The effects of NMDA receptor blockade on TMS-evoked EEG potentials from prefrontal and parietal cortex

Protocol to assess changes in brain network resistance to perturbation during offline processing using TMS-EEG

Transcranial magnetic stimulation (TMS) perturbs specific brain regions and, combined with electroencephalography (EEG), enables the assessment of activity within their connected networks. We present a resting-state TMS-EEG protocol, combined with a controlled experimental design, to assess changes in brain network activity during offline processing, following a behavioral task. We describe steps for experimental design planning, setup preparation, data collection, and analysis. This approach minimizes biases inherent to TMS-EEG, ensuring an accurate assessment of changes within the network. For complete details of the use and execution of this protocol, please refer to Bracco et al.1.

Disinhibition across Secondary Motor Cortical Regions during Motor Sequence Learning: A TMS-EEG Study

Secondary motor cortical regions, such as the supplementary motor area (SMA), are involved in planning and learning motor sequences; however, the neurophysiological mechanisms across these secondary cortical networks remain poorly understood. In the primary motor cortex, changes in excitatory and inhibitory neurotransmission (E:I balance) accompany motor sequence learning. In particular, there is an early reduction in inhibition (i.e., disinhibition). Here, we investigated whether disinhibition occurs across secondary motor cortical regions during motor sequence learning using combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Twenty-nine healthy adults (14 female) practiced a sequential motor task with TMS applied to the SMA during sequence planning. TMS-evoked potentials (TEPs) were measured with EEG before, during, and after practice. The N45 TEP peak was our primary measure of disinhibition, while we analyzed the slope of aperiodic EEG activity as an additional E:I balance measure. We observed a reduction in N45 amplitudes across an electrode cluster encompassing the SMA and nearby cortical regions as participants began learning new motor sequences, compared with a baseline rest phase (p < 0.01). Smaller N45 amplitudes during early learning were associated with improvements in reaction times across learning (p < 0.05). Intriguingly, aperiodic exponents increased as learning progressed and were associated with greater improvements in skill (p < 0.05). Overall, our results show that inhibition is modulated across SMA and secondary motor cortex during the planning phase of motor sequence learning and thus provide novel insight on the neurophysiological mechanisms within higher-order motor cortex that accompany new sequence learning.

Influence of Large-Scale Brain State Dynamics on the Evoked Response to Brain Stimulation

Understanding how spontaneous brain activity influences the response to neurostimulation is crucial for the development of neurotherapeutics and brain-computer interfaces. Localized brain activity is suggested to influence the response to neurostimulation, but whether fast-fluctuating (i.e., tens of milliseconds) large-scale brain dynamics also have any such influence is unknown. By stimulating the prefrontal cortex using combined transcranial magnetic stimulation (TMS) and electroencephalography, we examined how dynamic global brain state patterns, as defined by microstates, influence the magnitude of the evoked brain response. TMS applied during what resembled the canonical Microstate C was found to induce a greater evoked response for up to 80 ms compared with other microstates. This effect was found in a repeated experimental session, was absent during sham stimulation, and was replicated in an independent dataset. Ultimately, ongoing and fast-fluctuating global brain states, as probed by microstates, may be associated with intrinsic fluctuations in connectivity and excitation-inhibition balance and influence the neurostimulation outcome. We suggest that the fast-fluctuating global brain states be considered when developing any related paradigms.

Neurophysiological markers of disease severity and cognitive dysfunction in major depressive disorder: A TMS-EEG study

Background

Transcranial magnetic stimulation-electroencephalography (TMS-EEG) is a powerful technique to study the neuropathology and biomarkers of major depressive disorder (MDD). This study investigated cortical activity and its relationship with clinical symptoms and cognitive dysfunction in MDD patients by indexing TMS-EEG biomarkers in the dorsolateral prefrontal cortex (DLPFC).

Methods

133 patients with MDD and 76 healthy individuals participated in this study. Single-pulse TMS was performed on the left DLPFC to obtain TMS-evoked potential (TEP) indices. TMS-EEG waveforms and components were determined by global mean field amplitude. We used the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) to measure participants' cognitive function.

Results

Patients with MDD had a lower excitatory P180 index compared to healthy controls, and P180 amplitude was negatively correlated with the severity of depressive and anxiety symptoms in patients with MDD. In the MDD group, P30 amplitude was negatively associated with RBANS Visuospatial/ Constructional index and total score.

Conclusions

TMS-EEG findings suggest that abnormal cortical excitation and inhibition induced by TMS on the DLPFC are associated with the severity of clinical symptoms and cognitive dysfunction in patients with MDD. P180 and P30 have the potential to serve as neurophysiological biomarkers of clinical symptoms and cognitive dysfunction in MDD patients, respectively.

Investigating cortical excitability and inhibition in patients with schizophrenia: A TMS-EEG study

BACKGROUND

Transcranial magnetic stimulation (TMS) combined with electromyography (EMG) has widely been used as a non-invasive brain stimulation tool to assess excitation/inhibition (E/I) balance. E/I imbalance is a putative mechanism underlying symptoms in patients with schizophrenia. Combined TMS-electroencephalography (TMS-EEG) provides a detailed examination of cortical excitability to assess the pathophysiology of schizophrenia. This study aimed to investigate differences in TMS-evoked potentials (TEPs), TMS-related spectral perturbations (TRSP) and intertrial coherence (ITC) between patients with schizophrenia and healthy controls.

