Biology subjects

Thielscher, A.

Publications and source records attributed to Thielscher, A..

34 records · Page 2Linked to original sources

bioRxiv2022

Systematic evaluation of anatomical details on transcranial electric stimulation and transcranial magnetic stimulation induced electric fields in a non-human primate model

Non-human primates (NHPs) have become key for translational research in noninvasive brain stimulation (NIBS). However, in order to create comparable stimulation conditions to humans it is vital to evaluate and match electric fields across species. Numerical models to simulate electric fields are an important tool for experimental planning in NHPs and translation to human studies. It is thus essential to evaluate how anatomical details in NHP models affect NIBS electric fields. Here, we create a highly accurate head model of a non-human primate (NHP) from 10.5 T MR data. We systematically evaluate how muscle tissue and head size (due to different MRI fields of view) affect simulation results in transcranial electric and magnetic stimulation (TES and TMS). Our findings indicate that the inclusion of muscle can affect TES electric field strength up to 29.5% while TMS is largely unaffected. Additionally, comparing a full head model to a cropped head model illustrates the impact of head size on electric fields for both TES and TMS. We find opposing effects between TES and TMS with an increase up to 13.5% for TES and a decrease up to 21.5% for TMS for the cropped head model compared to the full head model. Our results provide important insights into the level of anatomical detail needed for NHP head models and can inform future translational efforts for NIBS studies. HighlightsO_LIWe created a high resolution non-human primate FEM head model from 10.5 T MR data. C_LIO_LIWe ran transcranial electric and magnetic stimulation (TES and TMS) simulations to evaluate the effects of muscle and head size on the induced electric field in the brain. C_LIO_LIWe simulated both isotropic and anisotropic muscle conductivities. C_LIO_LIMuscle tissue can greatly affect simulation results for TES (increase electric field strength by up to 29.5%), but not for TMS. C_LIO_LIThere are opposing, but large effects of using a full head model versus a cropped head model for both TES (increase up to 13.5%) and TMS (decrease of up to 21.5%) C_LI

neuroscience↗

bioRxiv2022

Evaluating the Influence of Anatomical Accuracy and Electrode Positions on EEG Forward Solutions

Generating realistic volume conductor models for forward calculations in electroencephalography (EEG) is not trivial and several factors contribute to the accuracy of such models, two of which are its anatomical accuracy and the accuracy with which electrode positions are known. Here, we investigate effects of anatomical accuracy by comparing forward solutions from SimNIBS, a tool which allows state-of-the-art anatomical modeling, with well-established pipelines in MNE-Python and FieldTrip. We also compare different ways of specifying electrode locations when digitized positions are not available such as transformation of measured positions from standard space and transformation of a manufacturer layout. Substantial effects of anatomical accuracy were seen throughout the entire brain both in terms of field topography and magnitude with SimNIBS generally being more accurate than the pipelines in MNE-Python and FieldTrip. Topographic and magnitude effects were particularly pronounced for MNE-Python which uses a three-layer boundary element method (BEM) model. We attribute these mainly to differences in skull and cerebrospinal fluid (CSF) modeling. Effects of electrode specification method were evident in occipital and posterior areas when using a transformed manufacturer layout whereas transforming measured positions from standard space generally resulted in smaller errors. We suggest modeling the anatomy of the volume conductor as accurately possible and we hope to facilitate this by making it easy to export simulations from SimNIBS to MNE-Python and FieldTrip for further analysis. Likewise, if digitized electrode positions are not available, a set of measured positions on a standard head template may be preferable to those specified by the manufacturer.

