To Transcranial Magnetic Stimulation Research Articles

Adapted Beamforming: A Robust and Flexible Approach for Removing Various Types of Artifacts from TMS-EEG Data.

Electroencephalogram (EEG) recorded as response to transcranial magnetic stimulation (TMS) can be highly informative of cortical reactivity and connectivity. Reliable EEG interpretation requires artifact removal as the TMS-evoked EEG can contain high-amplitude artifacts. Several methods have been proposed to uncover clean neuronal EEG responses. In practice, determining which method to select for different types of artifacts is often difficult. Here, we used a unified data cleaning framework based on beamforming to improve the algorithm selection and adaptation to the recorded signals. Beamforming properties are well understood, so they can be used to yield customized methods for EEG cleaning based on prior knowledge of the artifacts and the data. The beamforming implementations also cover, but are not limited to, the popular TMS-EEG cleaning methods: independent component analysis(ICA), signal-space projection (SSP), signal-space-projection-source-informed-reconstruction method (SSP-SIR), the source-estimate-utilizing noise-discarding algorithm (SOUND), data-driven Wiener filter (DDWiener), and the multiple-source approach. In addition to these established methods, beamforming provides a flexible way to derive novel artifact suppression algorithms by considering the properties of the recorded data. With simulated and measured TMS-EEG data, we show how to adapt the beamforming-based cleaning to different data and artifact types, namely TMS-evoked muscle artifacts, ocular artifacts, TMS-related peripheral responses, and channel noise. Importantly, beamforming implementations are fast to execute: We demonstrate how the SOUND algorithm becomes orders of magnitudes faster via beamforming. Overall, the beamforming-based spatial filtering framework can greatly enhance the selection, adaptability, and speed of EEG artifact removal.

TMS of parietal and occipital cortex locked to spontaneous transient large-scale brain states enhances natural oscillations in EEG

BackgroundFluctuating neuronal network states influence brain responses to transcranial magnetic stimulation (TMS). Our previous studies revealed that transient spontaneous bihemispheric brain states in the EEG, driven by oscillatory power, information flow and regional domination, modify cortical EEG responses to TMS. However, the impact of ongoing fluctuations of large-scale brain network states on TMS-EEG responses has not been explored. ObjectivesTo determine the effects of large-scale brain network states on TMS-EEG responses. MethodsResting-state EEG and structural MRI from 24 healthy subjects were recorded to infer large-scale brain states. TMS-EEG was acquired with TMS at state-related targets, identified by the spatial distribution of state activation power from resting-state EEG. TMS-induced oscillations were measured by event-related spectral perturbations (ERSPs), and classified with respect to the brain states preceding the TMS pulses. State-locked ERSPs with TMS at specific state-related targets and during state activation were compared with state-unlocked ERSPs. ResultsIntra-individual comparison of ERSPs by threshold free cluster enhancement (TFCE) revealed that posterior and visual state-locked TMS, respectively, increased beta and alpha responses to TMS of parietal and occipital cortex compared to state-unlocked TMS. Also, the peak frequencies of ERSPs were increased with state-locked TMS. In addition, inter-individual correlation analyses revealed that posterior and visual state-locked TMS-induced oscillation power (ERSP clusters identified by TFCE) positively correlated with state-dependent oscillation power preceding TMS. ConclusionsSpontaneous transient large-scale brain network states modify TMS-induced natural oscillations in specific brain regions. This significantly extends our knowledge on the critical importance of instantaneous state on explaining the brain's varying responsiveness to external perturbation.

Utility of Smartphone-Based Digital Phenotyping Biomarkers in Assessing Treatment Response to Transcranial Magnetic Stimulation in Depression: Proof-of-Concept Study.

