TMS field modelling-status and next steps

In the recent years, an increasing number of studies used geometrically accurate head models and finite element (FEM) or finite difference methods (FDM) to estimate the electric field induced by non-invasive neurostimulation techniques such as transcranial magnetic stimulation (TMS) or transcranial weak current stimulation (tCS; e.g., Datta et al., 2010 and Thielscher et al., 2011). A general outcome was that the field estimates based on these more realistic models differ substantially from the results obtained with simpler head models. This suggests that the former models are indeed needed to realistically capture the field distribution in the brain. However, it is unclear how accurate even these more advanced models are and, in particular, to which extent they allow predicting the physiological outcome of stimulation. An experimental validation of the novel methods for field calculation is thus necessary. Focusing on motor cortex stimulation by TMS, our goal is to explore to which extent the field estimates based on advanced models correlate with the physiological stimulation effects. For example, we aim at testing whether interindividual differences in the field estimates are also reflected in differences in the MEP responses. This would indicate that the field calculations accurately capture the impact of individual macroanatomical features of the head and brain on the induced field distribution, in turn strongly supporting their plausibility. Our approach is based on the SimNIBS software pipeline (www.simnibs.de) that allows for the automatic creation of accurate head models from structural and diffusion-weighted magnetic resonance images (MRI) (Windhoff et al., 2011). This enables us to perform field calculations for multiple subjects, as required in neuroscientific studies. We substantially improved the software in order to improve its usability in a group analysis. At the moment, we are performing field calculations and are acquiring motor mapping data in a group of subjects for a systematic comparison of both data sets. I will give an overview on the status of the SimNIBS project. I will start by summarizing the key findings on how the individual brain anatomy shapes the electric field induced by TMS Thielscher et al., 2011 and Opitz, 2011. The putative link between the modeling results and basic physiological TMS effects is highlighted. I will then introduce the novel features of SimNIBS that include the import of coil positions from neuronavigation systems, improved support for diffusion-weighted MRI and transformation of the estimated fields into MNI space for group analysis. Preliminary results on the comparison between field estimates and motor mapping data will be presented. To summarize, field estimates based on accurate head models have already proven highly useful for a better understanding of the biophysics of non-invasive brain stimulation. The improved software tools now allow for systematic tests of the links between the estimated fields and the physiological effects in multi-subject studies. This will give the knowledge needed, e.g., for a more accurate spatial targeting of specific brain areas by TMS

Comparing TMS perturbations to occipital and parietal cortices in concurrent TMS-fMRI studies-Methodological considerations

Neglect and hemianopia are two neuropsychological syndromes that are associated with reduced awareness for visual signals in patients' contralesional hemifield. They offer the unique possibility to dissociate the contributions of retino-geniculate and retino-colliculo circuitries in visual perception. Yet, insights from patient fMRI studies are limited by heterogeneity in lesion location and extent, long-term functional reorganization and behavioural compensation after stroke. Transcranial magnetic stimulation (TMS) has therefore been proposed as a complementary method to investigate the effect of transient perturbations on functional brain organization. This concurrent TMS-fMRI study applied TMS perturbation to occipital and parietal cortices with the aim to 'mimick' neglect and hemianopia. Based on the challenges and interpretational limitations of our own study we aim to provide tutorial guidance on how future studies should compare TMS to primary sensory and association areas that are governed by distinct computational principles, neural dynamics and functional architecture

Reaching with the sixth sense: Vestibular contributions to voluntary motor control in the human right parietal cortex

The vestibular system constitutes the silent sixth sense: It automatically triggers a variety of vital reflexes to maintain postural and visual stability. Beyond their role in reflexive behavior, vestibular afferents contribute to several perceptual and cognitive functions and also support voluntary control of movements by complementing the other senses to accomplish the movement goal. Investigations into the neural correlates of vestibular contribution to voluntary action in humans are challenging and have progressed far less than research on corresponding visual and proprioceptive involvement. Here, we demonstrate for the first time with event-related TMS that the posterior part of the right medial intraparietal sulcus processes vestibular signals during a goal-directed reaching task with the dominant right hand. This finding suggests a qualitative difference between the processing of vestibular vs. visual and proprioceptive signals for controlling voluntary movements, which are pre-dominantly processed in the left posterior parietal cortex. Furthermore, this study reveals a neural pathway for vestibular input that might be distinct from the processing for reflexive or cognitive functions, and opens a window into their investigation in humans

Human In-vivo MR Current Density Imaging (MRCDI) Based on Optimized Multi-echo Spin Echo (MESE)