neuroscience↗

bioRxiv2022

Modulating behavioral signatures of rhythmic auditory entrainment with tACS

Synchronization between auditory stimuli and brain rhythms is beneficial for perception. In principle, auditory perception could be improved by facilitating neural entrainment to sounds via brain stimulation. However, high inter-individual variability of brain stimulation effects questions the usefulness of this approach. Here we aimed to modulate auditory perception by modulating neural entrainment to frequency modulated (FM) sounds using transcranial alternating current stimulation (tACS). In addition, we evaluated the advantage of using tACS montages spatially optimized for each individuals anatomy and functional data compared to a standard montage applied to all participants. Across two different sessions, 2-Hz tACS was applied targeting auditory brain regions. Concurrent with tACS, participants listened to FM stimuli with modulation rate matching the tACS frequency but with different phase lags relative to the tACS, and detected silent gaps embedded in the FM sound. We observed that tACS modulated the strength of behavioral entrainment to the FM sound in a phase-lag specific manner. Both the optimal tACS lag and the magnitude of the tACS effect were variable across participants and sessions. Inter-individual variability of tACS effects was best explained by the strength of the inward electric field, depending on the field focality and proximity to the target brain region. Although additional evidence is necessary, our results also provided suggestive insights that spatially optimizing the electrode montage could be a promising tool to reduce inter-individual variability of tACS effects. This work demonstrates that tACS effectively modulates entrainment to sounds depending on the optimality of the electric field. However, the lack of reliability on optimal tACS lags calls for caution when planning tACS experiments based on separate sessions.

neuroscience↗

bioRxiv2022

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel

Background and ObjectiveTranscranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. MethodsData from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual MPRAGE images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. ResultsIn M1, higher mean E-field magnitude was associated with greater tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p =0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. ConclusionsOur data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects. HighlightsO_LIWe study the link between individually simulated electric field dose and tDCS-induced change in GABA in the cortex. C_LIO_LIThe electric field strength in the brain correlates with a decrease in GABA in the motor cortex. C_LIO_LIThe correlation between the electric field and GABA change is modulated by the amount of grey matter in the MRS voxel. C_LIO_LIWe find no association between the electric field and GABA in the temporal cortex. C_LI

neuroscience↗

bioRxiv2022

Short periods of bipolar anodal TDCS induce no instantaneous dose-dependent increase in cerebral blood flow in the targeted human motor cortex

BackgroundAnodal transcranial direct current stimulation (aTDCS) of primary motor hand area (M1-HAND) can enhance corticomotor excitability. Yet, it is still unknown which current intensity produces the strongest effect on regional neural activity. Magnetic resonance imaging (MRI) combined with pseudo-continuous Arterial Spin Labeling (pc-ASL MRI) can map regional cortical blood flow (rCBF) and may thus be useful to probe the relationship between current intensity and neural response at the individual level. ObjectiveHere we employed pc-ASL MRI to map acute rCBF changes during short-duration aTDCS of left M1-HAND. Using the rCBF response as a proxy for regional neuronal activity, we investigated if short-duration aTDCS produces an instantaneous dose-dependent rCBF increase in the targeted M1-HAND that may be useful for individual dosing. MethodsNine healthy right-handed participants received 30 seconds of aTDCS at 0.5, 1.0, 1.5, and 2.0 mA with the anode placed over left M1-HAND and cathode over the right supraorbital region. Concurrent pc-ASL MRI at 3 T probed TDCS-related rCBF changes in the targeted M1-HAND. Movement-induced rCBF changes were also assessed. ResultsApart from a subtle increase in rCBF at 0.5 mA, short-duration aTDCS did not modulate rCBF in the M1-HAND relative to no-stimulation periods. None of the participants showed a dose-dependent increase in rCBF during aTDCS, even after accounting for individual differences in TDCS-induced electrical field strength. In contrast, finger movements led to robust activation of left M1-HAND before and after aTDCS. ConclusionShort-duration bipolar aTDCS does not produce instantaneous dose-dependent rCBF increases in the targeted M1-HAND at conventional intensity ranges. Therefore, the regional hemodynamic response profile to short-duration aTDCS may not be suited to inform individual dosing of TDCS intensity. HighlightsO_LIArterial spin labeling (ASL) MRI probed regional cerebral blood flow (rCBF) during anodal TDCS. C_LIO_LIShort-duration anodal TDCS was applied to left motor hand area (M1-HAND) at 0.5, 1.0, 1.5 and 2.0 mA. C_LIO_LIAnodal TDCS produced no instantaneous dose-dependent rCBF increase in left M1-HAND. C_LIO_LIApart from a subtle increase at 0.5 mA, rCBF was not modified in M1-HAND during anodal TDCS. C_LI

neuroscience↗

bioRxiv2021

Relationship between high-frequency activity in the sensory and the motor hand areas, and regional myelin content