MATERIALS AND METHODS

TMS was applied over the motor cortex during EEG recording. Differences in TEPs, TRSP and ITC between the patient and healthy subjects were analysed for all electrodes at each time point, by applying multiple independent sample t-tests with a cluster-based permutation analysis to correct for multiple comparisons.

RESULTS

Patients demonstrated significantly reduced amplitudes of early and late TEP components compared to healthy controls. Patients also showed a significant reduction of early delta (50-160 ms) and theta TRSP (30-250ms),followed by a reduction in alpha and beta suppression (220-560 ms; 190-420 ms). Patients showed a reduction of both early (50-110 ms) gamma increase and later (180-230 ms) gamma suppression. Finally, the ITC was significantly lower in patients in the alpha band, from 30 to 260 ms.

CONCLUSION

Our findings support the putative role of impaired GABA-receptor mediated inhibition in schizophrenia impacting excitatory neurotransmission. Further studies can usefully elucidate mechanisms underlying specific symptoms clusters using TMS-EEG biometrics.

Stability of transcranial magnetic stimulation electroencephalogram evoked potentials in pediatric epilepsy

Transcranial magnetic stimulation paired with electroencephalography (TMS-EEG) can measure local excitability and functional connectivity. To address trial-to-trial variability, responses to multiple TMS pulses are recorded to obtain an average TMS evoked potential (TEP). Balancing adequate data acquisition to establish stable TEPs with feasible experimental duration is critical when applying TMS-EEG to clinical populations. Here we aim to investigate the minimum number of pulses (MNP) required to achieve stable TEPs in children with epilepsy. Eighteen children with Self-Limited Epilepsy with Centrotemporal Spikes, a common epilepsy arising from the motor cortices, underwent multiple 100-pulse blocks of TMS to both motor cortices over two days. TMS was applied at 120% of resting motor threshold (rMT) up to a maximum of 100% maximum stimulator output. The average of all 100 pulses was used as a "gold-standard" TEP to which we compared "candidate" TEPs obtained by averaging subsets of pulses. We defined TEP stability as the MNP needed to achieve a concordance correlation coefficient of 80% between the candidate and "gold-standard" TEP. We additionally assessed whether experimental or clinical factors affected TEP stability. Results show that stable TEPs can be derived from fewer than 100 pulses, a number typically used for designing TMS-EEG experiments. The early segment (15-80 ms) of the TEP was less stable than the later segment (80-350 ms). Global mean field amplitude derived from all channels was less stable than local TEP derived from channels overlying the stimulated site. TEP stability did not differ depending on stimulated hemisphere, block order, or antiseizure medication use, but was greater in older children. Stimulation administered with an intensity above the rMT yielded more stable local TEPs. Studies of TMS-EEG in pediatrics have been limited by the complexity of experimental set-up and time course. This study serves as a critical starting point, demonstrating the feasibility of designing efficient TMS-EEG studies that use a relatively small number of pulses to study pediatric epilepsy and potentially other pediatric groups.

Transcranial Magnetic Stimulation-Electroencephalography for Biomarker Discovery in Psychiatry

Current diagnosis and treatment of psychiatric illnesses are still based on behavioral observations and self-reports, commonly leading to prolonged untreated illness. Biological markers (biomarkers) may offer an opportunity to revolutionize clinical psychiatry practice by helping provide faster and potentially more effective therapies. Transcranial magnetic stimulation concurrent with electroencephalography (TMS-EEG) is a noninvasive brain mapping methodology that can assess the functions and dynamics of specific brain circuitries in awake humans and aid in biomarker discovery. This article provides an overview of TMS-EEG-based biomarkers that may hold potential in psychiatry. The methodological readiness of the TMS-EEG approach and steps in the validation of TMS-EEG biomarkers for clinical utility are discussed. Biomarker discovery with TMS-EEG is in the early stages, and several validation steps are still required before clinical implementations are realized. Thus far, TMS-EEG predictors of response to magnetic brain stimulation treatments in particular have shown promise for translation to clinical practice. Larger-scale studies can confirm validation followed by biomarker-informed trials to assess added value compared to existing practice.