Identifying biomarkers of response to transcranial magnetic stimulation (TMS) in treatment-resistant depression is a priority for personalizing care. Clinical and neurobiological determinants of treatment response to TMS, while promising, have limited scalability. Therefore, evaluating novel, technologically driven, and potentially scalable biomarkers, such as digital phenotyping, is necessary. This study aimed to examine the potential of smartphone-based digital phenotyping and its feasibility as a predictive biomarker of treatment response to TMS in depression. We assessed the feasibility of digital phenotyping by examining the adherence and retention rates. We used smartphone data from passive sensors as well as active symptom surveys to determine treatment response in a naturalistic course of TMS treatment for treatment-resistant depression. We applied a scikit-learn logistic regression model (l1 ratio=0.5; 2-fold cross-validation) using both active and passive data. We analyzed related variance metrics throughout the entire treatment duration and on a weekly basis to predict responders and nonresponders to TMS, defined as ≥50% reduction in clinician-rated symptom severity from baseline. The adherence rate was 89.47%, and the retention rate was 73%. The area under the curve for correct classification of TMS response ranged from 0.59 (passive data alone) to 0.911 (both passive and active data) for data collected throughout the treatment course. Importantly, a model using the average of all features (passive and active) for the first week had an area under the curve of 0.7375 in predicting responder status at the end of the treatment. The results of our study suggest that it is feasible to use digital phenotyping data to assess response to TMS in depression. Early changes in digital phenotyping biomarkers, such as predicting response from the first week of data, as shown in our results, may also help guide the treatment course.

Sex-specific reference values for total, central, and peripheral latency of motor evoked potentials from a large cohort.

Differentiating between physiologic and altered motor evoked potentials (MEPs) to transcranial magnetic stimulation (TMS) is crucial in clinical practice. Some physical characteristics, such as height and age, introduce sources of variability unrelated to neural dysfunction. We provided new age- and height-adjusted normal values for cortical latency, central motor conduction time (CMCT), and peripheral motor conduction time (PMCT) from a large cohort of healthy subjects. Previously reported data from 587 participants were re-analyzed. Nervous system disorders were ruled out by clinical examination and magnetic resonance imaging. MEP latency was determined as stimulus-to-response latency through stimulation with a circular coil over the "hot spot" of the First Dorsal Interosseous and Tibialis Anterior muscles, during mild tonic contraction. CMCT was estimated as the difference between MEP cortical latency and PMCT by radicular magnetic stimulation. Additionally, right-to-left differences were calculated. For each parameter, multiple linear regression models of increasing complexity were fitted using height, age, and sex as regressors. Motor evoked potential cortical latency, PMCT, and CMCT were shown to be age- and height-dependent, although age had only a small effect on CMCT. Relying on Bayesian information criterion for model selection, MEP cortical latency and PMCT were explained best by linear models indicating a positive correlation with both height and age. Also, CMCT to lower limbs positively correlated with height and age. CMCT to upper limbs positively correlated to height, but slightly inversely correlated to age, as supported by non-parametric bootstrap analysis. Males had longer cortical latencies and CMCT to lower limbs, as well as longer PMCT and cortical latencies to upper limbs, even when accounting for differences in body height. Right-to-left-differences were independent of height, age, and sex. Based on the selected regression models, sex-specific reference values were obtained for all TMS-related latencies and inter-side differences, with adjustments for height and age, where warranted. A significant relationship was observed between height and age and all MEP latency values, in both upper and lower limbs. These set of reference values facilitate the evaluation of MEPs in clinical studies and research settings. Unlike previous reports, we also highlighted the contribution of sex.

Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulation.

