Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation

Background: Transcranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer. Objective: To develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region. Methods: We designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand. Results: The transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum. Conclusion: The developed mTMS system enables electronically targeted brain stimulation within a cortical region. (c) 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer reviewe

Transcranial electrical stimulation motor threshold can estimate individualized tDCS dosage from reverse-calculation electric-field modeling

Background Unique amongst brain stimulation tools, transcranial direct current stimulation (tDCS) currently lacks an easy or widely implemented method for individualizing dosage. Objective We developed a method of reverse-calculating electric-field (E-field) models based on Magnetic Resonance Imaging (MRI) scans that can estimate individualized tDCS dose. We also evaluated an MRI-free method of individualizing tDCS dose by measuring transcranial magnetic stimulation (TMS) motor threshold (MT) and single pulse, suprathreshold transcranial electrical stimulation (TES) MT and regressing it against E-field modeling. Key assumptions of reverse-calculation E-field modeling, including the size of region of interest (ROI) analysis and the linearity of multiple E-field models were also tested. Methods In 29 healthy adults, we acquired TMS MT, TES MT, and anatomical T1-weighted MPRAGE MRI scans with a fiducial marking the motor hotspot. We then computed a “reverse-calculated tDCS dose” of tDCS applied at the scalp needed to cause a 1.00 V/m E-field at the cortex. Finally, we examined whether the predicted E-field values correlated with each participant’s measured TMS MT or TES MT. Results We were able to determine a reverse-calculated tDCS dose for each participant using a 5 × 5 x 5 voxel grid region of interest (ROI) approach (average = 6.03 mA, SD = 1.44 mA, range = 3.75–9.74 mA). The Transcranial Electrical Stimulation MT, but not the Transcranial Magnetic Stimulation MT, significantly correlated with the ROI-based reverse-calculated tDCS dose determined by E-field modeling (R2= 0.45, p \u3c 0.001). Conclusions Reverse-calculation E-field modeling, alone or regressed against TES MT, shows promise as a method to individualize tDCS dose. The large range of the reverse-calculated tDCS doses between subjects underscores the likely need to individualize tDCS dose. Future research should further examine the use of TES MT to individually dose tDCS as an MRI-free method of dosing tDCS

Water and Brain Function: Effects of Hydration Status on Neurostimulation and Neurorecording

Introduction: TMS and EEG are used to study normal neurophysiology, diagnose, and treat clinical neuropsychiatric conditions, but can produce variable results or fail. Both techniques depend on electrical volume conduction, and thus brain volumes. Hydration status can affect brain volumes and functions (including cognition), but effects on these techniques are unknown. We aimed to characterize the effects of hydration on TMS, EEG, and cognitive tasks. Methods: EEG and EMG were recorded during single-pulse TMS, paired-pulse TMS, and cognitive tasks from 32 human participants on dehydrated (12-hour fast/thirst) and rehydrated (1 Liter oral water ingestion in 1 hour) testing days. Hydration status was confirmed with urinalysis. MEP, ERP, and network analyses were performed to examine responses at the muscle, brain, and higher-order functioning. Results: Rehydration decreased motor threshold (increased excitability) and shifted the motor hotspot. Significant effects on TMS measures occurred despite being re-localized and re-dosed to these new parameters. Rehydration increased SICF of the MEP, magnitudes of specific TEP peaks in inhibitory protocols, specific ERP peak magnitudes and reaction time during the cognitive task. Rehydration amplified nodal inhibition around the stimulation site in inhibitory paired-pulse networks and strengthened nodes outside the stimulation site in excitatory and CSP networks. Cognitive performance was not improved by rehydration, although similar performance was achieved with generally weaker network activity. Discussion: Results highlight differences between mild dehydration and rehydration. The rehydrated brain was easier to stimulate with TMS and produced larger responses to external and internal stimuli. This is explainable by the known physiology of body water dynamics, which encompass macroscopic and microscopic volume changes. Rehydration can shift 3D cortical positioning, decrease scalp cortex distance (bringing cortex closer to stimulator/recording electrodes), and cause astrocyte swelling-induced glutamate release. Conclusions: Previously unaccounted variables like osmolarity, astrocyte and brain volumes likely affect neurostimulation/neurorecording. Controlling for and carefully manipulating hydration may reduce variability and improve therapeutic outcomes of neurostimulation. Dehydration is common and produces less excitable circuits. Rehydration should offer a mechanism to macroscopically bring target cortical areas closer to an externally applied neurostimulation device to recruit greater volumes of tissue and microscopically favor excitability in the stimulated circuits