Evoked EEG Responses to TMS Targeting Regions Outside the Primary Motor Cortex and Their Test-Retest Reliability

Transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) potentials (TEPs) provide unique insights into cortical excitability and connectivity. However, confounding EEG signals from auditory and somatosensory co-stimulation complicate TEP interpretation. Our optimized sham procedure established with TMS of primary motor cortex (Gordon in JAMA 245:118708, 2021) differentiates direct cortical EEG responses to TMS from those caused by peripheral sensory inputs. Using this approach, this study aimed to investigate TEPs and their test-retest reliability when targeting regions outside the primary motor cortex, specifically the left angular gyrus, supplementary motor area, and medial prefrontal cortex. We conducted three identical TMS-EEG sessions one week apart involving 24 healthy participants. In each session, we targeted the three areas separately using a figure-of-eight TMS coil for active TMS, while a second coil away from the head produced auditory input for sham TMS. Masking noise and electric scalp stimulation were applied in both conditions to achieve matched EEG responses to peripheral sensory inputs. High test-retest reliability was observed in both conditions. However, reliability declined for the 'cleaned' TEPs, resulting from the subtraction of evoked EEG response to the sham TMS from those to the active, particularly for latencies > 100 ms following the TMS pulse. Significant EEG differences were found between active and sham TMS at latencies < 90 ms for all targeted areas, exhibiting distinct spatiotemporal characteristics specific to each target. In conclusion, our optimized sham procedure effectively reveals EEG responses to direct cortical activation by TMS in brain areas outside primary motor cortex. Moreover, we demonstrate the impact of peripheral sensory inputs on test-retest reliability of TMS-EEG responses.

Effective connectivity abnormalities in Lewy body disease with visual hallucinations

OBJECTIVE

To assess the changes in effective connectivity of important regions of the visual network (VIS) and dorsal attention network (DAN) underlying visual hallucinations (VHs) in Dementia with Lewy Bodies (DLB), Parkinson's Disease (PD) and Parkinson's Disease Dementia (PDD), as measured by a transcranial magnetic stimulation-electroencephalographic technique (TMS-EEG).

METHODS

We stimulated the right visual cortex (V1/V2), the right intraparietal sulcus and the right frontal eye fields, two key regions of the DAN, and measured TMS-evoked cortical activation within the VIS and the DAN. We compared 11 patients with VHs and 15 patients without VHs.

RESULTS

Patients with VHs showed lower TMS-evoked cortical activation within the DAN following intraparietal sulcus and frontal eye fields stimulation than patients without VHs. No difference was found between patients with and without cognitive impairment. Also, when considering only patients with cognitive impairment, VHs were associated with lower TMS-evoked cortical activation following intraparietal sulcus stimulation.

CONCLUSIONS

DLB, PD, and PDD patients with VHs had less effective connectivity of the right intraparietal sulcus within the DAN than patients without VHs.

SIGNIFICANCE

We provided the first evidence that VHs are associated with specific intraparietal sulcus dysfunction within the DAN in patients with PDD, PD, and DLB.

Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers

Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.

Motor potentials evoked by transcranial magnetic stimulation: interpreting a simple measure of a complex system

Transcranial magnetic stimulation (TMS) is a non-invasive technique that is increasingly used to study the human brain. One of the principal outcome measures is the motor-evoked potential (MEP) elicited in a muscle following TMS over the primary motor cortex (M1), where it is used to estimate changes in corticospinal excitability. However, multiple elements play a role in MEP generation, so even apparently simple measures such as peak-to-peak amplitude have a complex interpretation. Here, we summarize what is currently known regarding the neural pathways and circuits that contribute to the MEP and discuss the factors that should be considered when interpreting MEP amplitude measured at rest in the context of motor processing and patients with neurological conditions. In the last part of this work, we also discuss how emerging technological approaches can be combined with TMS to improve our understanding of neural substrates that can influence MEPs. Overall, this review aims to highlight the capabilities and limitations of TMS that are important to recognize when attempting to disentangle sources that contribute to the physiological state-related changes in corticomotor excitability.

Immediate Effects of Intermittent Theta Burst Stimulation on Primary Motor Cortex in Stroke Patients: A Concurrent TMS-EEG Study

The neurophysiological effect of intermittent theta burst stimulation (iTBS) has been examined with TMS-electromyography (EMG)-based outcomes in healthy people; however, its effects in intracortical excitability and inhibition are largely unknown in patients with stroke. Concurrent transcranial magnetic stimulation and electroencephalogram (TMS-EEG) recording can be used to investigate both intracortical excitatory and inhibitory circuits of the primary motor cortex (M1) instantly and the property of brain networks at once. This study was to investigate the immediate effects of iTBS on intracortical excitatory and inhibitory circuits, neural connectivity, and network properties in patients with chronic stroke, using TMS-EEG and TMS-EMG approaches. In this randomized, sham-controlled, crossover study, 20 patients with chronic stroke received two separate stimulation conditions: a single-session iTBS or sham stimulation applied to the ipsilesional M1, in two separate visits, with a washout period of five to seven days between the two visits. A battery of TMS-EMG and TMS-EEG measurements were taken before and immediately after stimulation during the visit. Compared with sham stimulation, iTBS was effective in enhancing the amplitude of ipsilesional MEPs (p = 0.015) and P30 of TMS-evoked potentials located at the ipsilesional M1 (p = 0.037). However, iTBS did not show superior effects on ipsilesional intracortical facilitation, cortical silent period, or short-interval intracortical inhibition. Regarding the effects on TMS-related oscillations, and neural connectivity, comparisons of iTBS and sham did not yield any significant differences. iTBS facilitates intracortical excitability in patients with chronic stroke, but it does not show modulatory effects in intracortical inhibition.

