Elucidating the mechanisms and loci of neuronal excitation by transcranial magnetic stimulation using a finite element model of a cortical sulcus

Transcranial Magnetic Stimulation Facilitates Neural Speech Decoding

Transcranial magnetic stimulation (TMS) has been widely used to study the mechanisms that underlie motor output. Yet, the extent to which TMS acts upon the cortical neurons implicated in volitional motor commands and the focal limitations of TMS remain subject to debate. Previous research links TMS to improved subject performance in behavioral tasks, including a bias in phoneme discrimination. Our study replicates this result, which implies a causal relationship between electro-magnetic stimulation and psychomotor activity, and tests whether TMS-facilitated psychomotor activity recorded via electroencephalography (EEG) may thus serve as a superior input for neural decoding. First, we illustrate that site-specific TMS elicits a double dissociation in discrimination ability for two phoneme categories. Next, we perform a classification analysis on the EEG signals recorded during TMS and find a dissociation between the stimulation site and decoding accuracy that parallels the behavioral results. We observe weak to moderate evidence for the alternative hypothesis in a Bayesian analysis of group means, with more robust results upon stimulation to a brain region governing multiple phoneme features. Overall, task accuracy was a significant predictor of decoding accuracy for phoneme categories (F(1,135) = 11.51, p < 0.0009) and individual phonemes (F(1,119) = 13.56, p < 0.0003), providing new evidence for a causal link between TMS, neural function, and behavior.

How conductivity boundaries influence the electric field induced by transcranial magnetic stimulation in in vitro experiments

BACKGROUND

Although transcranial magnetic stimulation (TMS) has become a valuable method for non-invasive brain stimulation, the cellular basis of TMS activation of neurons is still not fully understood. In vitro preparations have been used to understand the biophysical mechanisms of TMS, but in many cases these studies have encountered substantial difficulties in activating neurons.

OBJECTIVE/HYPOTHESIS

The hypothesis of this work is that conductivity boundaries can have large effects on the electric field in commonly used in vitro preparations. Our goal was to analyze the resulting difficulties in in vitro TMS using a simulation study, using a charge-based boundary element model.

METHODS

We decomposed the total electric field into the sum of the primary electric field, which only depends on coil geometry and current, and the secondary electric field arising from conductivity boundaries, which strongly depends on tissue and chamber geometry. We investigated the effect of the conductivity boundaries on the electric field strength for a variety of in vitro experimental settings to determine the sources of difficulty.

RESULTS

We showed that conductivity boundaries can have large effects on the electric field in in vitro preparations. Depending on the geometry of the air-saline and the saline-tissue interfaces, the secondary electric field can significantly enhance, or attenuate the primary electric field, resulting in a much stronger or weaker total electric field inside the tissue; we showed this using a realistic preparation. Submerged chambers are generally much more efficient than interface chambers since the secondary field due to the thin film of saline covering the tissue in the interface chamber opposes the primary field and significantly reduces the total field in the tissue placed in the interface chamber. The relative dimensions of the chamber and the TMS coil critically determine the total field; the popular setup with a large coil and a small chamber is particularly sub-optimal because the secondary field due to the air-chamber boundary opposes the primary field, thereby attenuating the total field. The form factor (length vs width) of the tissue in the direction of the induced field can be important since a relatively narrow tissue enhances the total field at the saline-tissue boundary.

CONCLUSIONS

Overall, we found that the total electric field in the tissue is higher in submerged chambers, higher if the chamber size is larger than the coil and if the shorter tissue dimension is in the direction of the electric field. Decomposing the total field into the primary and secondary fields is useful for designing in vitro experiments and interpreting the results.

A systematic review and meta-analysis of the preclinical and clinical results of low-field magnetic stimulation in cognitive disorders

Cognitive disorders such as major depressive disorder and bipolar disorder severely compromise brain function and neuronal activity. Treatments to restore cognitive abilities can have severe side effects due to their intense and excitatory nature, in addition to the fact that they are expensive and invasive. Low-field magnetic stimulation (LFMS) is a novel non-invasive proposed treatment for cognitive disorders. It repairs issues in the brain by altering deep cortical areas with treatments of low-intensity magnetic stimulation. This paper aims to summarize the current literature on the effects and results of LFMS in cognitive disorders. We developed a search strategy to identify relevant studies utilizing LFMS and systematically searched eight scientific databases. Our review suggests that LFMS could be a viable and effective treatment for multiple cognitive disorders, especially major depressive disorder. Additionally, longer, more frequent, and more personalized LFMS treatments tend to be more efficacious.

A review of algorithms and software for real-time electric field modeling techniques for transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a device-based neuromodulation technique increasingly used to treat brain diseases. Electric field (E-field) modeling is an important technique in several TMS clinical applications, including the precision stimulation of brain targets with accurate stimulation density for the treatment of mental disorders and the localization of brain function areas for neurosurgical planning. Classical methods for E-field modeling usually take a long computation time. Fast algorithms are usually developed with significantly lower spatial resolutions that reduce the prediction accuracy and limit their usage in real-time or near real-time TMS applications. This review paper discusses several modern algorithms for real-time or near real-time TMS E-field modeling and their advantages and limitations. The reviewed methods include techniques such as basis representation techniques and deep neural-network-based methods. This paper also provides a review of software tools that can integrate E-field modeling with navigated TMS, including a recent software for real-time navigated E-field mapping based on deep neural-network models.