TMS combined with EEG: Recommendations and open issues for data collection and analysis

Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS−EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS−EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS−EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS−EEG covered all aspects that should be considered in TMS−EEG experiments, providing methodological recommendations (when possible) for effective TMS−EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS−EEG methodology and thus may promote standardization of experimental and computational procedures across groups

An artificial neural-network approach to identify motor hotspot for upper-limb based on electroencephalography: a proof-of-concept study

Abstract Background To apply transcranial electrical stimulation (tES) to the motor cortex, motor hotspots are generally identified using motor evoked potentials by transcranial magnetic stimulation (TMS). The objective of this study is to validate the feasibility of a novel electroencephalography (EEG)-based motor-hotspot-identification approach using a machine learning technique as a potential alternative to TMS. Methods EEG data were measured using 63 channels from thirty subjects as they performed a simple finger tapping task. Power spectral densities of the EEG data were extracted from six frequency bands (delta, theta, alpha, beta, gamma, and full) and were independently used to train and test an artificial neural network for motor hotspot identification. The 3D coordinate information of individual motor hotspots identified by TMS were quantitatively compared with those estimated by our EEG-based motor-hotspot-identification approach to assess its feasibility. Results The minimum mean error distance between the motor hotspot locations identified by TMS and our proposed motor-hotspot-identification approach was 0.22 ± 0.03cm, demonstrating the proof-of-concept of our proposed EEG-based approach. A mean error distance of 1.32 ± 0.15cm was measured when using only nine channels attached to the middle of the motor cortex, showing the possibility of practically using the proposed motor-hotspot-identification approach based on a relatively small number of EEG channels. Conclusion We demonstrated the feasibility of our novel EEG-based motor-hotspot-identification method. It is expected that our approach can be used as an alternative to TMS for motor hotspot identification. In particular, its usability would significantly increase when using a recently developed portable tES device integrated with an EEG device

Influence of sensorimotor µ rhythm phase and power on motor cortex excitability and plasticity induction, assessed with EEG-triggered TMS