BackgroundThe human primary sensory (S1) and primary motor (M1) hand areas feature high-frequency neuronal responses. Electrical nerve stimulation evokes high-frequency oscillations (HFO) at around 650 Hz in the contralateral S1. Likewise, transcranial magnetic stimulation (TMS) of M1 can evoke a series of descending volleys in the corticospinal pathway that can be detected non-invasively with a paired-pulse TMS protocol, called short interval intracortical facilitation (SICF). SICF features several peaks of facilitation of motor evoked potentials in contralateral hand muscles, which are separated by inter-peak intervals resembling HFO rhythmicity. HypothesisIn this study, we tested the hypothesis that the individual expressions of HFO and SICF are tightly related to each other and to the regional myelin content in the sensorimotor cortex. MethodsIn 24 healthy volunteers, we recorded HFO and SICF, and, in a subgroup of 20 participants, we mapped the cortical myelin content using the ratio between the T1- and T2-weighted MRI signal as read-out. ResultsThe individual frequencies and magnitudes of HFO and SICF curves were tightly correlated: the intervals between the first and second peak of cortical HFO and SICF showed a positive linear relationship (r= 0.703, p< 0.001), while their amplitudes were inversely related (r= -0.613, p= 0.001). The rhythmicity, but not the magnitude of the high-frequency responses, was related to the cortical myelin content: the higher the cortical myelin content, the shorter the inter-peak intervals of HFO and SICF. ConclusionThe results confirm a tight functional relationship between high-frequency responses in S1 (i.e., HFO) and M1 (i.e., as measured with SICF). They also establish a link between the degree of regional cortical myelination and the expression of high-frequency responses in the human sensorimotor cortex, giving further the opportunity to infer their generators.

neuroscience↗

bioRxiv2021

On the Reconstruction of Magnetic ResonanceCurrent Density Images of the Human Brain:Pitfalls and Perspectives

Magnetic resonance current density imaging (MRCDI) of the human brain aims to reconstruct the current density distribution caused by transcranial electric stimulation from MR-based measurements of the current-induced magnetic fields. The reconstruction problem is challenging due to a low signal-to-noise ratio and a limited volume coverage of the MR-based measurements, the lack of data from the scalp and skull regions and because MRCDI is only sensitive to the component of the current-induced magnetic field parallel to the scanner field. Most existing reconstruction approaches have been validated using simulation studies and measurements in phantoms with simplified geometries. Only one reconstruction method, the projected current density algorithm, has been applied to human in-vivo data so far, however resulting in blurred current density estimates even when applied to noise-free simulated data. We analyze the underlying causes for the limited performance of the projected current density algorithm when applied to human brain data. In addition, we compare it with an approach that relies on the optimization of the conductivities of a small number of tissue compartments of anatomically detailed head models reconstructed from structural MR data. Both for simulated ground truth data and human in-vivo MRCDI data, our results indicate that the estimation of current densities benefits more from using a personalized volume conductor model than from applying the projected current density algorithm. In particular, we introduce a hierarchical statistical testing approach as a principled way to test and compare the quality of reconstructed current density images that accounts for the limited signal-to-noise ratio of the human in-vivo MRCDI data and the fact that the ground truth of the current density is unknown for measured data. Our results indicate that the statistical testing approach constitutes a valuable framework for the further development of accurate volume conductor models of the head. Our findings also highlight the importance of tailoring the reconstruction approaches to the quality and specific properties of the available data.

