TMS-evoked Potentials Research Articles

Application of Fast Perturbational Complexity Index to the Diagnosis and Prognosis for Disorders of Consciousness.

Diagnosis and prognosis of patients with disorders of consciousness (DOC) is a challenge for neuroscience and clinical practice. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is an effective tool to measure the level of consciousness. However, a scientific and accurate method to quantify TMS-evoked activity is still lacking. This study applied fast perturbational complexity index (PCIst) to the diagnosis and prognosis of DOC patients. TMS-EEG data of 30 normal healthy participants (NOR) and 181 DOC patients were collected. The PCIst was used to assess the time-space complexity of TMS-evoked potentials (TEP). We selected parameters of PCIst in terms of data length, data delay, sampling rate and frequency band. In addition, we collected Coma Recovery Scale-Revised (CRS-R) values for 114 DOC patients after one year. Finally, we trained the classification and regression model. 1) PCIst shows the differences among NOR, minimally consciousness state (MCS) and unresponsive wakefulness syndrome (UWS) and has low computational cost. 2) Optimal parameters of data length and delay after TMS are 300 ms and 101-300 ms. Significant differences of PCIst at 5-8 Hz and 9-12 Hz bands are found among NOR, MCS and UWS groups. PCIst still works when TEP is down-sampled to 250 Hz. 3) PCIst at 9-12 Hz shows the highest performance in diagnosis and prognosis of DOC. This study confirms that PCIst can quantify the level of consciousness. PCIst is a potential measure for the diagnosis and prognosis of DOC patients.

Classification of Cognitive Impairment and Healthy Controls Based on Transcranial Magnetic Stimulation Evoked Potentials.

Backgrounds: Nowadays, risks of Cognitive Impairment (CI) [highly suspected Alzheimer's disease (AD) in this study] threaten the quality of life for more older adults as the population ages. The emergence of Transcranial Magnetic Stimulation-Electroencephalogram (TMS-EEG) enables noninvasive neurophysiological investi-gation of the human cortex, which might be potentially used for CI detection.Objectives: The aim of this study is to explore whether the spatiotemporal features of TMS Evoked Potentials (TEPs) could classify CI from healthy controls (HC).Methods: Twenty-one patients with CI and 22 HC underwent a single-pulse TMS-EEG stimulus in which the pulses were delivered to the left dorsolateral prefrontal cortex (left DLPFC). After preprocessing, seven regions of interest (ROIs) and two most reliable TEPs' components: N100 and P200 were selected. Next, seven simple and interpretable linear features of TEPs were extracted for each region, three common machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) were used to detect CI. Meanwhile, data augmentation and voting strategy were used for a more robust model. Finally, the performance differences of features in classifiers and their contributions were investigated.Results: 1. In the time domain, the features of N100 had the best performance in the SVM classifier, with an accuracy of 88.37%. 2. In the aspect of spatiality, the features of the right frontal region and left parietal region had the best performance in the SVM classifier, with an accuracy of 83.72%. 3. The Local Mean Field Power (LMFP), Average Value (AVG), Latency and Amplitude contributed most in classification.Conclusions: The TEPs induced by TMS over the left DLPFC has significant differences spatially and temporally between CI and HC. Machine learning based on the spatiotemporal features of TEPs have the ability to separate the CI and HC which suggest that TEPs has potential as non-invasive biomarkers for CI diagnosis.

Topography and lateralization of long-latency trigeminal somatosensory evoked potentials

ObjectiveLong-latency trigeminal somatosensory evoked potentials (SSEPs) have not been sufficiently studied regarding their topography and lateralization. SSEPs are hypothesized to contribute to the evoked potentials after transcranial magnetic stimulation (TMS). This study focused on trigeminal SSEPs with latencies > 100 ms, potentially overlapping with TMS-evoked N100. MethodsIn 14 healthy subjects, the trigeminus was electrically stimulated on the left and right forehead, and time-course, topography, and lateralization of trigeminal SSEPs were examined in 64-channel electroencephalogram (EEG). SSEPs were then compared to TMS-evoked potentials when TMS was applied to the left and right dorsolateral prefrontal cortex. ResultsTrigeminal stimulation produced a somatosensory N140 with topographic maximum over centroparietal electrodes with larger amplitudes contra- than ipsilaterally to the stimulation. Contralateral potentials after TMS were partly comparable in their topography but differed in latencies. ConclusionsSSEPs generated by electrical stimulation of the trigeminus occurred over somatosensory areas with a contralateral lateralization. Therefore, contralateral potentials after TMS should be interpreted with caution, as they may include somatosensory components. SignificanceThe topography and lateralization of long-latency trigeminal SSEPs should be considered in future TMS-EEG designs.