TMS-EEG perturbation biomarkers for Alzheimer's disease patients classification

The combination of TMS and EEG has the potential to capture relevant features of Alzheimer's disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45-80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients' classification as well as longitudinal disease tracking.

Isolating sensory artifacts in the suprathreshold TMS-EEG signal over DLPFC

Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an effective way to evaluate neurophysiological processes at the level of the cortex. To further characterize the TMS-evoked potential (TEP) generated with TMS-EEG, beyond the motor cortex, we aimed to distinguish between cortical reactivity to TMS versus non-specific somatosensory and auditory co-activations using both single-pulse and paired-pulse protocols at suprathreshold stimulation intensities over the left dorsolateral prefrontal cortex (DLPFC). Fifteen right-handed healthy participants received six blocks of stimulation including single and paired TMS delivered as active-masked (i.e., TMS-EEG with auditory masking and foam spacing), active-unmasked (TMS-EEG without auditory masking and foam spacing) and sham (sham TMS coil). We evaluated cortical excitability following single-pulse TMS, and cortical inhibition following a paired-pulse paradigm (long-interval cortical inhibition (LICI)). Repeated measure ANOVAs revealed significant differences in mean cortical evoked activity (CEA) of active-masked, active-unmasked, and sham conditions for both the single-pulse (F(1.76, 24.63) = 21.88, p < 0.001, η² = 0.61) and LICI (F(1.68, 23.49) = 10.09, p < 0.001, η² = 0.42) protocols. Furthermore, global mean field amplitude (GMFA) differed significantly across the three conditions for both single-pulse (F(1.85, 25.89) = 24.68, p < 0.001, η² = 0.64) and LICI (F(1.8, 25.16) = 14.29, p < 0.001, η² = 0.5). Finally, only active LICI protocols but not sham stimulation ([active-masked (0.78 ± 0.16, P < 0.0001)], [active-unmasked (0.83 ± 0.25, P < 0.01)]) resulted in significant signal inhibition. While previous findings of a significant somatosensory and auditory contribution to the evoked EEG signal are replicated by our study, an artifact attenuated cortical reactivity can reliably be measured in the TMS-EEG signal with suprathreshold stimulation of DLPFC. Artifact attenuation can be accomplished using standard procedures, and even when masked, the level of cortical reactivity is still far above what is produced by sham stimulation. Our study illustrates that TMS-EEG of DLPFC remains a valid investigational tool.

Transferability of cathodal tDCS effects from the primary motor to the prefrontal cortex: A multimodal TMS-EEG study

Neurophysiological effects of transcranial direct current stimulation (tDCS) have been extensively studied over the primary motor cortex (M1). Much less is however known about its effects over non-motor areas, such as the prefrontal cortex (PFC), which is the neuronal foundation for many high-level cognitive functions and involved in neuropsychiatric disorders. In this study, we, therefore, explored the transferability of cathodal tDCS effects over M1 to the PFC. Eighteen healthy human participants (11 males and 8 females) were involved in eight randomized sessions per participant, in which four cathodal tDCS dosages, low, medium, and high, as well as sham stimulation, were applied over the left M1 and left PFC. After-effects of tDCS were evaluated via transcranial magnetic stimulation (TMS)-electroencephalography (EEG), and TMS-elicited motor evoked potentials (MEP), for the outcome parameters TMS-evoked potentials (TEP), TMS-evoked oscillations, and MEP amplitude alterations. TEPs were studied both at the regional and global scalp levels. The results indicate a regional dosage-dependent nonlinear neurophysiological effect of M1 tDCS, which is not one-to-one transferable to PFC tDCS. Low and high dosages of M1 tDCS reduced early positive TEP peaks (P30, P60), and MEP amplitudes, while an enhancement was observed for medium dosage M1 tDCS (P30). In contrast, prefrontal low, medium and high dosage tDCS uniformly reduced the early positive TEP peak amplitudes. Furthermore, for both cortical areas, regional tDCS-induced modulatory effects were not observed for late TEP peaks, nor TMS-evoked oscillations. However, at the global scalp level, widespread effects of tDCS were observed for both, TMS-evoked potentials and oscillations. This study provides the first direct physiological comparison of tDCS effects applied over different brain areas and therefore delivers crucial information for future tDCS applications.

RELAX part 2: A fully automated EEG data cleaning algorithm that is applicable to Event-Related-Potentials

OBJECTIVE

Electroencephalography (EEG) is often used to examine neural activity time-locked to stimuli presentation, referred to as Event-Related Potentials (ERP). However, EEG is influenced by non-neural artifacts, which can confound ERP comparisons. Artifact cleaning reduces artifacts, but often requires time-consuming manual decisions. Most automated methods filter frequencies <1 Hz out of the data, so are not recommended for ERPs (which contain frequencies <1 Hz). Our aim was to test the RELAX (Reduction of Electroencephalographic Artifacts) pre-processing pipeline for use on ERP data.