We describe a novel application of methodology for high-density surface electromyography (HDsEMG) decomposition to identify motor unit (MU) firings in response to transcranial magnetic stimulation (TMS). The method is based on the MU filter estimation from HDsEMG decomposition with convolution kernel compensation during voluntary isometric contractions and its application to contractions elicited by TMS. First, we simulated synthetic HDsEMG signals during voluntary contractions followed by simulated motor evoked potentials (MEPs) recruiting an increasing proportion of the motor pool. The estimation of MU filters from voluntary contractions and their application to elicited contractions resulted in high (>90%) precision and sensitivity of MU firings during MEPs. Subsequently, we conducted three experiments in humans. From HDsEMG recordings in first dorsal interosseous and tibialis anterior muscles, we demonstrated an increase in the number of identified MUs during MEPs evoked with increasing stimulation intensity, low variability in the MU firing latency and a proportion of MEP energy accounted for by decomposition similar to voluntary contractions. A negative relationship between the MU recruitment threshold and the number of identified MU firings was exhibited during the MEP recruitment curve, suggesting orderly MU recruitment. During isometric dorsiflexion we also showed a negative association between voluntary MU firing rate and the number of firings of the identified MUs during MEPs, suggesting a decrease in the probability of MU firing during MEPs with increased background MU firing rate. We demonstrate accurate identification of a large population of MU firings in a broad recruitment range in response to TMS via non-invasive HDsEMG recordings. KEY POINTS: Transcranial magnetic stimulation (TMS) of the scalp produces multiple descending volleys, exciting motor pools in a diffuse manner. The characteristics of a motor pool response to TMS have been previously investigated with intramuscular electromyography (EMG), but this is limited in its capacity to detect many motor units (MUs) that constitute a motor evoked potential (MEP) in response to TMS. By simulating synthetic signals with known MU firing patterns, and recording high-density EMG signals from two human muscles, we show the feasibility of identifying firings of many MUs that comprise a MEP. We demonstrate the identification of firings of a large population of MUs in the broad recruitment range, up to maximal MEP amplitude, with fewer required stimuli compared to intramuscular EMG recordings. The methodology demonstrates an emerging possibility to study responses to TMS on a level of individual MUs in a non-invasive manner.

An agile, data-driven approach for target selection in rTMS therapy for anxiety symptoms: Proof of concept and preliminary data for two novel targets.

Data-driven approaches to transcranial magnetic stimulation (TMS) might yield more consistent and symptom-specific results based on individualized functional connectivity analyses compared to previous traditional approaches due to more precise targeting. We provide a proof of concept for an agile target selection paradigm based on using connectomic methods that can be used to detect patient-specific abnormal functional connectivity, guide treatment aimed at the most abnormal regions, and optimize the rapid development of new hypotheses for future study. We used the resting-state functional MRI data of 28 patients with medically refractory generalized anxiety disorder to perform agile target selection based on abnormal functional connectivity patterns between the Default Mode Network (DMN) and Central Executive Network (CEN). The most abnormal areas of connectivity within these regions were selected for subsequent targeted TMS treatment by a machine learning based on an anomalous functional connectivity detection matrix. Areas with mostly hyperconnectivity were stimulated with continuous theta burst stimulation and the converse with intermittent theta burst stimulation. An image-guided accelerated theta burst stimulation paradigm was used for treatment. Areas 8Av and PGs demonstrated consistent abnormalities, particularly in the left hemisphere. Significant improvements were demonstrated in anxiety symptoms, and few, minor complications were reported (fatigue (n=2) and headache (n=1)). Our study suggests that a left-lateralized DMN is likely the primary functional network disturbed in anxiety-related disorders, which can be improved by identifying and targeting abnormal regions with a rapid, data-driven, agile aTBS treatment on an individualized basis.

Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG

The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.

Corticospinal and intracortical responses from both motor cortices following unilateral concentric versus eccentric contractions.

Cross-education is the phenomenon where training of one limb can cause neuromuscular adaptations in the opposite untrained limb. This effect has been reported to be greater after eccentric (ECC) than concentric (CON) strength training; however, the underpinning neurophysiological mechanisms remain unclear. Thus, we compared responses to transcranial magnetic stimulation (TMS) in both motor cortices following single sessions of unilateral ECC and CON exercise of the elbow flexors. Fourteen healthy adults performed three sets of 10 ECC and CON right elbow flexor contractions at 75% of respective maximum on separate days. Elbow flexor maximal voluntary isometric contraction (MVIC) torques were measured before and after exercise, and responses to single- and paired-pulse TMS were recorded from the non-exercised left and exercised right biceps brachii. Pre-exercise and post-exercise responses for ECC and CON were compared by repeated measures analyses of variance (ANOVAs). MVIC torque of the exercised arm decreased (p < 0.01) after CON (-30 ± 14%) and ECC (-39 ± 13%) similarly. For the non-exercised left biceps brachii, resting motor threshold (RMT) decreased after CON only (-4.2 ± 3.9% of maximum stimulator output [MSO], p < 0.01), and intracortical facilitation (ICF) decreased (-15.2 ± 20.0%, p = 0.038) after ECC only. For the exercised right biceps, RMT increased after ECC (8.6 ± 6.2% MSO, p = 0.014) but not after CON (6.4 ± 8.1% MSO, p = 0.066). Thus, unilateral ECC and CON elbow flexor exercise modulated excitability differently for the non-exercised hemisphere. These findings suggest that responses after a single bout of exercise may not reflect longer term adaptations.