Field recordings of transcranial magnetic stimulation in human brain postmortem models

Introduction

The ability of repetitive transcranial magnetic stimulation (rTMS) to deliver a magnetic field (MF) in deep brain targets is debated and poorly documented.

Objective

To quantify the decay of MF in the human brain.

Methods

Magnetic field was generated by single pulses of TMS delivered at maximum intensity using a flat or angulated coil. Magnetic field was recorded by a 3D-magnetic probe. Decay was measured in the air using both coils and in the head of 10 postmortem human heads with the flat coil being positioned tangential to the scalp. Magnetic field decay was interpreted as a function of distance to the coil for 6 potential brain targets of noninvasive brain stimulation: the primary motor cortex (M1, mean depth: 28.5 mm), dorsolateral prefrontal cortex (DLPFC: 28 mm), secondary somatosensory cortex (S2: 35.5 mm), posterior and anterior insulae (PI: 38.5 mm; AI: 43.5 mm), and midcingulate cortex (MCC: 57.5 mm).

Results

In air, the maximal MF intensities at coil center were 0.88 and 0.77 T for the flat and angulated coils, respectively. The maximal intracranial MF intensity in the cadaver model was 0.34 T, with a ∼50% decay at 15 mm and a ∼75% MF decay at 30 mm. The decay of the MF in air was similar for the flat coil and significantly less attenuated with the angulated coil (a ∼50% decay at 20 mm and a ∼75% MF decay at 45 mm).

Conclusions

Transcranial magnetic stimulation coil MFs decay in brain structures similarly as in air, attenuation with distance being significantly lower with angulated coils. Reaching brain targets deeper than 20 mm such as the insula or Antérior Cingulate Cortex seems feasible only when using angulated coils. The abacus of MF attenuation provided here can be used to adjust modalities of deep brain stimulation with rTMS in future research protocols.

Traumatic Brain Injury and Neuromodulation Techniques in Rehabilitation: A Scoping Review

BACKGROUND AND OBJECTIVES

Traumatic Brain Injury (TBI) is a condition in which an external force, usually a violent blow to the head, causes functional impairment in the brain. Neuromodulation techniques are thought to restore altered function in the brain, resulting in improved function and reduced symptoms. Brain stimulation can alter the firing of neurons, boost synaptic strength, alter neurotransmitters and excitotoxicity, and modify the connections in their neural networks. All these are potential effects on brain activity. Accordingly, this is a promising therapy for TBI. These techniques are flexible because they can target different brain areas and vary in frequency and amplitude. This review aims to investigate the recent literature about neuromodulation techniques used in the rehabilitation of TBI patients.

MATERIALS AND METHODS

The identification of studies was made possible by conducting online searches on PubMed, Web of Science, Cochrane, Embase, and Scopus databases. Studies published between 2013 and 2023 were selected. This review has been registered on OSF (JEP3S).

RESULTS

We have found that neuromodulation techniques can improve the rehabilitation process for TBI patients in several ways. Transcranial Magnetic Stimulation (TMS) can improve cognitive functions such as recall ability, neural substrates, and overall improved performance on neuropsychological tests. Repetitive TMS has the potential to increase neural connections in many TBI patients but not in all patients, such as those with chronic diffuse axonal damage.

CONCLUSIONS

This review has demonstrated that neuromodulation techniques are promising instruments in the rehabilitation field, including those affected by TBI. The efficacy of neuromodulation can have a significant impact on their lives and improve functional outcomes for TBI patients.

A Review of Formulations, Boundary Value Problems and Solutions for Numerical Computation of Transcranial Magnetic Stimulation Fields

Since the inception of the transcranial magnetic stimulation (TMS) technique, it has become imperative to numerically compute the distribution of the electric field induced in the brain. Various models of the coil-brain system have been proposed for this purpose. These models yield a set of formulations and boundary conditions that can be employed to calculate the induced electric field. However, the literature on TMS simulation presents several of these formulations, leading to potential confusion regarding the interpretation and contribution of each source of electric field. The present study undertakes an extensive compilation of widely utilized formulations, boundary value problems and numerical solutions employed in TMS fields simulations, analyzing the advantages and disadvantages associated with each used formulation and numerical method. Additionally, it explores the implementation strategies employed for their numerical computation. Furthermore, this work provides numerical expressions that can be utilized for the numerical computation of TMS fields using the finite difference and finite element methods. Notably, some of these expressions are deduced within the present study. Finally, an overview of some of the most significant results obtained from numerical computation of TMS fields is presented. The aim of this work is to serve as a guide for future research endeavors concerning the numerical simulation of TMS.

[The influence of tissue conductivity on the calculation of electric field in the transcranial magnetic stimulation head model]

In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.

