at the cost of stimulus intensity (12 mT). Here we describe two novel TMS coils designed to deliver repetitive TMS (rTMS) at greater stimulation intensities whilst maintaining spatial resolution. Two circular coils (8 mm outer diameter) were constructed with either an air or pure iron-core. Peak magnetic field strength for the air and iron-cores were 90 and 120 mT, respectively, with the iron-core coil exhibiting less focality. Coil temperature and magnetic field stability for the two coils undergoing rTMS, were similar at 1 Hz but varied at 10 Hz. Finite element modeling of 10 Hz rTMS with the iron-core in a simplified rat brain model suggests a peak electric field of 85 and 12.7 V/m, within the skull and the brain, respectively. Delivering 10 Hz rTMS to the motor cortex of anaesthetized rats with the iron-core coil significantly increased motor evoked potential amplitudes immediately after stimulation (n = 4). Our results suggest these novel coils generate modest magnetic and electric fields, capable of altering cortical excitability and provide an alternative method to investigate the mechanisms underlying rTMS-induced plasticity in an experimental setting.

The heart side of brain neuromodulation

Neuromodulation refers to invasive, minimally invasive or non-invasive techniques to stimulate discrete cortical or subcortical brain regions with therapeutic purposes in otherwise intractable patients: for example, thousands of advanced Parkinsonian patients, as well as patients with tremor or dystonia, benefited by deep brain stimulation (DBS) procedures (neural targets: basal ganglia nuclei). A new era for DBS is currently opening for patients with drug-resistant depression, obsessive-compulsive disorders, severe epilepsy, migraine and chronic pain (neural targets: basal ganglia and other subcortical nuclei or associative fibres). Vagal nerve stimulation (VNS) has shown clinical benefits in patients with pharmacoresistant epilepsy and depression. Non-invasive brain stimulation neuromodulatory techniques such as repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are also being increasingly investigated for their therapeutic potential in several neurological and psychiatric disorders. In this review, we first address the most common neural targets of each of the mentioned brain stimulation techniques, and the known mechanisms of their neuromodulatory action on stimulated brain networks. Then, we discuss how DBS, VNS, rTMS and tDCS could impact on the function of brainstem centres controlling vital functions, critically reviewing their acute and long-term effects on brain sympathetic outflow controlling heart function and blood pressure. Finally, as there is clear experimental evidence in animals that brain stimulation can affect autonomic and heart functions, we will try to give a critical perspective on how it may enhance our understanding of the cortical/subcortical mechanisms of autonomic cardiovascular regulation, and also if it might find a place among therapeutic opportunities in patients with otherwise intractable autonomic dysfunctions.

Technical aspects of neurostimulation: Focus on equipment, electric field modeling, and stimulation protocols

Neuromodulation is a field of science, medicine, and bioengineering that encompasses implantable and non-implantable technologies for the purpose of improving quality of life and functioning of humans. Brain neuromodulation involves different neurostimulation techniques: transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), which are being used both to study their effects on cognitive brain functions and to treat neuropsychiatric disorders. The mechanisms of action of neurostimulation remain incompletely understood. Insight into the technical basis of neurostimulation might be a first step towards a more profound understanding of these mechanisms, which might lead to improved clinical outcome and therapeutic potential. This review provides an overview of the technical basis of neurostimulation focusing on the equipment, the present understanding of induced electric fields, and the stimulation protocols. The review is written from a technical perspective aimed at supporting the use of neurostimulation in clinical practice.

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

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.

The role of blood vessels in high-resolution volume conductor head modeling of EEG

Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.

Factors to consider when applying transcranial magnetic stimulation of dorsolateral prefrontal cortex when resting motor threshold is asymmetric: A case study

Transcranial magnetic stimulation (TMS) is an increasingly popular tool in treating psychiatric conditions. The dorsal lateral prefrontal cortex (DLPFC) is typically targeted for stimulation, with magnetic field intensity being calibrated by establishing resting motor threshold (RMT) at hand region of primary motor cortex (M1 hand). This presumes that scalp-to-cortex distance (SCD) and cortical thickness is similar at both sites. We present data from a patient who had very asymmetrical RMTs (47 and 78). We investigated SCDs in this patient at the M1 hand and DLPFC, and the M1 hand cortical thickness. We also investigated TMS electric field distribution. The M1 hand SCD and cortical thickness of the M1 hand was larger on the side with higher RMT. Electric field finite element modelling demonstrated the focal point did not effectively reach the M1 hand with higher RMT as the postcentral gyrus was shunting it. Hence, successful DLPFC treatment was based upon the side with lower RMT. This study highlights the importance of tailoring DLPFC treatment intensity not only based on RMT at the M1 hand, and upon the degree to which SCD distance differs between sites, but also based upon size, shape, and density of M1 hand, as well as electric field distribution.