Similarity of hand muscle synergies elicited by transcranial magnetic stimulation and those found during voluntary movement.

Converging evidence in human and animal models suggests that exogenous stimulation of the motor cortex (M1) elicits responses in the hand with similar modular structure to that found during voluntary grasping movements. The aim of this study was to establish the extent to which modularity in muscle responses to transcranial magnetic stimulation (TMS) to M1 resembles modularity in muscle activation during voluntary hand movements involving finger fractionation. Electromyography (EMG) was recorded from eight hand-forearm muscles in eight healthy individuals. Modularity was defined using non-negative matrix factorization to identify low-rank approximations (spatial muscle synergies) of the complex activation patterns of EMG data recorded during high-density TMS mapping of M1 and voluntary formation of gestures in the American Sign Language alphabet. Analysis of synergies revealed greater than chance similarity between those derived from TMS and those derived from voluntary movement. Both data sets included synergies dominated by single intrinsic hand muscles presumably to meet the demand for highly fractionated finger movement. These results suggest that corticospinal connectivity to individual intrinsic hand muscles may be combined with modular multimuscle activation via synergies in the formation of hand postures.NEW & NOTEWORTHY This is the first work to examine the similarity of modularity in hand muscle responses to transcranial magnetic stimulation (TMS) of the motor cortex and that derived from voluntary hand movement. We show that TMS-elicited muscle synergies of the hand, measured at rest, reflect those found in voluntary behavior involving finger fractionation. This work provides a basis for future work using TMS to investigate muscle activation modularity in the human motor system.

Enhanced availability of serotonin limits muscle activation during high-intensity, but not low-intensity, fatiguing contractions.

Serotonin (5-HT) modulates motoneuron excitability during muscle contractions, where the release of 5-HT in the central nervous system (CNS) is linked to the intensity of physical activity. Although there is evidence that enhanced availability of 5-HT can exacerbate fatigue, these effects on the development of fatigue during different contraction intensities are largely unknown. The purpose of this study was to investigate how enhanced 5-HT availability affects voluntary muscle activation and corticospinal excitability during fatigue-inducing contractions. Two experiments were performed. In the first experiment (n = 11), 12 isometric elbow flexions at 20% maximal voluntary contractions (MVCs) were performed for 2 min each with 40-s rest periods. In the second experiment (n = 14), 12 maximal isometric elbow flexions were held for 10 s each with 40-s rest periods. In both experiments, the selective serotonin reuptake inhibitor (20-mg paroxetine), or a placebo, was administered in a two-way crossover design. Muscle responses to transcranial magnetic stimulation (TMS) of the motor cortex (both experiments 1 and 2), as well as motor point stimulation of the elbow flexors (experiment 2) were assessed. Paroxetine reduced both motor cortical (P = 0.018) and motor point voluntary activation (P = 0.036) during the maximal contraction protocol. Paroxetine also reduced exercise-induced lengthening of the TMS silent period during the submaximal (P = 0.037) and maximal (P = 0.002) contraction protocols. Activation of inhibitory 5-HT1A receptors on motoneurons likely exacerbated exercise-induced reductions in voluntary drive to the elbow flexors. However, 5-HT modulation of motor activity also appeared at the supraspinal level.NEW & NOTEWORTHY As serotonin release onto motoneurons may be scaled to the strength of muscle contraction, it may have different effects when neuromuscular fatigue is induced by contractions of different intensities. Enhanced levels of serotonin compromised voluntary activation of muscle when fatigue was induced by strong contractions but not weak contractions. This provides evidence that the serotonergic system has the greatest influence on fatigue that is generated with high neural drive to the target muscle.