METHODS

The cleaning performance of multiple versions of RELAX were compared to four commonly used EEG cleaning pipelines across both artifact cleaning metrics and the amount of variance in ERPs explained by different conditions in a Go-Nogo task. Results RELAX with Multi-channel Wiener Filtering (MWF) and wavelet-enhanced independent component analysis applied to artifacts identified with ICLabel (wICA_ICLabel) cleaned data most effectively and produced amongst the most dependable ERP estimates. RELAX with wICA_ICLabel only or MWF_only may detect effects better for some ERPs.

CONCLUSIONS

RELAX shows high artifact cleaning performance even when data is high-pass filtered at 0.25 Hz (applicable to ERP analyses).

SIGNIFICANCE

RELAX is easy to implement via EEGLAB in MATLAB and freely available on GitHub. Given its performance and objectivity we recommend RELAX to improve artifact cleaning and consistency across ERP research.

Introducing RELAX: An automated pre-processing pipeline for cleaning EEG data - Part 1: Algorithm and application to oscillations

OBJECTIVE

Electroencephalographic (EEG) data are often contaminated with non-neural artifacts which can confound experimental results. Current artifact cleaning approaches often require costly manual input. Our aim was to provide a fully automated EEG cleaning pipeline that addresses all artifact types and improves measurement of EEG outcomes METHODS: We developed RELAX (the Reduction of Electroencephalographic Artifacts). RELAX cleans continuous data using Multi-channel Wiener filtering [MWF] and/or wavelet enhanced independent component analysis [wICA] applied to artifacts identified by ICLabel [wICA_ICLabel]). Several versions of RELAX were compared using three datasets (N = 213, 60 and 23 respectively) against six commonly used pipelines across a range of artifact cleaning metrics, including measures of remaining blink and muscle activity, and the variance explained by experimental manipulations after cleaning.

RESULTS

RELAX with MWF and wICA_ICLabel showed amongst the best performance at cleaning blink and muscle artifacts while preserving neural signal. RELAX with wICA_ICLabel only may perform better at differentiating alpha oscillations between working memory conditions.

CONCLUSIONS

RELAX provides automated, objective and high-performing EEG cleaning, is easy to use, and freely available on GitHub.

SIGNIFICANCE

We recommend RELAX for data cleaning across EEG studies to reduce artifact confounds, improve outcome measurement and improve inter-study consistency.

Repetitive transcranial magnetic stimulation in primary sleep disorders

Repetitive transcranial magnetic stimulation (rTMS) is a widely used non-invasive neuromodulatory technique. When applied in sleep medicine, the main hypothesis explaining its effects concerns the modulation of synaptic plasticity and the strength of connections between the brain areas involved in sleep disorders. Recently, there has been a significant increase in the publication of rTMS studies in primary sleep disorders. A multi-database-based search converges on the evidence that rTMS is safe and feasible in chronic insomnia, obstructive sleep apnea syndrome (OSAS), restless legs syndrome (RLS), and sleep deprivation-related cognitive deficits, whereas limited or no data are available for narcolepsy, sleep bruxism, and REM sleep behavior disorder. Regarding efficacy, the stimulation of the dorsolateral prefrontal cortex bilaterally, right parietal cortex, and dominant primary motor cortex (M1) in insomnia, as well as the stimulation of M1 leg area bilaterally, left primary somatosensory cortex, and left M1 in RLS reduced subjective symptoms and severity scale scores, with effects lasting for up to weeks; conversely, no relevant effect was observed in OSAS and narcolepsy. Nevertheless, several limitations especially regarding the stimulation protocols need to be considered. This review should be viewed as a step towards the further contribution of individually tailored neuromodulatory techniques for sleep disorders.

Synaptic Plasticity 101: The Story of the AMPA Receptor for the Brain Stimulation Practitioner

The fields of Neurobiology and Neuromodulation have never been closer. Consequently, the phrase "synaptic plasticity" has become very familiar to non-basic scientists, without actually being very familiar. We present the "Story of the AMPA receptor," an easy-to-understand "10,000 ft" narrative overview of synaptic plasticity, oriented toward the brain stimulation clinician or scientist without basic science training. Neuromodulation is unparalleled in its capacity to both modulate and probe plasticity, yet many are not comfortable with their grasp of the topic. Here, we describe the seminal discoveries that defined the canonical mechanisms of long-term potentiation (LTP), long-term depression (LTD), and homeostatic plasticity. We then provide a conceptual framework for how plasticity at the synapse is accomplished, describing the functional roles of N-methyl-d-aspartate (NMDA) receptors and calcium, their effect on calmodulin, phosphatases (ie, calcineurin), kinases (ie, calcium/calmodulin-dependent protein kinase [CaMKII]), and structural "scaffolding" proteins (ie, post-synaptic density protein [PSD-95]). Ultimately, we describe how these affect the α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor. More specifically, AMPA receptor delivery to (LTP induction), removal from (LTD), or recycling within (LTP maintenance) the synapse is determined by the status of phosphorylation and protein binding at specific sites on the tails of AMPA receptor subunits: GluA1 and GluA2. Finally, we relate these to transcranial magnetic stimulation (TMS) treatment, highlighting evidences for LTP as the basis of high-frequency TMS therapy, and briefly touch on the role of plasticity for other brain stimulation modalities. In summary, we present Synaptic Plasticity 101 as a singular introductory reference for those less familiar with the mechanisms of synaptic plasticity.