TMS‐EEG as a measure of cortical hyperexcitability in motor and parietal cortex in Alzheimer’s disease: A pilot study

AbstractBackgroundPatients with Alzheimer’s disease (AD) have abnormally high cortical excitability, with an increased risk of seizures and epileptiform discharges. Transcranial magnetic stimulation with electroencephalography (TMS‐EEG) can noninvasively measure cortical excitability in local brain regions, and has shown increased excitability in motor cortex in AD. However, practical applications of TMS‐EEG measures are currently limited by a dearth of data from brain regions involved early‐on in AD, such as the parietal cortex. This pilot study investigated the feasibility of using TMS‐EEG to compare "Excitability Gain" across multiple brain regions in AD.MethodThree biomarker‐confirmed AD participants (mean age 71, 1 female) and 4 healthy control participants (HC, mean age 68, 2 female) enrolled in this pilot study. Single‐pulse TMS stimulation was applied to left primary motor cortex (M1) and inferior parietal cortex (IPL), with 120 pulses given at both 120% and 135% resting motor threshold (RMT). We assessed tolerability of this protocol. TMS‐evoked potentials (TEPs) were measured as the average EEG response after a TMS pulse. The percent change in TEP between the two stimulation intensities was calculated (TEP Excitability Gain, %change). A power calculation for two sample means was performed to determine the number of subjects needed to demonstrate a between‐group difference in IPL excitability.ResultThe procedure was well‐tolerated; one HC participant complained of a mild positional neck discomfort. In HCs, TEP Excitability Gain was 12 (±19 SD) percent in M1, and ‐5 (±12 SD) percent in IPL. In AD participants, TEP Excitability Gain was 39 (±50 SD) percent in M1, and 31 (±31 SD) percent in IPL (Figure 1). Assuming a SD of 31 for IPL stimulation, a sample size of 13 in each group would have a >80% power to detect a between‐group difference of 36% in TEP Excitability Gain with an alpha of 0.05.ConclusionTMS‐EEG measures of "Excitability Gain" are feasible in AD participants. A sample size of 13 in each group will be required to test for a between‐group difference of cortical excitability in the parietal lobe. TMS‐EEG may be a useful tool to measure cortical excitability across multiple brain regions in AD.

Quantitative assessment of cortical excitability in Alzheimer’s dementia and its association with clinical symptoms: A systematic review and meta‐analyses

AbstractBackgroundAlzheimer’s Disease (AD) is characterized by cognitive and neuropsychiatric symptoms (NPS). Studies using electroencephalography (EEG) have shown increased epileptiform and epileptic activity in AD. Transcranial magnetic stimulation (TMS) studies have also shown abnormal cortical excitability in AD, however findings have been inconsistent. Further, relationship between cortical excitability and clinical symptoms of AD is not clear. This review and meta‐analyses aims to synthesize the existing evidence for abnormal cortical excitability in AD and its relationship with clinical symptoms.MethodWe systematically searched and reviewed publications that quantitatively assessed cortical excitability, using TMS resting motor threshold (rMT), active motor threshold (aMT), motor evoked potential (MEP) or directly from the cortex using TMS‐EEG via TMS‐evoked potential (TEP). Effect sizes and 95% confidence intervals (CI) of rMT and aMT were calculated using Hedges’ g and meta‐analyzed using a random effects model. Heterogeneity among studies was assessed by Cochran’s Q and I2 statistic.ResultWe identified 895 publications out of which 68 were reviewed in full‐text and 37 were included in the final review. Thirty studies using rMT and seven using aMT were included in the meta‐analyses. The AD group had reduced rMT (Hedges’ g = ‐0.99, 95% CI [‐1.29, ‐0.68], p < 0.00001) and aMT (Hedges’ g = ‐0.87, 95% CI [‐1.50, ‐0.24], p < 0.00001) as compared with control groups, indicative of higher cortical excitability. Evidence of considerable heterogeneity was found across the studies (Q (29) = 85.68, p < 0.00001, I2 =81%). Qualitative review of the literature showed some evidence of increased MEP amplitude (n = 2 studies), however findings related to TEP were inconsistent. Further, there was some evidence (n = 4 studies) supporting an inverse association between cortical excitability and global cognition. No publications reported on the relationship between cortical excitability and neuropsychiatric symptoms (NPS).ConclusionThere is strong evidence of increased motor cortex excitability in AD and some evidence of an inverse association between excitability and cognition. Future studies should assess cortical excitability from non‐motor areas and examine its relationship with cognition and NPS.