Prefrontal reactivity to TMS perturbation as a toy model of mental health outcomes during the COVID-19 pandemic

Psychosocial hardships associated with the COVID-19 pandemic led many individuals to suffer adverse mental health consequences, however, others show no negative effects. We hypothesized that the electroencephalographic (EEG) response to transcranial magnetic stimulation (TMS) could serve as a toy-model of an individual's capacity to resist psychological stress, in this case linked to the COVID-19 pandemic. We analyzed data from 74 participants who underwent mental health monitoring and concurrent electroencephalography with transcranial magnetic stimulation of the left dorsolateral prefrontal cortex (L-DLPFC) and left inferior parietal lobule (L-IPL). Within the following 19 months, mental health was reassessed at three timepoints during lock-down confinement and different phases of de-escalation in Spain. Compared with participants who remained stable, those who experienced increased mental distress showed, months earlier, significantly larger late EEG responses locally after L-DLPFC stimulation (but not globally nor after L-IPL stimulation). This response, together with years of formal education, was significantly predictive of mental health status during the pandemic. These findings reveal that the effect of TMS perturbation offers a predictive toy model of psychosocial stress response, as exemplified by the COVID-19 pandemic.

Local brain-state dependency of effective connectivity: a pilot TMS-EEG study [version 2; peer review: 2 approved

BackgroundSpontaneous cortical oscillations have been shown to modulate cortical responses to transcranial magnetic stimulation (TMS). However, whether these oscillations influence cortical effective connectivity is largely unknown. We conducted a pilot study to set the basis for addressing how spontaneous oscillations affect cortical effective connectivity measured through TMS-evoked potentials (TEPs).MethodsWe applied TMS to the left primary motor cortex and right pre-supplementary motor area of three subjects while recording EEG. We classified trials off-line into positive- and negative-phase classes according to the mu and beta rhythms. We calculated differences in the global mean-field amplitude (GMFA) and compared the cortical spreading of the TMS-evoked activity between the two classes.ResultsPhase affected the GMFA in four out of 12 datasets (3 subjects × 2 stimulation sites × 2 frequency bands). Two of the observed significant intervals were before 50 ms, two between 50 and 100 ms, and one after 100 ms post-stimulus. Source estimates showed complex spatial differences between the classes in the cortical spreading of the TMS-evoked activity.ConclusionsTMS-evoked effective connectivity seems to depend on the phase of local cortical oscillations at the stimulated site. This work paves the way to design future closed-loop stimulation paradigms.

Effect of neuroanatomy on corticomotor excitability during and after transcranial magnetic stimulation and intermittent theta burst stimulation.

Individual neuroanatomy can influence motor responses to transcranial magnetic stimulation (TMS) and corticomotor excitability after intermittent theta burst stimulation (iTBS). The purpose of this study was to examine the relationship between individual neuroanatomy and both TMS response measured using resting motor threshold (RMT) and iTBS measured using motor evoked potentials (MEPs) targeting the biceps brachii and first dorsal interosseus (FDI). Ten nonimpaired individuals completed sham‐controlled iTBS sessions and underwent MRI, from which anatomically accurate head models were generated. Neuroanatomical parameters established through fiber tractography were fiber tract surface area (FTSA), tract fiber count (TFC), and brain scalp distance (BSD) at the point of stimulation. Cortical magnetic field induced electric field strength (EFS) was obtained using finite element simulations. A linear mixed effects model was used to assess effects of these parameters on RMT and iTBS (post‐iTBS MEPs). FDI RMT was dependent on interactions between EFS and both FTSA and TFC. Biceps RMT was dependent on interactions between EFS and and both FTSA and BSD. There was no groupwide effect of iTBS on the FDI but individual changes in corticomotor excitability scaled with RMT, EFS, BSD, and FTSA. iTBS targeting the biceps was facilitatory, and dependent on FTSA and TFC. MRI‐based measures of neuroanatomy highlight how individual anatomy affects motor system responses to different TMS paradigms and may be useful for selecting appropriate motor targets when designing TMS based therapies.