Revisiting the Rotational Field TMS Method for Neurostimulation

Transcranial magnetic stimulation (TMS) is a non-invasive technique that has shown high efficacy in the treatment of major depressive disorder (MDD) and is increasingly utilized for various neuropsychiatric disorders. However, conventional TMS is limited to activating only a small fraction of neurons that have components parallel to the induced electric field. This likely contributes to the significant variability observed in clinical outcomes. A novel method termed rotational field TMS (rfTMS or TMS 360°) enables the activation of a greater number of neurons by reducing the sensitivity to orientation. Recruitment of a larger number of neurons offers the potential to enhance efficacy and reduce variability in the treatment of clinical indications for which neuronal recruitment and organization may play a significant role, such as MDD and stroke. The potential of the method remains to be validated in clinical trials. Here, we revisit and describe in detail the rfTMS method, its principles, mode of operation, effects on the brain, and potential benefits for clinical TMS.

Application of transcranial magnetic stimulation for major depression: Coil design and neuroanatomical variability considerations

High-frequency repeated transcranial magnetic stimulation (rTMS) as a treatment for major depressive disorder (MDD) has received FDA clearance for both the figure-of-8 coil (figure-8 coil) and the H1 coil. The FDA-cleared MDD protocols for both coils include high frequency (10-18 Hz) stimulation targeting the dorsolateral prefrontal cortex (dlPFC) at an intensity that is 120% of the right-hand resting motor threshold. Despite these similar parameters, the two coils generate distinct electrical fields (e-fields) which result in differences in the cortical stimulation they produce. Due to the differences in coil designs, the H1 coil induces a stimulation e-field that is broader and deeper than the one induced by the figure-8 coil. In this paper we review theoretical and clinical implications of these differences between the two coils and compare evidence of their safety and efficacy in treating MDD. We present the design principles of the coils, the challenges of identifying, finding, and stimulating the optimal brain target of each individual (both from functional and connectivity perspectives), and the possible implication of stimulating outside that target. There is only one study that performed a direct comparison between clinical effectiveness of the two coils, using the standard FDA-approved protocols in MDD patients. This study indicated clinical superiority of the H1 coil but did not measure long-term effects. Post-marketing data suggest that both coils have a similar safety profile in clinical practice, whereas effect size comparisons of the two respective FDA pivotal trials suggests that the H1 coil may have an advantage in efficacy. We conclude that further head-to-head experiments are needed, especially ones that will compare long-term effects and usage of similar temporal stimulation parameters and similar number of pulses.

Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation

OBJECTIVE

To develop a population-based biophysical model of motor-evoked potentials (MEPs) following transcranial magnetic stimulation (TMS).

METHODS

We combined an existing MEP model with population-based cortical modeling. Layer 2/3 excitatory and inhibitory neural populations, modeled with neural-field theory, are stimulated with TMS and feed layer 5 corticospinal neurons, which also couple directly but weakly to the TMS pulse. The layer 5 output controls mean motoneuron responses, which generate a series of single motor-unit action potentials that are summed to estimate a MEP.

RESULTS

A MEP waveform was generated comparable to those observed experimentally. The model captured TMS phenomena including a sigmoidal input-output curve, common paired pulse effects (short interval intracortical inhibition, intracortical facilitation, long interval intracortical inhibition) including responses to pharmacological interventions, and a cortical silent period. Changes in MEP amplitude following theta burst paradigms were observed including variability in outcome direction.

CONCLUSIONS

The model reproduces effects seen in common TMS paradigms.

SIGNIFICANCE

The model allows population-based modeling of changes in cortical dynamics due to TMS protocols to be assessed in terms of changes in MEPs, thus allowing a clear comparison between population-based modeling predictions and typical experimental outcome measures.

Restoration of arm and hand functions via noninvasive cervical cord neuromodulation after traumatic brain injury: a case study

Objectives: To investigate the effects of transcutaneous electrical stimulation (tES) on upper limb functional rehabilitation in a patient with traumatic brain injury (TBI), and to identify the optimum stimulation parameters of tES. Design: A preliminary case study. Methods: Two successive interventions: Phase I-voluntary physical training (vPT) and Phase II - tES along with vPT (tES+vPT). tES was delivered at C3 and C6 cervical regions. Clinical assessments presented the variation of muscle tone and motor functions, before and after each training phase, and evaluated at 1-month follow up after the last intervention. Results: Our results indicate that vPT alone contributed to a release of muscle spasticity of both arms of the patient with no significant improvement of hand function, while tES+vPT further reduced the spasticity of the left arm, and improved the voluntary motor function of both arms. The grip forces were also increased after the tES+vPT treatment. We found that 1 ms biphasic tES at 30 Hz produced optimum motor outputs. Conclusion: The study demonstrates, for the first time, the potential benefits of cervical tES in regard to improving upper limb motor functions in a patient with chronic TBI.

Examining state-dependent effects of transcranial direct current stimulation on visual search and executive function tasks

OBJECTIVE

The aim of this study was to evaluate whether the effects of transcranial direct current stimulation (tDCS) on cognitive performance are influenced by the state-dependency of targeted cortical regions.

METHODS

In a mixed within- and between-participants design, we targeted either the right parietal or left dorsolateral prefrontal cortex and measured effects on visual search versus inhibitory control (respectively). Critically, during active and sham stimulation, participants were exposed to an unrelated or task-congruent prime.