Measuring the timing of functional connections through TMS-evoked potentials

Measuring the timing of functional connections through TMS-evoked potentials

ArTGen: An Arduino-based trigger generator to remotely handle pulse timing in TMS units

Abstract Introduction: Transcranial magnetic stimulation (TMS) protocols are associated with specific combinations of stimulation parameters, including the location of the targeted site, E-field intensity and orientation, pulse shape and duration, variable/fixed inter-pulse interval (IPI), and coil shape and dimension. Among these parameters, IPI may significantly affect the direction of induced neuroplasticity and the possible interference of habituation and expectation effects with TMS-evoked potentials. The TMS units are not always flexible enough to generate customized pulse sequences, thus external devices/software are commonly used. To remotely handle the randomization of IPI, we designed an effective and cheap device (ArTGen – Arduino Uno-based Trigger Generator) for generating arbitrary sequences of square-wave digital pulses. Materials and methods: Using an external foot-switch pedal the TMS experimenter is able to handle the ArTGen’s firmware to remotely drive a customized sequence of pulses in the TMS unit. We designed the firmware to switch among four conditions (single pulse, sequence of jittered pulses, pause and stop) based on a single and double foot-switch taping. We used two BNC sockets to manage respectively the foot-switch signal and the randomized TTLs in output to ArTGen. We tested ArTGen on Magstim Rapid2 with AirFilm® figure-8 coil in tasks with the following characteristics: (i) %Maximal Stimulation Output at 50%; (ii) 100 pulses and (iii) central pulse frequencies set to either 0.1, 5, 10, 15, or 20 Hz. Results: Our results show that all the TTLs released by ArTGen were correctly detected by Magstim Rapid2, and highlight a short delay (computed as the difference between the Arduino trigger and the Magstim Rapid2 output) of about 5μsec across all pulse frequencies. Conclusion: ArTGen is a stand-alone, portable, and not cumbersome opensource device used to randomize TMS pulses or to trigger/synchronize different devices in a closed-loop TMS system with microseconds of accuracy. Keywords: TMS unit, Arduino board, Inter Pulse Interval randomization, Closed Loop TMS System Synchronization

Intermittent Theta Burst Stimulation to the Primary Motor Cortex Reduces Cortical Inhibition: A TMS-EEG Study.

Introduction: The aim of this study was to reveal the effects of intermittent theta burst stimulation (iTBS) in modulating cortical networks using transcranial magnetic stimulation and electroencephalography (TMS-EEG) recording. Methods: Eighteen young adults participated in our study and received iTBS to the primary motor cortex (M1), supplementary motor area, and the primary visual cortex in three separate sessions. A finger tapping task and ipsilateral single-pulse TMS-EEG recording for the M1 were administrated before and after iTBS in each session. The effects of iTBS in motor performance and TMS-evoked potentials (TEPs) were investigated. Results: The results showed that iTBS to the M1, but not supplementary motor area or the primary visual cortex, significantly reduced the N100 amplitude of M1 TEPs in bilateral hemispheres (p = 0.019), with a more prominent effect in the contralateral hemisphere than in the stimulated hemisphere. Moreover, only iTBS to the M1 decreased global mean field power (corrected ps < 0.05), interhemispheric signal propagation (t = 2.53, p = 0.030), and TMS-induced early α-band synchronization (p = 0.020). Conclusion: Our study confirmed the local and remote after-effects of iTBS in reducing cortical inhibition in the M1. TMS-induced oscillations after iTBS for changed cortical excitability in patients with various neurological and psychiatric conditions are worth further exploration.