neuroscience↗

bioRxiv2021

Sensitivity and resolution improvement for in-vivo magnetic resonance current density imaging (MRCDI) of the human brain

PurposeMagnetic resonance current density imaging (MRCDI) combines MR brain imaging with the injection of time-varying weak currents (1-2 mA) to assess the current flow pattern in the brain. However, the utility of MRCDI is still hampered by low measurement sensitivity and poor image quality. MethodsWe recently introduced a multi-gradient-echo-based MRCDI approach that has the hitherto best documented efficiency. We now advanced our MRCDI approach in three directions and performed phantom and in-vivo human brain experiments for validation: First, we verified the importance of enhanced spoiling and optimize it for imaging of the human brain. Second, we improved the sensitivity and spatial resolution by using acquisition weighting. Third, we added navigators as a quality control measure for tracking physiological noise. Combining these advancements, we tested our optimized MRCDI method by using 1 mA transcranial electrical stimulation (TES) currents injected via two different electrode montages in five subjects. ResultsFor a session duration of 4:20 min, the new MRCDI method was able to detect magnetic field changes caused by the TES current flow at a sensitivity level of 84 pT, representing in a twofold increase relative to our original method. Comparing both methods to current flow simulations based on personalized head models demonstrated a consistent increase in the coefficient of determination of {Delta}R2=0.12 for the current-induced magnetic fields and {Delta}R2=0.22 for the current flow reconstructions. Interestingly, some of the simulations still clearly deviated from the measurements despite of the strongly improved measurement quality. This suggests that MRCDI can reveal useful information for the improvement of head models used for current flow simulations. ConclusionThe advanced method strongly improves the sensitivity and robustness of MRCDI and is an important step from proof-of-concept studies towards a broader application of MRCDI in clinical and basic neuroscience research.

neuroscience↗

bioRxiv2021

Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression

Transcranial magnetic stimulation (TMS) is a powerful tool to investigate causal structure-function relationships in the human brain. However, a precise delineation of the effectively stimulated neuronal populations is notoriously impeded by the widespread and complex distribution of the induced electric field. Here, we propose a method that allows rapid and feasible cortical localization at the individual subject level. The functional relationship between electric field and behavioral effect is quantified by combining experimental data with numerically modelled fields to identify the cortical origin of the modulated effect. Motor evoked potentials (MEPs) from three finger muscles were recorded for a set of random stimulations around the primary motor area. All induced electric fields were nonlinearly regressed against the elicited MEPs to identify their cortical origin. We could distinguish cortical muscle representation with high spatial resolution and localized them primarily on the crowns and rims of the precentral gyrus. A post-hoc analysis revealed exponential convergence of the method with the number of stimulations, yielding a minimum of about 180 random stimulations to obtain stable results. Establishing a functional link between the modulated effect and the underlying mode of action, the induced electric field, is a fundamental step to fully exploit the potential of TMS. In contrast to previous approaches, the presented protocol is particularly easy to implement, fast to apply, and very robust due to the random coil positioning and therefore is suitable for practical and clinical applications.

neuroscience↗

bioRxiv2020

Optimizing the Electric Field Strength in Multiple Targets for Multichannel Transcranial Electric Stimulation

ObjectiveMost approaches to optimize the electric field pattern generated by multichannel Transcranial Electric Stimulation (TES) require the definition of a preferred direction of the electric field in the target region(s). However, this requires knowledge about how the neural effects depend on the field direction, which is not always available. Thus, it can be preferential to optimize the field strength in the target(s), irrespective of the field direction. However, this results in a more complex optimization problem. ApproachWe introduce and validate a novel optimization algorithm that maximizes focality while controlling the electric field strength in the target to maintain a defined value. It obeys the safety constraints, allows limiting the number of active electrodes and allows also for multi-target optimization. Main ResultsThe optimization algorithm outperformed naive search approaches in both quality of the solution and computational efficiency. Using the amygdala as test case, we show that it allows for reaching a reasonable trade-off between focality and field strength in the target. In contrast, simply maximizing the field strength in the target results in far more extended fields. In addition, by maintaining the pre-defined field strengths in the targets, the new algorithm allows for a balanced stimulation of two or more regions. SignificanceThe novel algorithm can be used to automatically obtain individualized, optimal montages for targeting regions without the need to define preferential directions. It will automatically select the field direction that achieves the desired field strength in the target(s) with the most focal stimulation pattern.