In dieser Arbeit werden zwei Experimente vorgestellt, bei denen EEG-getriggerte transkranielle Magnetstimulation (TMS) an gesunden Probanden eingesetzt wurde, um die Rolle des sensomotorischen 8-14Hz µ-Rhythmus auf die kortikospinale Erregbarkeit (CSE) und die Induktion positiver Plastizität zu untersuchen. Unser Ziel war es, für Plastizitätsinduktion günstige Zeitpunkte im EEG zu identifizieren, um in Zukunft die Effektivität solcher zurzeit oft noch unzuverlässigen Anwendungen zu steigern. Unser EEG-TMS System interpretierte Oszillationen im EEG in Echtzeit und löste einen Stimulus aus, wenn bestimmte, vorher festgelegte Eigenschaften zutrafen. Die ‘Gehirnwellen’ im EEG entstehen durch synchronisierte Fluktuationen des Membranpotentials kortikaler Neurone, welche aufgrund ihrer intrakortikalen Kommunikationsfunktion wertvolle Informationen über neuronale Erregbarkeit vermitteln. Im Gegensatz zu “open-loop” TMS ermöglicht EEG-TMS nicht nur eine präzisere Erforschung der Funktion von Gehirnwellen, sondern auch die Umsetzung der gewonnenen Erkenntnisse in effizientere therapeutische Anwendungen. Speziell Oszillationen im Alpha-Frequenzbereich (8-14Hz) spielen eine bedeutsame Rolle, indem sie den Informationsfluss im Gehirn durch Hemmung aktuell irrelevanter Areale steuern, und zwar laut einer führenden Theorie als “asymmetrisch gepulste Inhibition” mit einem Maximum der Hemmung während der Hochpunkte (“Peaks”) und während hoher “Power” (∼ Amplitude). Der “µ-Rhythmus”, Wellen in alpha-Frequenz über dem sensomotorischen Kortex, scheint für diese Areale eine analoge Rolle wie das okzipitale Alpha für den visuellen Kortex zu spielen. Die CSE lässt sich durch die Amplitude der ausgelösten kontralateralen Muskelzuckungen (MEPs im EMG) quantifizieren. Im Vorexperiment erforschten wir den Einfluss der Power der µ-Wellen auf die CSE. 16 Teilnehmer wurden in einer Sitzung mit Einzelpuls-TMS des linken M1 stimuliert. Die Pulse wurden durch die momentane Power ausgelöst, 10 Dezile des individuellen µ-Powerspektrums wurden in pseudorandomisierter Reihenfolge angesteuert, verteilt auf 4 Stimulationsblöcke. Nach Berücksichtigung der “Inter-Trial-Intervalle” (ITIs, bekannter “Confounder”) und Normalisierung pro Block zeigten unsere Daten eine schwache positiv-lineare Korrelation zwischen µ Power und MEP-Amplitude, welche somit im Widerspruch zur angenommenen hemmenden Wirkung von µ steht, aber mittlerweile in mehreren anderen Studien repliziert wurde. Diese Diskrepanz kann z.B. durch eine tatsächlich fazilitatorische Wirkung erklärt werden, oder auch durch eine anatomisch dem sensorischen Kortex (S1) zuzuordnende Quelle der angesteuerten µ-Wellen, was über hem- 83mende Interneurone von S1 auf M1 zu einer ‘Vorzeichenumkehrung’ der Effektrichtung führen könnte. Weiterhin wird eine Abhängigkeit der ‘erregbarsten’ Power-Werte von der Stimulusstärke diskutiert. Im Hauptexperiment sollte mit ‘paarig-assoziativer Stimulation’ (PAS) (intervallsensitive Kombination von Elektrostimulation des rechten Nervus medianus mit TMS des linken M1) positive Plastizität (die Intervention überdauernde Stärkung von Synapsen) induziert werden. Dem ging ein umfangreiches “Screening” zur Identifikation geeigneter Probanden mit ausgeprägtem µ-Rhythmus (für präzise EEGTriggerung) voraus. Letztlich absolvierten 16 Teilnehmer je 4 Sitzungen (eine pro Trigger-Bedingung). Unsere Hypothese war hierbei, mehr Plastizität nach Stimulation während der Tiefpunkte (“Troughs”) als während der Peaks zu erzielen, also mehr synaptische ‘Formbarkeit’ während höherer Erregbarkeit. In Anbetracht der schwachen Ergebnisse des Vorexperiments sowie einer widersprüchlichen Beweislage bezüglich einer fazilitatorischen oder inhibitorischen Funktion wurden hohe und niedrige Power nicht explizit miteinander verglichen. TMS während PAS wurde durch (1) µ-Peaks, (2) µ-Troughs, (3) mittlere µ-Power und (4) open-loop getriggert. (3) und (4) dienten jeweils als Kontrollbedingung. PAS konnte, unabhängig von der EEG-Bedingung, keine signifikante Veränderung der MEP-Amplituden vom Ausgangswert hervorrufen. Die fehlende Wirkung könnte durch intra- und interindividuelle Schwankungen gewisser Parameter zwischen den Sitzungen erklärt werden (z.B. MEP-Ausgangswerte, absolute µ-Power während PAS), die sich jedoch nicht als systematische Confounder zwischen EEG-Bedingungen herausstellten. Die, im Gegensatz zu open-loop-Studien, schwankenden ITIs während der PAS könnten die Wirkung ebenfalls beeinträchtigt haben. Weiterhin waren zwei verschiedene Kortexareale (S1 und M1) am Protokoll beteiligt, was die Identifikation einer relevanten EEG-Eigenschaft erschwerte. Gegenwärtig rufen Plastizitäts-induzierende TMS-Protokolle in der Forschung und in Studien mit Schlaganfallpatienten schwankende und zeitlich begrenzte Wirkungen hervor. Durch EEG-Triggerung und / oder die Kombination mit klassischer Physiotherapie könnte eine