Phase-Synchronized Transcranial Alternating Current Stimulation-Induced Neural Oscillations Modulate Cortico-Cortical Signaling Efficacy.

Introduction: Synchronized oscillatory brain activity is considered a basis for flexible neuronal network communication. However, the causal role of inter-regional oscillatory phase relations in modulating signaling efficacy in cortical networks has not been directly demonstrated in humans so far. Aim: The current study addresses the causal role of transcranial alternating current stimulation (tACS)-induced oscillatory cross-network phase relations in modulating signaling efficacy across human cortical networks. Methods: To this end, concurrent tACS, transcranial magnetic stimulation (TMS), and electroencephalography (EEG) were employed to measure the modulation of excitability and signaling efficacy across cortical networks during externally induced neural oscillations. Theta oscillatory activity was introduced through tACS in two nodes of the human frontoparietal network: the dorsolateral prefrontal cortex (DLPFC) and the posterior parietal cortex (PPC). Six Hertz tACS was applied to the DLPFC and PPC simultaneously in an in-phase or antiphase manner. In addition, single-pulse TMS was administered over the DLPFC at four different phases of tACS and the propagation of TMS-evoked neuronal activity was measured with EEG. Results: We show that tACS-induced theta oscillations modulate TMS-evoked potentials (TEPs) in a phase-dependent manner, and that the induced oscillatory phase relation across the frontoparietal network affects the propagation of phase-dependent TEPs within as well as beyond the frontoparietal network. Conclusion: We show that the effect of tACS-induced phase relation across the frontoparietal network on signal transmission extends beyond the frontoparietal network. The results support a causal role of inter-nodal oscillatory phase synchrony in routing cortico-cortical information flow. Impact statement Theoretical models have proposed that phase relations of cross-network neural oscillations control communication efficacy across human cortical networks. The current study introduced concurrent transcranial alternating current stimulation-transcranial magnetic stimulation-electroencephalography (tACS-TMS-EEG) to experimentally study the theoretical framework. Dual-site in-phase or antiphase 6 Hz tACS was applied to the frontoparietal network. Synchronized tACS was shown to affect signaling within as well as beyond the targeted network. The study demonstrates how inter-regional oscillatory coherence supports the control of brain network signaling.

Alpha-band cortico-cortical phase synchronization is associated with effective connectivity in the motor network

ObjectiveCommunication-through-coherence proposes that the phase synchronization (PS) of neural oscillations between cortical areas supports neural communication. In this study, we exploited transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) to test this hypothesis at the macroscale level, i.e., whether PS between cortical areas supports interarea communication. TEPs are electroencephalographic (EEG) responses time-locked to TMS pulses reflecting interarea communication, as they are generated by the transmission of neural activity from the stimulated area to connected regions. If interarea PS is important for communication, it should be associated with the TEP amplitude in the connected areas. MethodsTMS was delivered over the left primary motor cortex (M1) of fourteen healthy volunteers, and 70-channel EEG was recorded. Early TEP components were source-localized to identify their generators, i.e., distant brain regions activated by M1 through effective connections. Next, linear regressions were used to test the relationship between the TEP amplitude and the pre-stimulus PS between the M1 and the connected regions in four frequency bands (range 4–45 Hz). ResultsPre-stimulus interarea PS in the alpha-band was positively associated with the amplitude of early TEP components, namely, the N15 (ipsilateral supplementary motor area), P25 (contralateral M1) and P60 (ipsilateral parietal cortex). ConclusionsAlpha-band PS predicts the response amplitude of the distant brain regions effectively connected to M1. SignificanceOur study supports the role of EEG-PS in interarea communication, as theorized by communication-through-coherence.