bioengineering↗

bioRxiv2020

Multimodal finger-printing of the human precentral cortex forming the motor hand knob

Transcranial magnetic stimulation (TMS) of the precentral hand knob can evoke motor evoked potentials (MEP) in contralateral hand muscles. Biophysical modelling points to the dorsal premotor cortex (PMd) in the superficial crown-lip region as primary site of TMS-induced neuronal excitation. Here, we used a sulcus-aligned MRI-informed TMS mapping approach to determine the optimal site (hotspot) for evoking MEPs in the precentral hand knob. Individual precentral hotspot location varied along the rostro-caudal axis. Individuals with a more rostral location had longer MEP latencies. Spatiotemporal "hotspot rostrality" was associated with higher precentral myelin-related signals, stronger movement-related activation of PMd in the precentral crown, and higher temporal precision during paced finger tapping. Together, our multimodal mapping approach provides first-time evidence for behaviourally relevant, structural and functional phenotypic variation in the crown of human precentral motor hand knob. The results have important implications for physiological and interventional TMS studies targeting the precentral hand knob.

neuroscience↗

bioRxiv2019

Comparing and Validating Automated Tools for Individualized Electric Field Simulations in the Human Head

Comparing electric field simulations from individualized head models against in-vivo recordings is important for direct validation of computational field modeling for transcranial brain stimulation and brain mapping techniques such as electro- and magnetoencephalography. This also helps to improve simulation accuracy by pinning down the factors having the largest influence on the simulations. Here we compare field simulations from four different automated pipelines, against intracranial voltage recordings in an existing dataset of 14 epilepsy patients. We show that ignoring uncertainty in the simulations leads to a strong bias in the estimated linear relationship between simulated and measured fields. In addition, even though the simulations between the pipelines differ notably, this is not reflected in the correlation with the measurements. We discuss potential reasons for this apparent mismatch and propose a new Bayesian regression analysis of the data that yields unbiased estimates enabling robust conclusions to be reached.

bioengineering↗

bioRxiv2019

A novel approach to localize cortical TMS effects

Despite the widespread use of transcranial magnetic stimulation (TMS), the precise cortical location underlying the physiological and behavioral stimulation effects are still only coarsely known. So far, mapping strategies rely on center of gravity approaches and therefore localize the stimulated cortical site only approximately and indirectly. Focusing on the motor cortex, we present a novel method to reliably determine the effectively stimulated cortical site at the individual subject level. The approach combines measurements of motor evoked potentials (MEPs) at different coil positions and orientations with numerical modeling of induced electric fields. We identify sharply bounded cortical areas around the gyral crowns and rims of the motor hand area as the origin of MEPs and show that the tangential component and the magnitude of the electric field is most relevant for the observed effect. To validate our approach, we determined motor thresholds for coil positions and orientations for the predicted cortical target. Our methods allows for the identification of optimal coil positions and orientations. Moreover, we used extensive uncertainty and sensitivity analyses to verify the robustness of the method and identify the most critical model parameters. Our generic approach improves the localization of the cortex area stimulated by TMS and may be transferred to other modalities such as language mapping.