Investigation of Spatiotemporal Profiles of Single-Pulse TMS-Evoked Potentials with Active Stimulation Compared with a Novel Sham Condition

Identifying genuine cortical stimulation-elicited electroencephalography (EEG) is crucial for improving the validity and reliability of neurophysiology using transcranial magnetic stimulation (TMS) combined with EEG. In this study, we evaluated the spatiotemporal profiles of single-pulse TMS-elicited EEG response administered to the left dorsal prefrontal cortex (DLPFC) in 28 healthy participants, employing active and sham stimulation conditions. We hypothesized that the early component of TEP would be activated in active stimulation compared with sham stimulation. We specifically analyzed the (1) stimulus response, (2) frequency modulation, and (3) phase synchronization of TMS-EEG data at the sensor level and the source level. Compared with the sham condition, the active condition induced a significant increase in TMS-elicited EEG power in the 30-60 ms time interval in the stimulation area at the sensor level. Furthermore, in the source-based analysis, the active condition induced significant increases in TMS-elicited response in the 30-60 ms compared with the sham condition. Collectively, we found that the active condition could specifically activate the early component of TEP compared with the sham condition. Thus, the TMS-EEG method that was applied to the DLPFC could detect the genuine neurophysiological cortical responses by properly handling potential confounding factors such as indirect response noises.

Characterizing TMS-EEG perturbation indexes using signal energy: initial study on Alzheimer's Disease classification

Transcranial Magnetic Stimulation (TMS) combined with EEG recordings (TMS-EEG) has shown great potential in the study of the brain and in particular of Alzheimer's Disease (AD). In this study, we propose an automatic method of determining the duration of TMS-induced perturbation of the EEG signal as a potential metric reflecting the brain's functional alterations. A preliminary study is conducted in patients with Alzheimer's disease (AD). Three metrics for characterizing the strength and duration of TMS-evoked EEG (TEP) activity are proposed and their potential in identifying AD patients from healthy controls was investigated. A dataset of TMS-EEG recordings from 17 AD and 17 healthy controls (HC) was used in our analysis. A Random Forest classification algorithm was trained on the extracted TEP metrics and its performance is evaluated in a leave-one-subject-out cross-validation. The created model showed promising results in identifying AD patients from HC with an accuracy, sensitivity and specificity of 69.32%, 72.23% and 66.41%, respectively. Clinical relevance- Three preliminary metrics were proposed to quantify the strength and duration of the response to TMS on EEG data. The proposed metrics were successfully used to identify Alzheimer's disease patients from healthy controls. These results proved the potential of this approach which will provide additional diagnostic value.

Identification and verification of a 'true' TMS evoked potential in TMS-EEG

The concurrent combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) can unveil functional neural mechanisms with applications in basic and clinical research. In particular, TMS-evoked potentials (TEPs) potentially allow studying excitability and connectivity of the cortex in a causal manner that is not easily or non-invasively attainable with other neuroimaging techniques. The TEP waveform is obtained by isolating the EEG responses phase-locked to the time of TMS application. The intended component in a TEP waveform is the cortical activation by the TMS-induced electric current, free of instrumental and physiological artifact sources. This artifact-free cortical activation can be referred to as 'true' TEP. However, due to many unwanted auxiliary effects of TMS, the interpretation of 'true' TEPs has not been free of controversy. This paper reviews the most recent understandings of 'true' TEPs and their application. In the first part of the paper, TEP components are defined according to recommended methodologies. In the second part, the verification of 'true' TEP is discussed along with its sensitivity to brain-state, age, and disease. The various proposed origins of TEP components are then presented in the context of existing literature. Throughout the paper, lessons learned from the past TMS-EEG studies are highlighted to guide the identification and interpretation of 'true' TEPs in future studies.

Identifying novel biomarkers with TMS-EEG - Methodological possibilities and challenges

Biomarkers are essential for understanding the underlying pathologies in brain disorders and for developing effective treatments. Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an emerging neurophysiological tool that can be used for biomarker development. This method can identify biomarkers associated with the function and dynamics of the inhibitory and excitatory neurotransmitter systems and effective connectivity between brain areas. In this review, we outline the current state of the TMS-EEG biomarker field by summarizing the existing protocols and the possibilities and challenges associated with this methodology.