MRCDI aims at imaging an externally injected current flow in the human body, and might be useful for many biomedical applications. However, the method requires very sensitive measurement of the current-induced magnetic field component ?Bz,c parallel to main field. We systematically optimized MESE to determine its most efficient parameters. In one of the first human in-vivo applications of MRCDI, the optimized sequence was successfully used to image the ?Bz,c distribution in the brain caused by a two-electrode montage, as confirmed by finite-element calculations of ?Bz,c. Further improvements will be performed to increase its robustness to field drifts

A Head Template for Computational Dose Modelling for Transcranial Focused Ultrasound Stimulation

Transcranial focused Ultrasound Stimulation (TUS) at low intensities is emerging as a novel non-invasive brain stimulation method with higher spatial resolution than established transcranial stimulation methods and the ability to selectively stimulate also deep brain areas. Accurate control of the focus position and strength of the TUS acoustic waves is important to enable a beneficial use of the high spatial resolution and to ensure safety. As the human skull causes strong attenuation and distortion of the waves, simulations of the transmitted waves are needed to accurately determine the TUS dose distribution inside the cranial cavity. The simulations require information of the skull morphology and its acoustic properties. Ideally, they are informed by computed tomography (CT) images of the individual head. However, suited individual imaging data is often not readily available. For this reason, we here introduce and validate a head template that can be used to estimate the average effects of the skull on the TUS acoustic wave in the population. The template was created from CT images of the heads of 29 individuals of different ages (between 20-50 years), gender and ethnicity using an iterative non-linear co-registration procedure. For validation, we compared acoustic and thermal simulations based on the template to the average of the simulation results of all 29 individual datasets. Acoustic simulations were performed for a model of a focused transducer driven at 500 kHz, placed at 24 standardized positions by means of the EEG 10-10 system. Additional simulations at 250 kHz and 750 kHz at 16 of the positions were used for further confirmation. The amount of ultrasound-induced heating at 500 kHz was estimated for the same 16 transducer positions. Our results show that the template represents the median of the acoustic pressure and temperature maps from the individuals reasonably well in most cases. This underpins the usefulness of the template for the planning and optimization of TUS interventions in studies of healthy young adults. Our results further indicate that the amount of variability between the individual simulation results depends on the position. Specifically, the simulated ultrasound-induced heating inside the skull exhibited strong interindividual variability for three posterior positions close to the midline, caused by a high variability of the local skull shape and composition. This should be taken into account when interpreting simulation results based on the template

Sensitivity analysis of magnetic field measurements for magnetic resonance electrical impedance tomography (MREIT)

Purpose Clinical use of magnetic resonance electrical impedance tomography (MREIT) still requires significant sensitivity improvements. Here, the measurement of the current-induced magnetic field (ΔBz,c) is improved using systematic efficiency analyses and optimization of multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. Theory and Methods Considering T1, T2, and math formula relaxation in the signal-to-noise ratios (SNRs) of the MR magnitude images, the efficiency of MESE and SSFP-FID MREIT experiments, and its dependence on the sequence parameters, are analytically analyzed and simulated. The theoretical results are experimentally validated in a saline-filled homogenous spherical phantom with relaxation parameters similar to brain tissue. Measurement of ΔBz,c is also performed in a cylindrical phantom with saline and chicken meat. Results The efficiency simulations and experimental results are in good agreement. When using optimal parameters, ΔBz,c can be reliably measured in the phantom even at injected current strengths of 1 mA or lower for both sequence types. The importance of using proper crusher gradient selection on the phase evolution in a MESE experiment is also demonstrated. Conclusion The efficiencies observed with the optimized sequence parameters will likely render in-vivo human brain MREIT feasible

Contributions of the PPC to online control of visually guided reaching movements assessed with fMRI-Guided TMS

The posterior parietal cortex (PPC) plays an important role in controlling voluntary movements by continuously integrating sensory information about body state and the environment. We tested which subregions of the PPC contribute to the processing of target- and body-related visual information while reaching for an object, using a reaching paradigm with 2 types of visual perturbation: displacement of the visual target and displacement of the visual feedback about the hand position. Initially, functional magnetic resonance imaging (fMRI) was used to localize putative target areas involved in online corrections of movements in response to perturbations. The causal contribution of these areas to online correction was tested in subsequent neuronavigated transcranial magnetic stimulation (TMS) experiments. Robust TMS effects occurred at distinct anatomical sites along the anterior intraparietal sulcus (aIPS) and the anterior part of the supramarginal gyrus for both perturbations. TMS over neighboring sites did not affect online control. Our results support the hypothesis that the aIPS is more generally involved in visually guided control of movements, independent of body effectors and nature of the visual information. Furthermore, they suggest that the human network of PPC subregions controlling goal-directed visuomotor processes extends more inferiorly than previously thought. Our results also point toward a good spatial specificity of the TMS effects. © 2010 The Author