RESULTS

Analyses examined whether priming induced state-dependent changes in behavior on a subsequent visual search or inhibitory control task. Results demonstrated consistent support for the null hypothesis, with neither tDCS nor priming influencing behavioral outcomes.

CONCLUSIONS

This outcome does not provide direct support for state-dependency or activity-selectivity models of tDCS effects on cognitive outcomes. We discuss the possibility that behavioral patterns supporting these mechanistic models may only be found when the priming and outcome tasks share critical neurocognitive features. Overall, we found no evidence that offline (pretask) tDCS targeting the right parietal or left dorsolateral prefrontal induces reliable changes in visual search or inhibitory control behavior, and this pattern is not modulated by state-dependency induced by priming task-related activity.

Individual head models for estimating the TMS-induced electric field in rat brain

In transcranial magnetic stimulation (TMS), the initial cortical activation due to stimulation is determined by the state of the brain and the magnitude, waveform, and direction of the induced electric field (E-field) in the cortex. The E-field distribution depends on the conductivity geometry of the head. The effects of deviations from a spherically symmetric conductivity profile have been studied in detail in humans. In small mammals, such as rats, these effects are more pronounced due to their less spherical head, proportionally much thicker neck region, and overall much smaller size compared to the TMS coils. In this study, we describe a simple method for building individual realistically shaped head models for rats from high-resolution X-ray tomography images. We computed the TMS-induced E-field with the boundary element method and assessed the effect of head-model simplifications on the estimated E-field. The deviations from spherical symmetry have large, non-trivial effects on the E-field distribution: for some coil orientations, the strongest stimulation is in the brainstem even when the coil is over the motor cortex. With modelling prior to an experiment, such problematic coil orientations can be avoided for more accurate targeting.

Low-Field Magnetic Stimulation Accelerates the Differentiation of Oligodendrocyte Precursor Cells via Non-canonical TGF-β Signaling Pathways

Demyelination and oligodendrocyte loss are characteristic changes in demyelinating disorders. Low-field magnetic stimulation (LFMS) is a novel transcranial neuromodulation technology that has shown promising therapeutic potential for a variety of neuropsychiatric conditions. The cellular and molecular mechanisms of magnetic stimulation remain unclear. Previous studies mainly focused on the effects of magnetic stimulation on neuronal cells. Here we aimed to examine the effects of a gamma frequency LFMS on the glial progenitor cells. We used rat central glia-4 (CG4) cell line as an in vitro model. CG4 is a bipotential glial progenitor cell line that can differentiate into either oligodendrocyte or type 2-astrocyte. The cells cultured in a defined differentiation media were exposed to a 40-Hz LFMS 20 min daily for five consecutive days. We found that LFMS transiently elevated the level of TGF-β1 in the culture media in the first 24 h after the treatment. In correlation with the TGF-β1 levels, the percentage of cells possessing complex branches and expressing the late oligodendrocyte progenitor marker O4 was increased, indicating the accelerated differentiation of CG4 cells towards oligodendrocyte in LFMS-treated cultures. LFMS increased phosphorylation of Akt and Erk1/2 proteins, but not SMAD2/3. TGF-β1 receptor I specific inhibitor LY 364947 partially suppressed the effects of LFMS on differentiation and on levels of pAkt and pErk1/2, indicating that LFMS enhances the differentiation of oligodendrocyte progenitor cells via activation of non-canonical TGF-β-Akt and TGF-β-Erk1/2 pathways but not the canonical SMAD pathway. The data from this study reveal a novel mechanism of magnetic stimulation as a potential therapy for demyelination disorders.

Rotational field TMS: Comparison with conventional TMS based on motor evoked potentials and thresholds in the hand and leg motor cortices

BACKGROUND

Transcranial magnetic stimulation (TMS) is a rapidly expanding technology utilized in research and neuropsychiatric treatments. Yet, conventional TMS configurations affect primarily neurons that are aligned parallel to the induced electric field by a fixed coil, making the activation orientation-specific. A novel method termed rotational field TMS (rfTMS), where two orthogonal coils are operated with a 90° phase shift, produces rotation of the electric field vector over almost a complete cycle, and may stimulate larger portion of the neuronal population within a given brain area.

OBJECTIVE

To compare the physiological effects of rfTMS and conventional unidirectional TMS (udTMS) in the motor cortex.

METHODS

Hand and leg resting motor thresholds (rMT), and motor evoked potential (MEP) amplitudes and latencies (at 120% of rMT), were measured using a dual-coil array based on the H7-coil, in 8 healthy volunteers following stimulation at different orientations of either udTMS or rfTMS.

RESULTS

For both target areas rfTMS produced significantly lower rMTs and much higher MEPs than those induced by udTMS, for comparable induced electric field amplitude. Both hand and leg rMTs were orientation-dependent.

CONCLUSIONS

rfTMS induces stronger physiologic effects in targeted brain regions at significantly lower intensities. Importantly, given the activation of a much larger population of neurons within a certain brain area, repeated application of rfTMS may induce different neuroplastic effects in neural networks, opening novel research and clinical opportunities.