O-TS004. Site-specific decrease in cortical reactivity during sensory trick in cervical dystonia patients

Introduction . Sensory tricks (SeT) are various maneuvers that can alleviate dystonic contractions and are a characteristic feature of cervical dystonia (CD). The neurophysiology underlying SeT, however, still remains largely unknown. Reducing the abnormal cortical facilitation and modulating the abnormal cortical and subcortical oscillatory activity are likely mechanisms that have been proposed. The supplementary motor area (SMA) and primary sensorimotor cortices are thought to be involved in this phenomenon. In the current study, using concurrent EEG recording during transcranial magnetic stimulation (TMS) of the SMA and primary motor cortex (M1), we aimed at determining the changes in cortical reactivity and oscillatory activity induced by SeT. Method . We recruited thirteen patients with CD who exhibited SeT and equal number of age- and gender-matched healthy controls. Single TMS pulses were delivered over the SMA and M1 either at rest or during SeT. 32-channel EEG was recorded and TMS-evoked potentials were obtained. Further, time-frequency analysis was performed on the induced data. Correlation analysis for significant neurophysiological parameters was done with clinical measures. Results . In the current study, we found that SeT induced a significant decrease in the amplitude of TEP elicited from M1 stimulation at ∼210–260 ms in patients, which correlated with symptom duration. Post hoc analysis of EMG activity in the neck muscles revealed that this effect on TEP was present only in the subset of patients with effective SeT. Conclusion . Our results suggest that SeT reduces cortical reactivity over M1 approximately 200ms after stimulation. This adds support to the idea that reduced cortical facilitation underlies the phenomenon.

Investigating neurophysiological markers of impaired cognition in schizophrenia

Cognitive impairment is highly prevalent in schizophrenia and treatment options are severely limited. A greater understanding of the pathophysiology of impaired cognition would have broad implications, including for the development of effective treatments. In the current study we used a multimodal approach to identify neurophysiological markers of cognitive impairment in schizophrenia. Fifty-seven participants (30 schizophrenia, 27 controls) underwent neurobiological assessment (electroencephalography [EEG] and Transcranial Magnetic Stimulation combined with EEG [TMS-EEG]) and assessment of cognitive functioning using an n-back task and the MATRICS Consensus Cognitive Battery. Neurobiological outcome measures included oscillatory power during a 2-back task, TMS-related oscillations and TMS-evoked potentials (TEPs). Cognitive outcome measures were d prime and accurate reaction time on the 2-back and MATRICS domain scores. Compared to healthy controls, participants with schizophrenia showed significantly reduced theta oscillations in response to TMS, and trend level decreases in task-related theta and cortical reactivity (i.e. reduced N100 and N40 TEPs). Participants with schizophrenia also showed significantly impaired cognitive performance across all measures. Correlational analysis identified significant associations between cortical reactivity and TMS-related oscillations in both groups; and trend level associations between task-related oscillations and impaired cognition in schizophrenia. The current study provides experimental support for possible neurophysiological markers of cognitive impairment in schizophrenia. The potential implications of these findings, including for treatment development, are discussed.

A multimodal approach using TMS and EEG reveals neurophysiological changes in Parkinson's disease

IntroductionAlterations in large scale neural networks leading to neurophysiological changes have been described in Parkinson's disease (PD). The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been suggested as a promising tool to identify and quantify neurophysiological mechanisms. The aim of this study was to investigate specific changes in electrical brain activity in response to stimulation of four brain areas in patients with PD. Methods21 healthy controls and 32 patients with PD underwent a combined TMS-EEG assessment that included stimulation of four brain areas: left M1, right M1, left dorso-lateral prefrontal cortex (DLPFC), and right DLPFC. Six measures were calculated to characterize the TMS evoked potentials (TEP) using EEG: (1) wave form adherence (WFA), (2) late phase deflection (LPD), (3) early phase deflection (EPD), (4) short-term plasticity (STP), (5) inter-trial adherence, and (6) connectivity between right and left M1 and DLPFC. A Linear mixed-model was used to compare these measures between groups and areas stimulated. ResultsPatients with PD showed lower WFA (p = 0.052), lower EPD (p = 0.009), lower inter-trial adherence (p < 0.001), and lower connectivity between homologs areas (p = 0.050), compared to healthy controls. LPD and STP measures were not different between the groups. In addition, lower inter-trial adherence correlated with longer disease duration (r = −0.355, p = 0.050). ConclusionsOur findings provide evidence to various alterations in neurophysiological measures in patients with PD. The higher cortical excitability along with increased variability and lower widespread of the evoked potentials in PD can elucidate different aspects related to the pathophysiology of the disease.