verbesserte Effektivität und somit eine routinemäßige Anwendung erreicht werden. Trotz unserer negativen Ergebnisse bleibt EEG-getriggerte TMS ein vielversprechendes Instrument in Forschung und Klinik.This thesis presents two experiments employing real-time EEG-triggered transcranial magnetic stimulation (TMS) on healthy volunteers to investigate the role of sensorimotor 8-14Hz µ rhythm in EEG at rest on corticospinal excitability and induction of positive plasticity. We intended to identify brain states favorable to induction of positive plasticity to inform development of more efficient TMS protocols for clinical application e.g. in stroke patients. Applying TMS triggered by pre-determined EEG brain states in real time (opposed to open-loop TMS with post-hoc trial sorting) offers not only more precise research into the role of certain brain waves, but also translation into more efficient therapies. The membrane potential of superficial cortical neurons fluctuates rhythmically, visible as oscillations in surface EEG. Different brain areas seem to communicate through these synchronized fluctuations. ‘Brain waves’ therefore convey valuable information about the excitability of said areas. Oscillations in the alpha frequency range (8-14Hz) play a crucial role in this, gating information by inhibiting brain areas irrelevant to the current task. According to an influential hypothesis, this function is exerted as an ‘asymmetric pulsed inhibition’, with a maximum of inhibition during the peaks and during high alpha power (∼ amplitude). Sensorimotor alpha frequency waves (µ rhythm) play a similar role as the well-researched occipital alpha does for the visual cortex. The primary motor cortex (M1) provides a quantifiable measure of (corticospinal) excitability, the amplitude of TMS-elicited contralateral muscle twitches (appearing as MEPs in the EMG). The first experiment investigated the role of µ power for M1 excitability. 16 participants underwent one session of single-pulse TMS of the left M1, triggered by overall 10 individual power deciles in pseudorandomized order, partitioned into 4 ‘blocks’ of stimulation over time. The data revealed, after stratification for confounding inter-trial-intervals (ITIs) and normalization to block average, a weak positive linear relationship contrary to the proposed inhibitory role of µ, which has however since been replicated several times in other studies. This discrepancy can be explained e.g. by an in fact facilitatory nature of µ, by a postcentral and thus sensory cortical (S1) source of the targeted oscillations, reversing the inhibitory effect in sign to a facilitatory one through S1-to-M1 feedforward inhibition, or by a shift of most excitable power values dependent on stimulus strength. For the main experiment, we applied a paired associative stimulation (PAS) pro- 81tocol intended to induce positive plasticity (strengthening of synaptic connection outlasting the intervention), combining electrical stimulation of the right median nerve at the wrist with a TMS of the left M1 in a temporally sensitive manner. After an extensive screening to pre-select suitable subjects with a sufficiently strong µ rhythm (to ensure accurate performance of the real-time EEG targeting), 16 participants completed 4 sessions (one condition each). We expected to induce more positive plasticity during more excitable brain states, i.e., µ troughs rather than µ peaks. In light of our findings on µ power from the first experiment (weak influence as compared to ITIs and intrinsic variability over time) and overall contradictory evidence as to its (facilitatory versus inhibitory) role, high vs. low power were not explicitly compared. TMS during PAS was applied at (1) µ peaks, (2) µ troughs, (3) at medium µ powers and (4) open-loop. (3) and (4) both served as controls. The intervention failed to evoke a significant change in MEP amplitudes from baseline irrespective of condition. Possible explanations can be found in the intra- and interindividual variability of decisive parameters across sessions (e.g. baseline amplitudes and absolute µ powers during PAS), which however did not significantly depend on the targeted condition and were thus not true confounders. The number of sessions might still have introduced a further measure of variability. Varying PAS ITIs (due to EEG-triggering) could have also impeded plasticity induction, and the involvement of two cortical regions (S1 and M1) might have complicated the identification of one relevant brain state. Currently, plasticity-inducing TMS protocols in research and clinical trials evoke variable and transient effects. Improvements to enable routine application might come from EEG-triggering and/or combining with traditional motor training (physiotherapy). Regardless of our nil results in plasticity induction, EEG-triggered TMS remains a promising instrument in research and therapy