Modified cable equation incorporating transverse polarization of neuronal membranes for accurate coupling of electric fields

OBJECTIVE

We present a theory and computational methods to incorporate transverse polarization of neuronal membranes into the cable equation to account for the secondary electric field generated by the membrane in response to transverse electric fields. The effect of transverse polarization on nonlinear neuronal activation thresholds is quantified and discussed in the context of previous studies using linear membrane models.

APPROACH

The response of neuronal membranes to applied electric fields is derived under two time scales and a unified solution of transverse polarization is given for spherical and cylindrical cell geometries. The solution is incorporated into the cable equation re-derived using an asymptotic model that separates the longitudinal and transverse dimensions. Two numerical methods are proposed to implement the modified cable equation. Several common neural stimulation scenarios are tested using two nonlinear membrane models to compare thresholds of the conventional and modified cable equations.

MAIN RESULTS

The implementations of the modified cable equation incorporating transverse polarization are validated against previous results in the literature. The test cases show that transverse polarization has limited effect on activation thresholds. The transverse field only affects thresholds of unmyelinated axons for short pulses and in low-gradient field distributions, whereas myelinated axons are mostly unaffected.

SIGNIFICANCE

The modified cable equation captures the membrane's behavior on different time scales and models more accurately the coupling between electric fields and neurons. It addresses the limitations of the conventional cable equation and allows sound theoretical interpretations. The implementation provides simple methods that are compatible with current simulation approaches to study the effect of transverse polarization on nonlinear membranes. The minimal influence by transverse polarization on axonal activation thresholds for the nonlinear membrane models indicates that predictions of stronger effects in linear membrane models with a fixed activation threshold are inaccurate. Thus, the conventional cable equation works well for most neuroengineering applications, and the presented modeling approach is well suited to address the exceptions.

Coupling Magnetically Induced Electric Fields to Neurons: Longitudinal and Transverse Activation

We present a theory and computational models to couple the electric field induced by magnetic stimulation to neuronal membranes. Based on the characteristics of magnetically induced electric fields and the modified cable equation that we developed previously, quasipotentials are derived as a simple and accurate approximation for coupling of the electric fields to neurons. The conventional and modified cable equations are used to simulate magnetic stimulation of long peripheral nerves by circular and figure-8 coils. Activation thresholds are obtained over a range of lateral and vertical coil positions for two nonlinear membrane models representing unmyelinated and myelinated straight axons and also for undulating myelinated axons. For unmyelinated straight axons, the thresholds obtained with the modified cable equation are significantly lower due to transverse polarization, and the spatial distributions of thresholds as a function of coil position differ significantly from predictions by the activating function. However, the activation thresholds of unmyelinated axons obtained with either cable equation are very high and beyond the output capabilities of conventional magnetic stimulators. For myelinated axons, threshold values are similar for both cable equations and within the range of magnetic stimulators. Whereas the transverse field contributes negligibly to the activation thresholds of myelinated fibers, axonal undulation can significantly increase or decrease thresholds depending on coil position. The analysis provides a rigorous theoretical foundation and implementation methods for the use of the cable equation to model neuronal response to magnetically induced electric fields. Experimentally observed stimulation with the electric fields perpendicular to the nerve trunk cannot be explained by transverse polarization and is likely due to nerve fiber undulation and other geometrical inhomogeneities.

Direct Electrical Stimulation in Electrocorticographic Brain-Computer Interfaces: Enabling Technologies for Input to Cortex

Electrocorticographic brain computer interfaces (ECoG-BCIs) offer tremendous opportunities for restoring function in individuals suffering from neurological damage and for advancing basic neuroscience knowledge. ECoG electrodes are already commonly used clinically for monitoring epilepsy and have greater spatial specificity in recording neuronal activity than techniques such as electroencephalography (EEG). Much work to date in the field has focused on using ECoG signals recorded from cortex as control outputs for driving end effectors. An equally important but less explored application of an ECoG-BCI is directing input into cortex using ECoG electrodes for direct electrical stimulation (DES). Combining DES with ECoG recording enables a truly bidirectional BCI, where information is both read from and written to the brain. We discuss the advantages and opportunities, as well as the barriers and challenges presented by using DES in an ECoG-BCI. In this article, we review ECoG electrodes, the physics and physiology of DES, and the use of electrical stimulation of the brain for the clinical treatment of disorders such as epilepsy and Parkinson’s disease. We briefly discuss some of the translational, regulatory, financial, and ethical concerns regarding ECoG-BCIs. Next, we describe the use of ECoG-based DES for providing sensory feedback and for probing and modifying cortical connectivity. We explore future directions, which may draw on invasive animal studies with penetrating and surface electrodes as well as non-invasive stimulation methods such as transcranial magnetic stimulation (TMS). We conclude by describing enabling technologies, such as smaller ECoG electrodes for more precise targeting of cortical areas, signal processing strategies for simultaneous stimulation and recording, and computational modeling and algorithms for tailoring stimulation to each individual brain.