Designing and comparing cleaning pipelines for TMS-EEG data: a theoretical overview and practical example

Combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) is growing in popularity as a method for probing the reactivity and connectivity of neural circuits in basic and clinical research. However, using EEG to measure the neural responses to TMS is challenging due to the unique artifacts introduced by combining the two techniques. In this paper, we overview the artifacts present in TMS-EEG data and the offline cleaning methods used to suppress these unwanted signals. We then describe how open science practices, including the development of open-source toolboxes designed for TMS-EEG analysis (e.g., TESA - the TMS-EEG signal analyser), have improved the availability and reproducibility of TMS-EEG cleaning methods. We provide theoretical and practical considerations for designing TMS-EEG cleaning pipelines and then give an example of how to compare different pipelines using TESA. We show that changing even a single step in a pipeline designed to suppress decay artifacts results in TMS-evoked potentials (TEPs) with small differences in amplitude and spatial topography. The variability in TEPs resulting from the choice of cleaning pipeline has important implications for comparing TMS-EEG findings between research groups which use different online and offline approaches. Finally, we discuss the challenges of validating cleaning pipelines and recommend that researchers compare outcomes from TMS-EEG experiments using multiple pipelines to ensure findings are not related to the choice of cleaning methods. We conclude that the continued improvement, availability, and validation of cleaning pipelines is essential to ensure TMS-EEG reaches its full potential as a method for studying human neurophysiology.

TMS-EEG responses across the lifespan: Measurement, methods for characterisation and identified responses

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows probing of the neurophysiology of any neocortical brain area in vivo with millisecond accuracy. TMS-EEG is particularly unique compared with other available neurophysiological methods, as it can measure the state and dynamics of excitatory and inhibitory systems separately. Because of these capabilities, TMS-EEG responses are sensitive to the brain state, and the responses are influenced by brain maturation and ageing, making TMS-EEG a suitable method to study age-specific pathophysiology. In this review, we outline the TMS-EEG measurement procedure, the existing methods used for characterising TMS-EEG responses and the challenges associated with identifying the responses. We also summarise the findings thus far on how TMS-EEG responses change across the lifespan and the TMS-EEG features that separate typical and atypical brain maturation and ageing. Finally, we give an overview of the gaps in current knowledge to provide directions for future studies.

Topography and lateralization of long-latency trigeminal somatosensory evoked potentials

OBJECTIVE

Long-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.

METHODS

In 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.

RESULTS

Trigeminal 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.

CONCLUSIONS

SSEPs 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.

SIGNIFICANCE

The topography and lateralization of long-latency trigeminal SSEPs should be considered in future TMS-EEG designs.

Dorsolateral prefrontal cortex excitability abnormalities in Alzheimer's Dementia: Findings from transcranial magnetic stimulation and electroencephalography study

There is some evidence of cortical hyper-excitability in Alzheimer's Dementia (AD) but its relationship with cognition is not clear. In this study, we assessed dorsolateral prefrontal cortex (DLPFC) excitability and its relationship with cognition in AD. Twenty-four participants with AD (mean [SD] age = 74.1 [7.2] years) and eleven elderly healthy controls (HC) (mean [SD] age = 68.8 [7.3] years) were recruited. Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) was used to assess cortical excitability. Cortical evoked activity (CEA) between 25 and 80 ms post-TMS stimulus was calculated as the primary measure of cortical excitability. TMS-evoked potential peak (TEP) amplitudes (P30, N45 and P60) were also calculated. Cognition was assessed using Montreal Cognitive Assessment (MoCA), Executive Interview (EXIT) and Cambridge Neuropsychological Test Automated Battery Stockings of Cambridge (SOC). There was no difference in TMS stimulus intensity between the groups. DLPFC-CEA was higher in the AD (mean [SD] = 134.64 [90.22] μV) than the HC group (mean [SD] = 82.65 [40.28] μV; t₃₃ = 2.357, p = 0.025). There were no differences in TEP peak amplitudes between the groups. Further, DLPFC-CEA was inversely associated with MoCA and SOC, and positively associated with EXIT scores in AD. These results suggest increased DLPFC excitability in AD, and its inverse associations with global cognition and executive function. Future studies should examine these findings in larger samples and longitudinally, and could also assess these markers of cortical excitability in relation to other established markers of AD and in response to interventions.

The Role of the Dorsal-Lateral Prefrontal Cortex in Reward Sensitivity During Approach-Avoidance Conflict

Approach-Avoidance conflict (AAC) arises from decisions with embedded positive and negative outcomes, such that approaching leads to reward and punishment and avoiding to neither. Despite its importance, the field lacks a mechanistic understanding of which regions are driving avoidance behavior during conflict. In the current task, we utilized transcranial magnetic stimulation (TMS) and drift-diffusion modeling to investigate the role of one of the most prominent regions relevant to AAC-the dorsolateral prefrontal cortex (dlPFC). The first experiment uses in-task disruption to examine the right dlPFC's (r-dlPFC) causal role in avoidance behavior. The second uses single TMS pulses to probe the excitability of the r-dlPFC, and downstream cortical activations, during avoidance behavior. Disrupting r-dlPFC during conflict decision-making reduced reward sensitivity. Further, r-dlPFC was engaged with a network of regions within the lateral and medial prefrontal, cingulate, and temporal cortices that associate with behavior during conflict. Together, these studies use TMS to demonstrate a role for the dlPFC in reward sensitivity during conflict and elucidate the r-dlPFC's network of cortical regions associated with avoidance behavior. By identifying r-dlPFC's mechanistic role in AAC behavior, contextualized within its conflict-specific downstream neural connectivity, we advance dlPFC as a potential neural target for psychiatric therapeutics.

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

OBJECTIVE

Communication-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.

METHODS

TMS 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).