The impact of artifact removal approaches on TMS–EEG signal

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) allow one to assess cortical excitability and effective connectivity in clinical and basic research. However, obtaining clean TEPs is challenging due to the various TMS-related artifacts that contaminate the electroencephalographic (EEG) signal when the TMS pulse is delivered. Different preprocessing approaches have been employed to remove the artifacts, but the degree of artifact reduction or signal distortion introduced in this phase of analysis is still unknown. Knowing and controlling this potential source of uncertainty will increase the inter-rater reliability of TEPs and improve the comparability between TMS–EEG studies. The goal of this study was to assess the variability in TEP waveforms due to of the use of different preprocessing pipelines. To accomplish this aim, we preprocessed the same TMS–EEG data with four different pipelines and compared the results. The dataset was obtained from 16 subjects in two identical recording sessions, each session consisting of both left dorsolateral prefrontal cortex and left inferior parietal lobule stimulation at 100% of the resting motor threshold. Considerable differences in TEP amplitudes and global mean field power (GMFP) were found between the preprocessing pipelines. Topographies of TEPs from the different pipelines were all highly correlated (ρ>0.8) at latencies over 100 ms. By contrast, waveforms at latencies under 100 ms showed a variable level of correlation, with ρ ranging between 0.2 and 0.9. Moreover, the test–retest reliability of TEPs depended on the preprocessing pipeline. Taken together, these results take us to suggest that the choice of the preprocessing approach has a marked impact on the final TEP, and that further studies are needed to understand advantages and disadvantages of the different approaches.

Motor adaptation and internal model formation in a robot-mediated forcefield.

Motor adaptation relies on error-based learning for accurate movements in changing environments. However, the neurophysiological mechanisms driving individual differences in performance are unclear. Transcranial magnetic stimulation (TMS)-evoked potential can provide a direct measure of cortical excitability. To investigate cortical excitability as a predictor of motor learning and motor adaptation in a robot-mediated forcefield. A group of 15 right-handed healthy participants (mean age 23 years) performed a robot-mediated forcefield perturbation task. There were two conditions: unperturbed non-adaptation and perturbed adaptation. TMS was applied in the resting state at baseline and following motor adaptation over the contralateral primary motor cortex (left M1). Electroencephalographic (EEG) activity was continuously recorded, and cortical excitability was measured by TMS-evoked potential (TEP). Motor learning was quantified by the motor learning index. Larger error-related negativity (ERN) in fronto-central regions was associated with improved motor performance as measured by a reduction in trajectory errors. Baseline TEP N100 peak amplitude predicted motor learning (P=0.005), which was significantly attenuated relative to baseline (P=0.0018) following motor adaptation. ERN reflected the formation of a predictive internal model adapted to the forcefield perturbation. Attenuation in TEP N100 amplitude reflected an increase in cortical excitability with motor adaptation reflecting neuroplastic changes in the sensorimotor cortex. TEP N100 is a potential biomarker for predicting the outcome in robot-mediated therapy and a mechanism to investigate psychomotor abnormalities in depression.