neuroscience↗

bioRxiv2019

Efficient Electric Field Simulations for Transcranial Brain Stimulation

ObjectiveTranscranial magnetic stimulation (TMS) and transcranial electric stimulation (TES) modulate brain activity non-invasively by generating electric fields either by electromagnetic induction or by injecting currents via skin electrodes. Numerical simulations based on anatomically detailed head models of the TMS and TES electric fields can help us to understand and optimize the spatial stimulation pattern in the brain. However, most realistic simulations are still slow, and their numerical accuracy and the factors that influence it have not been evaluated in detail so far. ApproachWe present and validate a new implementation of the Finite Element Method (FEM) for TMS and TES that is based on modern algorithms and libraries. We also evaluate the convergence of the simulations and give estimates for the discretization errors. Main resultsComparisons with analytical solutions for spherical head models validate our new FEM implementation. It is five to ten times faster than previous implementations. The convergence results suggest that accurately capturing the tissue geometry in addition to choosing a sufficiently high mesh density is of fundamental importance for accurate simulations. SignificanceThe new implementation allows for a substantial increase in computational efficiency of TMS and TES simulations. This is especially relevant for applications such as the systematic assessment of model uncertainty and the optimization of multi-electrode TES montages. The results of our systematic error analysis allow the user to select the best tradeoff between model resolution and simulation speed for a specific application. The new FEM code will be made openly available as a part of our open-source software SimNIBS 3.0.

bioengineering↗

bioRxiv2018

SimNIBS 2.1: A Comprehensive Pipeline for Individualized Electric Field Modelling for Transcranial Brain Stimulation

Numerical simulation of the electric fields induced by Non-Invasive Brain Stimulation (NIBS), using realistic anatomical head models has gained interest in recent years for understanding the NIBS effects in individual subjects. Although automated tools for generating the head models and performing the electric field simulations have become available, individualized modelling is still not standard practice in NIBS studies. This is likely partly explained by the lack of robustness and usability of the previously available software tools, and partly by the still developing understanding of the link between physiological effects and electric field distributions in the brain. To facilitate individualized modelling in NIBS, we have introduced the SimNIBS (Simulation of NIBS) software package, providing easy-to-use automated tools for electric field modelling. In this article, we give an overview of the modelling pipeline in SimNIBS 2.1, with step-by-step examples of how to run a simulation. Furthermore, we demonstrate a set of scripts for extracting average electric fields for a group of subjects, and finally demonstrate the accuracy of automated placement of standard electrode montages on the head model. SimNIBS 2.1 is freely available at www.simnibs.org.

bioengineering↗

bioRxiv2018

The non-transcranial TMS-evoked potential is an inherent source of ambiguity in TMS-EEG studies

Transcranial Magnetic Stimulation (TMS) excites populations of neurons in the stimulated cortex, and the resulting activation may spread to connected brain regions. The distributed cortical response can be recorded with electroencephalography (EEG). Since TMS also stimulates peripheral sensory and motor axons and generates a loud \"click\" sound, the TMS-evoked EEG potential (TEP) not only reflects neural activity induced by transcranial neuronal excitation but also neural activity reflecting somatosensory and auditory processing. In 17 healthy young individuals, we systematically assessed the contribution of multisensory peripheral stimulation to TEPs using a TMS-compatible EEG system. Real TMS was delivered with a figure-of-eight coil over the left para-median posterior parietal cortex or superior frontal gyrus with the coil being oriented perpendicularly or in parallel to the target gyrus. We also recorded the EEG responses evoked by sham stimulation over the posterior parietal and superior frontal cortex, mimicking the auditory and somatosensory sensations evoked by real TMS. We applied state-of-the-art procedures to attenuate somatosensory and auditory confounds during real TMS, including the placement of a foam layer underneath the coil and auditory noise masking. Despite these precautions, the temporal and spatial features of the cortical potentials evoked by real TMS at the prefrontal and parietal site closely resembled the cortical potentials evoked by realistic sham TMS, both for early and late TEP components. Our findings stress the need to include a peripheral multisensory control stimulation in the study design to enable a dissociation between truly transcranial and non-transcranial components of TEPs.

neuroscience↗