RESULTS

Pre-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).

CONCLUSIONS

Alpha-band PS predicts the response amplitude of the distant brain regions effectively connected to M1.

SIGNIFICANCE

Our study supports the role of EEG-PS in interarea communication, as theorized by communication-through-coherence.

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.

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.

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

Introduction

Transcranial 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.

Methods

TMS 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.

Results

TEP 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.

Conclusion

TEPs 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.

Cortical responses to noninvasive perturbations enable individual brain fingerprinting

BACKGROUND

In recent years, it has become increasingly apparent that characterizing individual brain structure, connectivity and dynamics is essential for understanding brain function in health and disease. However, the majority of neuroimaging and brain stimulation research has characterized human brain function by averaging measurements from groups of subjects and providing population-level inferences. External perturbations applied directly to well-defined brain regions can reveal distinctive information about the state, connectivity and dynamics of the human brain at the individual level.

OBJECTIVES

In a series of studies, we aimed to characterize individual brain responses to MRI-guided transcranial magnetic stimulation (TMS), and explore the reproducibility of the evoked effects, differences between brain regions, and their individual specificity.

METHODS

In the first study, we administered single pulses of TMS to both anatomically (left dorsolateral prefrontal cortex- 'L-DLPFC', left Intra-parietal lobule- 'L-IPL) and functionally (left motor cortex- 'L-M1', right default mode network- 'R-DMN, right dorsal attention network- 'R-DAN') defined cortical nodes in the frontal, motor, and parietal regions across two identical sessions spaced one month apart in 24 healthy volunteers. In the second study, we extended our analyses to two independent data sets (n = 10 in both data sets) having different sham-TMS protocols.

RESULTS

In the first study, we found that perturbation-induced cortical propagation patterns are heterogeneous across individuals but highly reproducible within individuals, specific to the stimulated region, and distinct from spontaneous activity. Most importantly, we demonstrate that by assessing the spatiotemporal characteristics of TMS-induced brain responses originating from different cortical regions, individual subjects can be identified with perfect accuracy. In the second study, we demonstrated that subject specificity of TEPs is generalizable across independent data sets and distinct from non-transcranial neural responses evoked by sham-TMS protocols.

CONCLUSIONS

Perturbation-induced brain responses reveal unique "brain fingerprints" that reflect causal connectivity dynamics of the stimulated brain regions, and may serve as reliable biomarkers of individual brain function.

Transcranial Evoked Potentials Can Be Reliably Recorded with Active Electrodes

Electroencephalographic (EEG) signals evoked by transcranial magnetic stimulation (TMS) are usually recorded with passive electrodes (PE). Active electrode (AE) systems have recently become widely available; compared to PE, they allow for easier electrode preparation and a higher-quality signal, due to the preamplification at the electrode stage, which reduces electrical line noise. The performance between the AE and PE can differ, especially with fast EEG voltage changes, which can easily occur with TMS-EEG; however, a systematic comparison in the TMS-EEG setting has not been made. Therefore, we recorded TMS-evoked EEG potentials (TEPs) in a group of healthy subjects in two sessions, one using PE and the other using AE. We stimulated the left primary motor cortex and right medial prefrontal cortex and used two different approaches to remove early TMS artefacts, Independent Component Analysis and Signal Space Projection—Source Informed Recovery. We assessed statistical differences in amplitude and topography of TEPs, and their similarity, by means of the concordance correlation coefficient (CCC). We also tested the capability of each system to approximate the final TEP waveform with a reduced number of trials. The results showed that TEPs recorded with AE and PE do not differ in amplitude and topography, and only few electrodes showed a lower-than-expected CCC between the two methods of amplification. We conclude that AE are a viable solution for TMS-EEG recording.

EEG Functional Connectivity is a Weak Predictor of Causal Brain Interactions

In recent years there has been an explosion of research evaluating resting-state brain functional connectivity (FC) using different modalities. However, the relationship between such measures of FC and the underlying causal brain interactions has not been well characterized. To further characterize this relationship, we assessed the relationship between electroencephalography (EEG) resting state FC and propagation of transcranial magnetic stimulation (TMS) evoked potentials (TEPs) at the sensor and source level in healthy participants. TMS was applied to six different cortical regions in ten healthy individuals (9 male; 1 female), and effects on brain activity were measured using simultaneous EEG. Pre-stimulus FC was assessed using five different FC measures (Pearson's correlation, mutual information, weighted phase lag index, coherence and phase locking value). Propagation of the TEPs was quantified as the root mean square (RMS) of the TEP voltage and current source density (CSD) at the sensor and source level, respectively. The relationship between pre-stimulus FC and the spatial distribution of TEP activity was determined using a generalized linear model (GLM) analysis. On the group level, all FC measures correlated significantly with TEP activity over the early (15-75 ms) and full range (15-400 ms) of the TEP at the sensor and source level. However, the predictive value of all FC measures is quite limited, accounting for less than 10% of the variance of TEP activity, and varies substantially across participants and stimulation sites. Taken together, these results suggest that EEG functional connectivity studies in sensor and source space should be interpreted with caution.