Neurophysiological effects of repetitive transcranial magnetic stimulation (rTMS) in treatment resistant depression

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) is effective for treatment resistant depression (TRD), but little is known about rTMS’ effects on neurophysiological markers. We previously identified neurophysiological markers in depression (N45 and N100) of GABA receptor mediated inhibition. Here, we indexed TMS-electroencephalographic (TMS-EEG) effects of rTMS. MethodsTMS-EEG data was analyzed from a double blind 2:1 randomized active (10 Hz left/bilateral):sham rTMS TRD trial. Participants underwent TMS-EEG over left dorsolateral prefrontal cortex (DLPFC) before and after 6 weeks of rTMS. 30 had useable datasets. TMS-evoked potentials (TEP) and components (N45, N100, P60) were examined with global mean field analysis (GMFA) and locally in DLPFC regions of interest. ResultsThe N45 amplitude differed between active and sham groups over time, N100 amplitude did not. N45 (t = 2.975, p = 0.007) and N100 amplitudes (t = 2.177, p = 0.042) decreased after active rTMS, demonstrating alterations in cortical inhibition. TEP amplitudes decreased after active rTMS in left (t = 4.887, p < 0.001) and right DLPFC (t = 4.403, p < 0.001) not sham rTMS, demonstrating alterations in cortical excitability. ConclusionsOur results provide important new knowledge regarding rTMS effects on TMS-EEG measures in TRD, suggesting rTMS reduces neurophysiological markers of inhibition and excitability. SignificanceThese findings uncover potentially important neurophysiological mechanisms of rTMS action.

Assessing cerebellar-cortical connectivity using concurrent TMS-EEG: a feasibility study.

Combined single-pulse transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been used to probe the features of local networks in the cerebral cortex. Here, we investigated whether we can use this approach to explore long-range connections between the cerebellum and cerebral cortex. Ten healthy adults received single-pulse suprathreshold TMS to the cerebellum and an occipital/parietal control site with double-cone and figure-of-eight coils while cerebral activity was recorded. A multisensory electrical control condition was used to simulate the sensation of the double-cone coil at the cerebellar site. Two cleaning pipelines were compared, and the spatiotemporal relationships of the EEG output between conditions were examined at sensor and source levels. Cerebellar stimulation with the double-cone coil resulted in large artifact in the EEG trace. The addition of SOUND filtering to the cleaning pipeline improved the signal such that further analyses could be undertaken. The cortical potentials evoked by the active TMS conditions showed strong relationships with the responses to the multisensory control condition after ∼50 ms. A distinct parietal component at ∼42 ms was found following cerebellar double-cone stimulation. Although evoked potentials differed across all conditions at early latencies, it is unclear as to whether these represented TMS-related network activation of the cerebellarthalamocortical tract, or whether components were dominated by sensory contamination and/or coil-driven artifact. This study highlights the need for caution when interpreting outcomes from cerebellar TMS-EEG studies.NEW & NOTEWORTHY This is the first study to systematically assess the feasibility of obtaining TMS-evoked potentials from cerebellar stimulation with concurrent EEG. An innovative control condition using electrical stimulation was modified to mimic the sensory aspects of cerebellar stimulation with a double-cone coil, and a state-of-the art cleaning pipeline was trialled. The extent of artifact contamination in signals from stimulation of a cerebellar and an occipital/parietal control site using two TMS coil types was highlighted.

Single-Pulse TMS to the Temporo-Occipital and Dorsolateral Prefrontal Cortex Evokes Lateralized Long Latency EEG Responses at the Stimulation Site.

IntroductionTranscranial magnetic stimulation (TMS)–evoked potentials (TEPs) allow for probing cortical functions in health and pathology. However, there is uncertainty whether long-latency TMS-evoked potentials reflect functioning of the targeted cortical area. It has been suggested that components such as the TMS-evoked N100 are stereotypical and related to nonspecific sensory processes rather than transcranial effects of the changing magnetic field. In contrast, TEPs that vary according to the targeted brain region and are systematically lateralized toward the stimulated hemisphere can be considered to reflect activity in the stimulated brain region resulting from transcranial electromagnetic induction.MethodsTMS with concurrent 64-channel electroencephalography (EEG) was sequentially performed in homologous areas of both hemispheres. One sample of healthy adults received TMS to the dorsolateral prefrontal cortex; another sample received TMS to the temporo-occipital cortex. We analyzed late negative TEP deflections corresponding to the N100 component in motor cortex stimulation.ResultsTEP topography varied according to the stimulation target site. Long-latency negative TEP deflections were systematically lateralized (higher in ipsilateral compared to contralateral electrodes) in electrodes over the stimulated brain region. A calculation that removes evoked components that are not systematically lateralized relative to the stimulated hemisphere revealed negative maxima located around the respective target sites.ConclusionTEPs contain long-latency negative components that are lateralized toward the stimulated hemisphere and have their topographic maxima at the respective stimulation sites. They can be differentiated from co-occurring components that are invariable across different stimulation sites (probably reflecting coactivation of peripheral sensory afferences) according to their spatiotemporal patterns. Lateralized long-latency TEP components located at the stimulation site likely reflect activity evoked in the targeted cortex region by direct transcranial effects and are therefore suitable for assessing cortical functions.