Localization of Sensorimotor Cortex Using Navigated Transcranial Magnetic Stimulation and Magnetoencephalography

The mapping of the sensorimotor cortex gives information about the cortical motor and sensory functions. Typical mapping methods are navigated transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG). The differences between these mapping methods are, however, not fully known. TMS center of gravities (CoGs), MEG somatosensory evoked fields (SEFs), corticomuscular coherence (CMC), and corticokinematic coherence (CKC) were mapped in ten healthy adults. TMS mapping was performed for first dorsal interosseous (FDI) and extensor carpi radialis (ECR) muscles. SEFs were induced by tactile stimulation of the index finger. CMC and CKC were determined as the coherence between MEG signals and the electromyography or accelerometer signals, respectively, during voluntary muscle activity. CMC was mapped during the activation of FDI and ECR muscles separately, whereas CKC was measured during the waving of the index finger at a rate of 3–4 Hz. The maximum CMC was found at beta frequency range, whereas maximum CKC was found at the movement frequency. The mean Euclidean distances between different localizations were within 20 mm. The smallest distance was found between TMS FDI and TMS ECR CoGs and longest between CMC FDI and CMC ECR sites. TMS-inferred localizations (CoGs) were less variable across participants than MEG-inferred localizations (CMC, CKC). On average, SEF locations were 8 mm lateral to the TMS CoGs (p < 0.01). No differences between hemispheres were found. Based on the results, TMS appears to be more viable than MEG in locating motor cortical areas.

Rewiring the Addicted Brain: Circuits-Based Treatment for Addiction

The advent of the noninvasive brain stimulation (NIBS) technique has paved the way for neural circuit-based treatments for addiction. Recently, evidence from both preclinical and clinical studies has evaluated the use of transcranial magnetic stimulation (TMS) as a safe and cost-effective therapeutic tool for substance use disorders (SUDs). Indeed, repetitive TMS impacts on neural activity inducing short- and long-term effects involving neuroplasticity mechanisms locally within the target area of stimulation and the network level throughout the brain. Here, we provide an integrated view of evidence highlighting the mechanisms of TMS-induced effects on modulating the maladaptive brain circuitry of addiction. We then review the preclinical and clinical findings suggesting rTMS as an effective interventional tool for the treatment of SUDs.

Modulating Applied Task Performance via Transcranial Electrical Stimulation

Basic and applied research are increasingly adopting transcranial electrical stimulation (tES) for modulating perceptual, cognitive, affective, and motor processes. Industry and defense applications of tES hold potential for accelerating training and knowledge acquisition and sustaining work-related performance in the face of fatigue, workload, and stress. This mini-review article describes the promises and perils of tES, and reviews research testing its influence on two broad applied areas: sustaining and dividing attention, and operating in virtual environments. Also included is a discussion of challenges related to viable mechanistic explanations for tES effectiveness, attempts at replication and consideration of null results, and the potential importance of individual differences in predicting tES influences on human performance. Finally, future research directions are proposed to address these challenges and help develop a fuller understanding of tES viability for enhancing real-world performance.

The Effects of Waveform and Current Direction on the Efficacy and Test-Retest Reliability of Transcranial Magnetic Stimulation

The pulse waveform and current direction of transcranial magnetic stimulation (TMS) influence its interactions with the neural substrate; however, their role in the efficacy and reliability of single- and paired-pulse TMS measures is not fully understood. We investigated how pulse waveform and current direction affect the efficacy and test-retest reliability of navigated, single- and paired-pulse TMS measures. 23 healthy adults (aged 18-35 years) completed two identical TMS sessions, assessing resting motor threshold (RMT), motor-evoked potentials (MEPs), cortical silent period (cSP), short- and long-interval intra-cortical inhibition (SICI and LICI), and intracortical facilitation (ICF) using either monophasic posterior-anterior (monoPA; n = 9), monophasic anterior-posterior (monoAP; n = 7), or biphasic (biAP-PA; n = 7) pulses. Averages of each TMS measure were compared across the three groups and intraclass correlation coefficients were calculated to assess test-retest reliability. RMT was the lowest and cSP was the longest with biAP-PA pulses, whereas MEP latency was the shortest with monoPA pulses. SICI and LICI had the largest effect with monoPA pulses, whereas only monoAP and biAP-PA pulses resulted in significant ICF. MEP amplitude was more reliable with either monoPA or monoAP than with biAP-PA pulses. LICI was the most reliable with monoAP pulses, whereas ICF was the most reliable with biAP-PA pulses. Waveform/current direction influenced RMT, MEP latency, cSP, SICI, LICI, and ICF, as well as the reliability of MEP amplitude, LICI, and ICF. These results show the importance of considering TMS pulse parameters for optimizing the efficacy and reliability of TMS neurophysiologic measures.

Modulating Spatial Processes and Navigation via Transcranial Electrical Stimulation: A Mini Review

Transcranial electrical stimulation (tES) uses low intensity current to alter neuronal activity in superficial cortical regions, and has gained popularity as a tool for modulating several aspects of perception and cognition. This mini-review article provides an overview of tES and its potential for modulating spatial processes underlying successful navigation, including spatial attention, spatial perception, mental rotation and visualization. Also considered are recent advances in empirical research and computational modeling elucidating several stable cortical-subcortical networks with dynamic involvement in spatial processing and navigation. Leveraging these advances may prove valuable for using tES, particularly transcranial direct and alternating current stimulation (tDCS/tACS), to indirectly target subcortical brain regions by altering neuronal activity in distant yet functionally connected cortical areas. We propose future research directions to leverage these advances in human neuroscience.