Repetitive magnetic stimulation induces plasticity of inhibitory synapses

Repetitive transcranial magnetic stimulation (rTMS) is used as a therapeutic tool in neurology and psychiatry. While repetitive magnetic stimulation (rMS) has been shown to induce plasticity of excitatory synapses, it is unclear whether rMS can also modify structural and functional properties of inhibitory inputs. Here we employed 10-Hz rMS of entorhinohippocampal slice cultures to study plasticity of inhibitory neurotransmission on CA1 pyramidal neurons. Our experiments reveal a rMS-induced reduction in GABAergic synaptic strength (2-4 h after stimulation), which is Ca(2+)-dependent and accompanied by the remodelling of postsynaptic gephyrin scaffolds. Furthermore, we present evidence that 10-Hz rMS predominantly acts on dendritic, but not somatic inhibition. Consistent with this finding, a reduction in clustered gephyrin is detected in CA1 stratum radiatum of rTMS-treated anaesthetized mice. These results disclose that rTMS induces coordinated Ca(2+)-dependent structural and functional changes of specific inhibitory postsynapses on principal neurons.

An integrated framework for targeting functional networks via transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a powerful investigational tool for in vivo manipulation of regional or network activity, with a growing number of potential clinical applications. Unfortunately, the vast majority of targeting strategies remain limited by their reliance on non-realistic brain models and assumptions that anatomo-functional relationships are 1:1. Here, we present an integrated framework that combines anatomically realistic finite element models of the human head with resting functional MRI to predict functional networks targeted via TMS at a given coil location and orientation. Using data from the Human Connectome Project, we provide an example implementation focused on dorsolateral prefrontal cortex (DLPFC). Three distinct DLPFC stimulation zones were identified, differing with respect to the network to be affected (default, frontoparietal) and sensitivity to coil orientation. Network profiles generated for DLPFC targets previously published for treating depression revealed substantial variability across studies, highlighting a potentially critical technical issue.

Investigating the cortical regions involved in MEP modulation in tDCS

Transcranial magnetic stimulation (TMS) is used in several studies to evaluate cortical excitability changes induced by transcranial direct current stimulation (tDCS) of the primary motor cortex. Interpretation of these results, however, is hindered by the very different spatial distribution of the electric field (E-field) induced by the two techniques and by the different target neurons that they might act upon. In this study we used the finite element method to calculate the E-field distribution induced by TMS and tDCS in a realistically shaped model of a human head. A model of a commercially available figure-8 coil was placed over a position above the identified hand knob (HK) region. We also modeled two configurations of bipolar tDCS montages with one of the electrodes placed over the HK and a return electrode over the contralateral orbital region. The electrodes over the HK were either rectangular in shape, with an area of 35 cm² or cylindrical with an area of π cm² (1 cm radius). To compare the E-field distribution in TMS and the two tDCS models, average values of the E-field's magnitude as well as the polar and azimuthal angle were investigated in the HK region and premotor areas. The results show that both techniques induce fields with different magnitudes and directions in the HK: the field in tDCS is predominantly perpendicular to the cortical surface, contrary to what happens in TMS where the field is mostly parallel to it. In the premotor areas, the magnitude of the E-field induced in TMS was well below the accepted threshold for MEP generation, 100 V/m. In tDCS, the magnitude of the field in these areas was comparable to that induced at the HK with a significant component perpendicular to the cortical surface. These results indicate that tDCS and TMS target preferentially different neuronal structures at the HK. Besides, they show that premotor areas may play a role in the tDCS-induced after effects on motor cortex excitability.

Modeling sequence and quasi-uniform assumption in computational neurostimulation

Computational neurostimulation aims to develop mathematical constructs that link the application of neuromodulation with changes in behavior and cognition. This process is critical but daunting for technical challenges and scientific unknowns. The overarching goal of this review is to address how this complex task can be made tractable. We describe a framework of sequential modeling steps to achieve this: (1) current flow models, (2) cell polarization models, (3) network and information processing models, and (4) models of the neuroscientific correlates of behavior. Each step is explained with a specific emphasis on the assumptions underpinning underlying sequential implementation. We explain the further implementation of the quasi-uniform assumption to overcome technical limitations and unknowns. We specifically focus on examples in electrical stimulation, such as transcranial direct current stimulation. Our approach and conclusions are broadly applied to immediate and ongoing efforts to deploy computational neurostimulation.