Preconditioning Stimulus Intensity Alters Paired-Pulse TMS Evoked Potentials.

Motor cortex (M1) paired-pulse TMS (ppTMS) probes excitatory and inhibitory intracortical dynamics by measurement of motor-evoked potentials (MEPs). However, MEPs reflect cortical and spinal excitabilities and therefore cannot isolate cortical function. Concurrent TMS-EEG has the ability to measure cortical function, while limiting peripheral confounds; TMS stimulates M1, whilst EEG acts as the readout: the TMS-evoked potential (TEP). Whilst varying preconditioning stimulus intensity influences intracortical inhibition measured by MEPs, the effects on TEPs is undefined. TMS was delivered to the left M1 using single-pulse and three, ppTMS paradigms, each using a different preconditioning stimulus: 70%, 80% or 90% of resting motor threshold. Corticospinal inhibition was present in all three ppTMS conditions. ppTMS TEP peaks were reduced predominantly under the ppTMS 70 protocol but less so for ppTMS 80 and not at all for ppTMS 90. There was a significant negative correlation between MEPs and N45 TEP peak for ppTMS 70 reaching statistical trends for ppTMS 80 and 90. Whilst ppTMS MEPs show inhibition across a range of preconditioning stimulus intensities, ppTMS TEPs do not. TEPs after M1 ppTMS vary as a function of preconditioning stimulus intensity: smaller preconditioning stimulus intensities result in better discriminability between conditioned and unconditioned TEPs. We recommend that preconditioning stimulus intensity should be minimized when using ppTMS to probe intracortical inhibition.

Local Differences in Cortical Excitability - A Systematic Mapping Study of the TMS-Evoked N100 Component.

Transcranial magnetic stimulation (TMS) with simultaneous electroencephalography applied to the primary motor cortex provides two parameters for cortical excitability: motor evoked potentials (MEPs) and TMS-evoked potentials (TEPs). This study aimed to evaluate the effects of systematic coil shifts on both the TEP N100 component and MEPs in addition to the relationship between both parameters. In 12 healthy adults, the center of a standardized grid was fixed above the hot spot of the target muscle of the left primary motor cortex. Twelve additional positions were arranged in a quadratic grid with positions between 5 and 10 mm from the hot spot. At each of the 13 positions, TMS single pulses were applied. The topographical maximum of the resulting N100 was located ipsilateral and slightly posterior to the stimulation site. A source analysis revealed an equivalent dipole localized more deeply than standard motor cortex coordinates that could not be explained by a single seeded primary motor cortex dipole. The N100 topography might not only reflect primary motor cortex activation, but also sum activation of the surrounding cortex. N100 amplitude and latency decreased significantly during stimulation anterior-medial to the hot spot although MEP amplitudes were smaller at all other stimulation sites. Therefore, N100 amplitudes might be suitable for detecting differences in local cortical excitability. The N100 topography, with its maximum located posterior to the stimulation site, possibly depends on both anatomical characteristics of the stimulated cortex and differences in local excitability of surrounding cortical areas. The less excitable anterior cortex might contribute to a more posterior maximum. There was no correlation between N100 and MEP amplitudes, but a single-trial analysis revealed a trend toward larger N100 amplitudes in trials with larger MEPs. Thus, functionally efficient cortical excitation might increase the probability of higher N100 amplitudes, but TEPs are also generated in the absence of MEPs.