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.

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.

Treatment of depression with low-strength transcranial pulsed electromagnetic fields: A mechanistic point of view

BACKGROUND

Mood disorders constitute a high burden for both patients and society. Notwithstanding the large arsenal of available treatment options, a considerable group of patients does not remit on current antidepressant treatment. There is an urgent need to develop alternative treatment strategies. Recently, low-strength transcranial pulsed electromagnetic field (tPEMF) stimulation has been purported as a promising strategy for such treatment-resistant depression (TRD). The mode of action of this new technique is however largely unknown.

METHODS

We searched PubMed for literature reports on the effects of tPEMF and for information regarding its working mechanism and biological substrate.

RESULTS

Most studies more or less connect with the major hypotheses of depression and concern the effects of tPEMF on brain metabolism, neuronal connectivity, brain plasticity, and the immune system. Relatively few studies paid attention to the possible chronobiologic effects of electromagnetic fields.

LIMITATIONS

We reviewed the literature of a new and still developing field. Some of the reports involved translational studies, which inevitably limits the reach of the conclusions.

CONCLUSION

Weak magnetic fields influence divergent neurobiological processes. The antidepressant effect of tPEMF may be specifically attributable to its effects on local brain activity and connectivity.

The effect of current flow direction on motor hot spot allocation by transcranial magnetic stimulation

The objective of this study was to investigate the significance of pulse configurations and current direction for corticospinal activation using transcranial magnetic stimulation (TMS). In 11 healthy subjects (8 female), a motor map for the motor evoked potentials (MEPs) recorded from the first dorsal interosseus (FDI), abductor digiti minimi (ADM), extensor carpi radialis, and biceps brachii (BB) muscles of the dominant side was established. Starting from a manually determined hot spot of the FDI representation, we measured MEPs at equal oriented points on an hexagonal grid, with 7 MEPs recorded at each point, using the following pulse configurations: posteriorly directed monophasic (Mo-P), anteriorly directed monophasic (Mo-A), biphasic with the more relevant second cycle oriented posteriorly (Bi-P) as well as a reversed biphasic condition (Bi-A). For each pulse configuration, a hot spot was determined and a center of gravity (CoG) was calculated. We found that the factor current direction had an effect on location of the CoG-adjusted hot spot in the cranio-caudal axis but not in the latero-medial direction with anteriorly directed pulses locating the CoG more anteriorly and vice versa. In addition, the CoG for the FDI was more laterally than the cortical representations for the abductor digiti minimi (ADM) and extensor carpi radialis (ECR) which were registered as well. The results indicate that direction of the current pulse should be taken into account for determination of the motor representation of a muscle by TMS.

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.

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.

Computational modeling of neurostimulation in brain diseases

Neurostimulation as a therapeutic tool has been developed and used for a range of different diseases such as Parkinson's disease, epilepsy, and migraine. However, it is not known why the efficacy of the stimulation varies dramatically across patients or why some patients suffer from severe side effects. This is largely due to the lack of mechanistic understanding of neurostimulation. Hence, theoretical computational approaches to address this issue are in demand. This chapter provides a review of mechanistic computational modeling of brain stimulation. In particular, we will focus on brain diseases, where mechanistic models (e.g., neural population models or detailed neuronal models) have been used to bridge the gap between cellular-level processes of affected neural circuits and the symptomatic expression of disease dynamics. We show how such models have been, and can be, used to investigate the effects of neurostimulation in the diseased brain. We argue that these models are crucial for the mechanistic understanding of the effect of stimulation, allowing for a rational design of stimulation protocols. Based on mechanistic models, we argue that the development of closed-loop stimulation is essential in order to avoid inference with healthy ongoing brain activity. Furthermore, patient-specific data, such as neuroanatomic information and connectivity profiles obtainable from neuroimaging, can be readily incorporated to address the clinical issue of variability in efficacy between subjects. We conclude that mechanistic computational models can and should play a key role in the rational design of effective, fully integrated, patient-specific therapeutic brain stimulation.

The coil orientation dependency of the electric field induced by TMS for M1 and other brain areas

Background

The effectiveness of transcranial magnetic stimulation (TMS) depends highly on the coil orientation relative to the subject’s head. This implies that the direction of the induced electric field has a large effect on the efficiency of TMS. To improve future protocols, knowledge about the relationship between the coil orientation and the direction of the induced electric field on the one hand, and the head and brain anatomy on the other hand, seems crucial. Therefore, the induced electric field in the cortex as a function of the coil orientation has been examined in this study.

Methods

The effect of changing the coil orientation on the induced electric field was evaluated for fourteen cortical targets. We used a finite element model to calculate the induced electric fields for thirty-six coil orientations (10 degrees resolution) per target location. The effects on the electric field due to coil rotation, in combination with target site anatomy, have been quantified.