Simultaneous stereo-EEG and high-density scalp EEG recordings to study the effects of intracerebral stimulation parameters

BackgroundCortico-cortical evoked potentials (CCEPs) recorded by stereo-electroencephalography (SEEG) are a valuable tool to investigate brain reactivity and effective connectivity. However, invasive recordings are spatially sparse since they depend on clinical needs. This sparsity hampers systematic comparisons across-subjects, the detection of the whole-brain effects of intracortical stimulation, as well as their relationships to the EEG responses evoked by non-invasive stimuli. ObjectiveTo demonstrate that CCEPs recorded by high-density electroencephalography (hd-EEG) provide additional information with respect SEEG alone and to provide an open, curated dataset to allow for further exploration of their potential. MethodsThe dataset encompasses SEEG and hd-EEG recordings simultaneously acquired during Single Pulse Electrical Stimulation (SPES) in drug-resistant epileptic patients (N = 36) in whom stimulations were delivered with different physical, geometrical, and topological parameters. Differences in CCEPs were assessed by amplitude, latency, and spectral measures. ResultsWhile invasively and non-invasively recorded CCEPs were generally correlated, differences in pulse duration, angle and stimulated cortical area were better captured by hd-EEG. Further, intracranial stimulation evoked site-specific hd-EEG responses that reproduced the spectral features of EEG responses to transcranial magnetic stimulation (TMS). Notably, SPES, albeit unperceived by subjects, elicited scalp responses that were up to one order of magnitude larger than the responses typically evoked by sensory stimulation in awake humans. ConclusionsCCEPs can be simultaneously recorded with SEEG and hd-EEG and the latter provides a reliable descriptor of the effects of SPES as well as a common reference to compare the whole-brain effects of intracortical stimulation to those of non-invasive transcranial or sensory stimulations in humans.

Local brain-state dependency of effective connectivity: a pilot TMS–EEG study

Background Spontaneous cortical oscillations have been shown to modulate cortical responses to transcranial magnetic stimulation (TMS). However, whether these oscillations influence cortical effective connectivity is largely unknown. We conducted a pilot study to set the basis for addressing how spontaneous oscillations affect cortical effective connectivity measured through TMS-evoked potentials (TEPs). Methods We applied TMS to the left primary motor cortex and right pre-supplementary motor area of three subjects while recording EEG. We classified trials off-line into positive- and negative-phase classes according to the mu and beta rhythms. We calculated differences in the global mean-field amplitude (GMFA) and compared the cortical spreading of the TMS-evoked activity between the two classes. Results Phase affected the GMFA in four out of 12 datasets (3 subjects × 2 stimulation sites × 2 frequency bands). Two of the observed significant intervals were before 50 ms, two between 50 and 100 ms, and one after 100 ms post-stimulus. Source estimates showed complex spatial differences between the classes in the cortical spreading of the TMS-evoked activity. Conclusions TMS-evoked effective connectivity appears to depend on the phase of local cortical oscillations at the stimulated site. This work paves the way to design future closed loop stimulation paradigms.

Enhancement of LTD-like plasticity by associative pairing of quadripulse magnetic stimulation with peripheral nerve stimulation

ObjectiveQuadripulse magnetic stimulation (QPS) is useful for changing corticospinal excitability, but the long-term depression (LTD)-like effect considerably has low responder rate. To solve this problem, we modified inhibitory QPS (QPSLTD) by pairing it with the application of an electrical stimulus (ES) to peripheral nerves (paired-associative QPS [PA-QPSLTD]), and investigated the effects of PA-QPSLTD on motor-evoked potentials (MEPs). MethodsThe peripheral-nerve ES was applied at two timings with a synchrony to transcranial magnetic stimulation (TMS) over the primary motor cortex (M1). The intrapair interval between ES and TMS was the N20-peak latency plus 2 ms for PALTP-QPSLTD, and N20-peak latency minus 5 ms for PALTD-QPSLTD. MEPs elicited by TMS over the left M1 were recorded from the right abductor pollicis brevis muscle before and after the interventions. The responder rates of PALTD-QPSLTD and QPSLTD was also studied. ResultsThe PALTD-QPSLTD induced larger LTD-like effect than QPSLTD, and the PALTP-QPSLTD induced smaller aftereffect than QPSLTD. The responder rates were significantly higher for PALTD-QPSLTD than for QPSLTD. ConclusionsThe new protocol, PALTD-QPSLTD, induces powerful and consistent LTD-like aftereffects in the corticospinal tract neurons. SignificancePALTD-QPSLTD is suitable for use in physiological evaluations and therapeutic approaches in various neurological disorders.