Accuracy and precision of navigated transcranial magnetic stimulation

Objective. Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil-head coregistration and the estimated E-field. Approach. By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models. Main results. Average total coregistration accuracies were in the range of 2.2-3.6 mm and 1 degrees; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5-1.9 mm/0.2-0.4 degrees and precisions 0.5-0.8 mm/0.1-0.2 degrees better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5 and 5.0 mm, 0.9 and 4.8 degrees, and 4.4 and 8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm/15 degrees/25% to about 2 mm/2 degrees/5% when increasing realism of the E-field model. Significance. The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.Peer reviewe

Manipulating neuronal communication by using low-intensity repetitive transcranial magnetic stimulation combined with electroencephalogram

Repetitive transcranial magnetic stimulation (rTMS) modulates ongoing brain rhythms by activating neuronal structures and evolving different neuronal mechanisms. In the current work, the role of stimulation strength and frequency for brain rhythms was studied. We hypothesized that a weak oscillating electric field induced by low-intensity rTMS could induce entrainment effects in the brain. To test the hypothesis, we conducted three separate experiments, in which we stimulated healthy human participants with rTMS. We individualized stimulation parameters using computational modeling of induced electric fields in the targets and individual frequency estimated by electroencephalography (EEG). We demonstrated the immediately induced entrainment of occipito-parietal and sensorimotor mu-alpha rhythm by low-intensity rTMS that resulted in phase and amplitude changes measured by EEG. Additionally, we found long-lasting corticospinal excitability changes in the motor cortex measured by motor evoked potentials from the corresponding musle.2021-11-2

Modern Developments in Transcranial Magnetic Stimulation (TMS) – Applications and Perspectives in Clinical Neuroscience

Transcranial magnetic stimulation (TMS) is being increasingly used in neuroscience and clinics. Modern advances include but are not limited to the combination of TMS with precise neuronavigation as well as the integration of TMS into a multimodal environment, e.g., by guiding the TMS application using complementary techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), diffusion tensor imaging (DTI), or magnetoencephalography (MEG). Furthermore, the impact of stimulation can be identified and characterized by such multimodal approaches, helping to shed light on the basic neurophysiology and TMS effects in the human brain. Against this background, the aim of this Special Issue was to explore advancements in the field of TMS considering both investigations in healthy subjects as well as patients

Clinical diagnostic utility of transcranial magnetic stimulation in neurological disorders. Updated report of an IFCN committee

The review provides a comprehensive update (previous report: Chen R, Cros D, Curra A, Di Lazzaro V, Lefaucheur JP, Magistris MR, et al. The clinical diagnostic utility of transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 2008;119(3):504–32) on clinical diagnostic utility of transcranial magnetic stimulation (TMS) in neurological diseases. Most TMS measures rely on stimulation of motor cortex and recording of motor evoked potentials. Paired-pulse TMS techniques, incorporating conventional amplitude-based and threshold tracking, have established clinical utility in neurodegenerative, movement, episodic (epilepsy, migraines), chronic pain and functional diseases. Cortical hyperexcitability has emerged as a diagnostic aid in amyotrophic lateral sclerosis. Single-pulse TMS measures are of utility in stroke, and myelopathy even in the absence of radiological changes. Short-latency afferent inhibition, related to central cholinergic transmission, is reduced in Alzheimer’s disease. The triple stimulation technique (TST) may enhance diagnostic utility of conventional TMS measures to detect upper motor neuron involvement. The recording of motor evoked potentials can be used to perform functional mapping of the motor cortex or in preoperative assessment of eloquent brain regions before surgical resection of brain tumors. TMS exhibits utility in assessing lumbosacral/cervical nerve root function, especially in demyelinating neuropathies, and may be of utility in localizing the site of facial nerve palsies. TMS measures also have high sensitivity in detecting subclinical corticospinal lesions in multiple sclerosis. Abnormalities in central motor conduction time or TST correlate with motor impairment and disability in MS. Cerebellar stimulation may detect lesions in the cerebellum or cerebello-dentatothalamo- motor cortical pathways. Combining TMS with electroencephalography, provides a novel method to measure parameters altered in neurological disorders, including cortical excitability, effective connectivity, and response complexity