Results

The results confirm that the electric field perpendicular to the anterior sulcal wall of the central sulcus is highly susceptible to coil orientation changes and has to be maximized for an optimal stimulation effect of the motor cortex. In order to obtain maximum stimulation effect in areas other than the motor cortex, the electric field perpendicular to the cortical surface in those areas has to be maximized as well. Small orientation changes (10 degrees) do not alter the induced electric field drastically.

Conclusions

The results suggest that for all cortical targets, maximizing the strength of the electric field perpendicular to the targeted cortical surface area (and inward directed) optimizes the effect of TMS. Orienting the TMS coil based on anatomical information (anatomical magnetic resonance imaging data) about the targeted brain area can improve future results. The standard coil orientations, used in cognitive and clinical neuroscience, induce (near) optimal electric fields in the subject-specific head model in most cases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-015-0036-2) contains supplementary material, which is available to authorized users.

Subject-Specific Multiscale Modeling to Investigate Effects of Transcranial Magnetic Stimulation

OBJECTIVE

Transcranial magnetic stimulation (TMS) is an effective intervention in noninvasive neuromodulation used to treat a number of neurophysiological disorders. Predicting the spatial extent to which neural tissue is affected by TMS remains a challenge. The goal of this study was to develop a computational model to predict specific locations of neural tissue that are activated during TMS. Using this approach, we assessed the effects of changing TMS coil orientation and waveform.

MATERIALS AND METHODS

We integrated novel techniques to develop a subject-specific computational model, which contains three main components: 1) a figure-8 coil (Magstim, Magstim Company Limited, Carmarthenshire, UK); 2) an electromagnetic, time-dependent, nonhomogeneous, finite element model of the whole head; and 3) an adaptation of a previously published pyramidal cell neuron model. We then used our modeling approach to quantify the spatial extent of affected neural tissue for changes in TMS coil rotation and waveform.

RESULTS

We found that our model shows more detailed predictions than previously published models, which underestimate the spatial extent of neural activation. Our results suggest that fortuitous sites of neural activation occur for all tested coil orientations. Additionally, our model predictions show that excitability of individual neural elements changes with a coil rotation of ±15°.

CONCLUSIONS

Our results indicate that the extent of neuromodulation is more widespread than previous published models suggest. Additionally, both specific locations in cortex and the extent of stimulation in cortex depend on coil orientation to within ±15° at a minimum. Lastly, through computational means, we are able to provide insight into the effects of TMS at a cellular level, which is currently unachievable by imaging modalities.

Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS

In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron's local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract's position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values.

Uncertainty quantification in transcranial magnetic stimulation via high-dimensional model representation

A computational framework for uncertainty quantification in transcranial magnetic stimulation (TMS) is presented. The framework leverages high-dimensional model representations (HDMRs), which approximate observables (i.e., quantities of interest such as electric (E) fields induced inside targeted cortical regions) via series of iteratively constructed component functions involving only the most significant random variables (i.e., parameters that characterize the uncertainty in a TMS setup such as the position and orientation of TMS coils, as well as the size, shape, and conductivity of the head tissue). The component functions of HDMR expansions are approximated via a multielement probabilistic collocation (ME-PC) method. While approximating each component function, a quasi-static finite-difference simulator is used to compute observables at integration/collocation points dictated by the ME-PC method. The proposed framework requires far fewer simulations than traditional Monte Carlo methods for providing highly accurate statistical information (e.g., the mean and standard deviation) about the observables. The efficiency and accuracy of the proposed framework are demonstrated via its application to the statistical characterization of E-fields generated by TMS inside cortical regions of an MRI-derived realistic head model. Numerical results show that while uncertainties in tissue conductivities have negligible effects on TMS operation, variations in coil position/orientation and brain size significantly affect the induced E-fields. Our numerical results have several implications for the use of TMS during depression therapy: 1) uncertainty in the coil position and orientation may reduce the response rates of patients; 2) practitioners should favor targets on the crest of a gyrus to obtain maximal stimulation; and 3) an increasing scalp-to-cortex distance reduces the magnitude of E-fields on the surface and inside the cortex.

Neurostimulation for traumatic brain injury

Traumatic brain injury (TBI) remains a significant public health problem and is a leading cause of death and disability in many countries. Durable treatments for neurological function deficits following TBI have been elusive, as there are currently no FDA-approved therapeutic modalities for mitigating the consequences of TBI. Neurostimulation strategies using various forms of electrical stimulation have recently been applied to treat functional deficits in animal models and clinical stroke trials. The results from these studies suggest that neurostimulation may augment improvements in both motor and cognitive deficits after brain injury. Several studies have taken this approach in animal models of TBI, showing both behavioral enhancement and biological evidence of recovery. There have been only a few studies using deep brain stimulation (DBS) in human TBI patients, and future studies are warranted to validate the feasibility of this technique in the clinical treatment of TBI. In this review, the authors summarize insights from studies employing neurostimulation techniques in the setting of brain injury. Moreover, they relate these findings to the future prospect of using DBS to ameliorate motor and cognitive deficits following TBI.