Abstract WMP37: Differential Montage Effect On Cortical Excitability In Ischemic Stroke Patients By Single Session Of High Amperage Transcranial Direct Current Stimulation

Background and Objective: We aim to assess the cortical excitability under three montages with single session of transcranial direct current stimulation (tDCS) at 4 mA on ischemic stroke patients. Methods: Adult subjects with first-ever unilateral ischemic stroke ≥6 months and inducible motor evoked potentials (MEP) underwent 3 sessions (washed out ≥2 days apart) of 30 minutes 4 mA tDCS in anodal, cathodal or bihemispheric montage (in pseudorandom order) combined with t upper extremity repetitive task training administered by an Occupational Therapist. We collected MEP responses to transcranial magnetic stimulation (TMS) single pulse, short intracortical inhibition (SICI, 3 ms) and intracortical facilitation (ICF, 15 ms) on bilateral abductor pollicis brevis (APB) muscles at baseline and four post-stimulation timepoints 12 minutes apart. We also monitored safety by recording adverse events, surveying subjects with a questionnaire on tolerability issues and collecting biometric measures (body resistance, skin temperature under the tDCS electrode). Results: Eighteen subjects completed 54 tDCS sessions in total. We observed montage ( P &lt;0.0001) and time ( P &lt;0.01) effects only on the lesioned hemisphere, with bihemispheric tDCS showing relatively higher peak-to-peak MEP. Lack of montage effect in baseline ( P &gt;0.949) suggested sufficient washout interval across the visits. No subjects experienced any adverse events. Biometric measures and tolerability were comparable across the three montages. The most common tolerability issue was transient redness under the tDCS electrodes (70% at anode, 48% at cathode). Conclusions: The bihemispheric montage increased ipsilateral cortical excitability the most in a single session of 4 mA tDCS in chronic ischemic stroke patients. Additionally, a current level of 4 mA is safe and tolerable over multiple sessions.

Preserved central cholinergic functioning to transcranial magnetic stimulation in de novo patients with celiac disease.

BackgroundCeliac disease (CD) is now viewed as a systemic disease with multifaceted clinical manifestations. Among the extra-intestinal features, neurological and neuropsychiatric symptoms are still a diagnostic challenge, since they can precede or follow the diagnosis of CD. In particular, it is well known that some adults with CD may complain of cognitive symptoms, that improve when the gluten-free diet (GFD) is started, although they may re-appear after incidental gluten intake. Among the neurophysiological techniques, motor evoked potentials (MEPs) to transcranial magnetic stimulation (TMS) can non-invasively probe in vivo the excitation state of cortical areas and cortico-spinal conductivity, being also able to unveil preclinical impairment in several neurological and psychiatric disorders, as well as in some systemic diseases affecting the central nervous system (CNS), such as CD. We previously demonstrated an intracortical disinhibition and hyperfacilitation of MEP responses to TMS in newly diagnosed patients. However, no data are available on the central cholinergic functioning indexed by specific TMS measures, such as the short-latency afferent inhibition (SAI), which might represent the neurophysiological correlate of cognitive changes in CD patients, also at the preclinical level.MethodsCognitive and depressive symptoms were screened by means of the Montreal Cognitive Assessment (MoCA) and the 17-item Hamilton Depression Rating Scale (HDRS), respectively, in 15 consecutive de novo CD patients and 15 healthy controls. All patients were on normal diet at the time of the enrolment. Brain computed tomography (CT) was performed in all patients. SAI, recorded at two interstimulus intervals (2 and 8 ms), was assessed as the percentage amplitude ratio between the conditioned and the unconditioned MEP response. Resting motor threshold, MEP amplitude and latency, and central motor conduction time were also measured.ResultsThe two groups were comparable for age, sex, anthropometric features, and educational level. Brain CT ruled out intracranial calcifications and clear radiological abnormalities in all patients. Scores at MoCA and HDRS were significantly worse in patients than in controls. The comparison of TMS data between the two groups revealed no statistically significant difference for all measures, including SAI at both interstimulus intervals.ConclusionsCentral cholinergic functioning explored by the SAI of the motor cortex resulted to be not affected in these de novo CD patients compared to age-matched healthy controls. Although the statistically significant difference in MoCA, an overt cognitive impairment was not clinically evident in CD patients. Coherently, to date, no study based on TMS or other diagnostic techniques has shown any involvement of the central acetylcholine or the cholinergic fibers within the CNS in CD. This finding might add support to the vascular inflammation hypothesis underlying the so-called “gluten encephalopathy”, which seems to be due to an aetiology different from that of the cholinergic dysfunction. Longitudinal studies correlating clinical, TMS, and neuroimaging data, both before and after GFD, are needed.

Bihemispheric sensorimotor oscillatory network states determine cortical responses to transcranial magnetic stimulation

BackgroundBrain responses to external stimuli vary with fluctuating states of neuronal activity. Previous work has demonstrated effects of phase and power of the ongoing local sensorimotor μ-alpha-oscillation on responses to transcranial magnetic stimulation (TMS) of motor cortex (M1). However, M1 is part of a distributed network, and the effects of oscillatory activity in this network on TMS-evoked EEG responses (TEPs) have not been explored. ObjectivesTo determine the effects of oscillatory activity in the bihemispheric sensorimotor network on TEPs. Methods31 healthy subjects received single-pulse TMS of the left M1 hand area during EEG recording. Ongoing bihemispheric sensorimotor cortex oscillatory states were reconstructed from the EEG directly preceding TMS, and inferred by a data-driven method combining a multivariate autoregressive model and a Hidden Markov model. TEP amplitudes (P25, N45, P70, N100 and P180) were then compared between different bihemispheric sensorimotor cortex oscillatory states. ResultsFour bihemispheric sensorimotor cortex oscillatory states were identified, with different interhemispheric expressions of theta and alpha oscillations. High alpha-power states in the stimulated sensorimotor cortex increased P25 amplitude. Alpha power in the alpha-alpha state (stimulated - non-stimulated hemisphere) correlated in both hemispheres with N45 amplitude. Theta power in the alpha-theta state correlated in the non-stimulated hemisphere with P70 amplitude. ConclusionsBihemispheric sensorimotor cortex oscillatory states contribute to TEPs, with a relevance shift from stimulated to non-stimulated M1 from P25 over N45 to P70. This significantly extends previous findings: not only ongoing local oscillations but distributed network oscillatory states determine cortical responsiveness to external stimuli.

Recording brain responses to TMS of primary motor cortex by EEG – utility of an optimized sham procedure

IntroductionElectroencephalography (EEG) is increasingly used to investigate brain responses to transcranial magnetic stimulation (TMS). A relevant issue is that TMS is associated with considerable auditory and somatosensory stimulation, causing peripherally evoked potentials (PEPs) in the EEG, which contaminate the direct cortical responses to TMS (TEPs). All previous attempts to control for PEPs suffer from significant limitations. Objective/HypothesisTo design an optimized sham procedure to control all sensory input generated by subthreshold real TMS targeting the hand area of the primary motor cortex (M1), enabling reliable separation of TEPs from PEPs. MethodsIn 23 healthy (16 female) subjects, we recorded EEG activity evoked by an optimized sham TMS condition which masks and matches auditory and somatosensory co-stimulation during the real TMS condition: auditory control was achieved by noise masking and by using a second TMS coil that was placed on top of the real TMS coil and produced a calibrated sound pressure level. Somatosensory control was obtained by electric stimulation (ES) of the scalp with intensities sufficient to saturate somatosensory input. ES was applied in both the sham and real TMS conditions. Perception of auditory and somatosensory inputs in the sham and real TMS conditions were compared by psychophysical testing. Transcranially evoked EEG signal changes were identified by subtraction of EEG activity in the sham condition from EEG activity in the real TMS condition. ResultsPerception of auditory and somatosensory inputs in the sham vs. real TMS conditions was comparable. Both sham and real TMS evoked a series of similar EEG signal deflections and induced broadband power increase in oscillatory activity. Notably, the present procedure revealed EEG potentials and a transient increase in beta band power at the site of stimulation that were only present in the real TMS condition. DiscussionThe results validate the effectiveness of our optimized sham approach. Despite the presence of typical responses attributable to sensory input, the procedure provided evidence for direct cortical activation by subthreshold TMS of M1. The findings are relevant for future TMS-EEG experiments that aim at measuring regional brain target engagement controlled by an optimized sham procedure.