TMS-EEG: An emerging tool to study the neurophysiologic biomarkers of psychiatric disorders

Validation of the number of pulses required for TMS-EEG in the prefrontal cortex considering test feasibility

BACKGROUND

Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG), TMS-EEG, is a useful neuroscientific tool for the assessment of neurophysiology in the human cerebral cortex. Theoretically, TMS-EEG data is expected to have a better data quality as the number of stimulation pulses increases. However, since TMS-EEG testing is a modality that is examined on human subjects, the burden on the subject and tolerability of the test must also be carefully considered.

METHOD

In this study, we aimed to determine the number of stimulation pulses that satisfy the reliability and validity of data quality in single-pulse TMS (spTMS) for the dorsolateral prefrontal cortex (DLPFC). TMS-EEG data for (1) 40-pulse, (2) 80-pulse, (3) 160-pulse, and (4) 240-pulse conditions were extracted from spTMS experimental data for the left DLPFC of 20 healthy subjects, and the similarities between TMS-evoked potentials (TEP) and oscillations across the conditions were evaluated.

RESULTS

As a result, (2) 80-pulse and (3) 160-pulse conditions showed highly equivalent to the benchmark condition of (4) 240-pulse condition. However, (1) 40-pulse condition showed only weak to moderate equivalence to the (4) 240-pulse condition. Thus, in the DLPFC TMS-EEG experiment, 80 pulses of stimulations was found to be a reasonable enough number of pulses to extract reliable TEPs, compared to 160 or 240 pulses.

CONCLUSIONS

This is the first substantial study to examine the appropriate number of stimulus pulses that are reasonable and feasible for TMS-EEG testing of the DLPFC.

Individualized time windows enhance TMS-EEG signal characterization and improve assessment of cortical function in schizophrenia

Transcranial magnetic stimulation and electroencephalography (TMS-EEG) recordings are crucial to directly assess cortical excitability and inhibition in a non-invasive and task-free manner. TMS-EEG signals are characterized by TMS-evoked potentials (TEPs), which are employed to evaluate cortical function. Nonetheless, different time windows (TW) have been used to compute them over the years. Moreover, these TWs tend to be the same for all participants omitting the intersubject variability. Therefore, the objective of this study is to assess the effect of using different TWs to compute the TEPs, moving from a common fixed TW to more adaptive individualized TWs. Twenty-nine healthy (HC) controls and twenty schizophrenia patients (SCZ) underwent single-pulse (SP) TMS-EEG protocol. Firstly, only the HC were considered to evaluate the TEPs for three different TWs in terms of amplitude and topographical distribution. Secondly, the SCZ patients were included to determine which TW is better to characterize the brain alterations of SCZ. The results indicate that a more individualized TW provides a better characterization of the SP TMS-EEG signals, although all of them show the same tendency. Regarding the comparison between groups, the individualized TW is the one that provides a better differentiation between populations. They also provide further support to the possible imbalance of cortical excitability/inhibition in the SCZ population due to its reduced activity in the N45 TEP and greater amplitude values in the N100. Results also suggest that the SCZ brain has a baseline hyperactive state since the TEPs of the SCZ appear earlier than those of the HC.

Investigational applications of transcranial magnetic stimulation (TMS) in Mood Disorders: Studies from a tertiary care center in India

The investigational potential of TMS in psychiatry is largely underutilized. In the current article, we present the results of five studies with similar TMS protocols that looked at the investigative applications of TMS via measuring cortical reactivity as potential biomarkers in mood disorders. The first two studies, evaluate potential of TMS parameters and Motor neuron system (MNS) as state or trait markers of BD. Third and fourth studies evaluate these as endophenotypic markers of BD. The fifth study which is an RCT evaluating add-on yoga in UD, evaluates if markers of CI can index the therapeutic response of yoga. In study one MT1 was significantly greater in the SM (symptomatic-mania) group compared to HC (healthy-control) (P=0.032). The cortical inhibition measures SICI was reduced in SM(P=0.021) and BD (remitted Bipolar) (P=0.023) groups compared to HC. LICI was increased in the SM(0.021) and BD(P=0.06) groups compared to HC. In study two, a significant group x time interaction effect was observed indicating higher putative MNS-activity mediation in patients compared to HC on SlCl(P=0.024), LlCl(P=0.033). There were no significant group differences noted in the endophenotype studies. The fifth study showed a significant time X group interaction for CSP, favoring improvement in YG (yoga-group) (p<0.01).No significant change was observed for LICI(p=0.2), SICI(p=0.5). Limitations of these studies notwithstanding, we conclude that cortical reactivity measured using TMS is a potential biomarker across the course of mood disorders, starting from state and trait markers to understanding the therapeutic mechanism of a particular treatment modality in these disorders.

Instantaneous effects of prefrontal transcranial magnetic stimulation on brain oxygenation: A systematic review

This systematic review investigates how prefrontal transcranial magnetic stimulation (TMS) immediately influences neuronal excitability based on oxygenation changes measured by functional magnetic resonance imaging (fMRI) or functional near-infrared spectroscopy (fNIRS). A thorough understanding of TMS-induced excitability changes may enable clinicians to adjust TMS parameters and optimize treatment plans proactively. Five databases were searched for human studies evaluating brain excitability using concurrent TMS/fMRI or TMS/fNIRS. Thirty-seven studies (13 concurrent TMS/fNIRS studies, 24 concurrent TMS/fMRI studies) were included in a qualitative synthesis. Despite methodological inconsistencies, a distinct pattern of activated nodes in the frontoparietal central executive network, the cingulo-opercular salience network, and the default-mode network emerged. The activated nodes included the prefrontal cortex (particularly dorsolateral prefrontal cortex), insula cortex, striatal regions (especially caudate, putamen), anterior cingulate cortex, and thalamus. High-frequency repetitive TMS most consistently induced expected facilitatory effects in these brain regions. However, varied stimulation parameters (e.g., intensity, coil orientation, target sites) and the inter- and intra-individual variability of brain state contribute to the observed heterogeneity of target excitability and co-activated regions. Given the considerable methodological and individual variability across the limited evidence, conclusions should be drawn with caution.

Differential effects of high-definition transcranial direct current stimulation (HD-tDCS) on attentional guidance by working memory in males with substance use disorder according to memory modality

Information stored in working memory can guide perception selection, and this process is modulated by cognitive control. Although previous studies have demonstrated that neurostimulation over the left dorsolateral prefrontal cortex (lDLPFC) contributes to restore cognitive control among individuals with substance use disorder (SUD), there remains an open question about the potential stimulation effects on memory-driven attention. To address this issue, the present study adopted a combined working memory/attention paradigm while employing high-definition transcranial direct current stimulation (HD-tDCS) to stimulate the lDLPFC. Observers were asked to maintain visual or audiovisual information in memory while executing a search task, while the validity of the memory contents for the subsequent search task could be either invalid or neutral. The results showed a faint memory-driven attentional suppression effect in sham stimulation only under the audiovisual condition. Moreover, anodal HD-tDCS facilitated attentional suppression effect in both the strength and temporal dynamics under the visual-only condition, whereas the effect was impaired or unchanged under the audiovisual condition. Surprisingly, cathodal HD-tDCS selectively improved temporal dynamics of the attentional suppression effect under the audiovisual condition. The present study revealed the differential enhancement of HD-tDCS on cognitive control over visual and audiovisual memory-driven attention among individuals with SUD.

Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex

We currently lack a reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC). We recently found that the strength of early and local dlPFC transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely across dlPFC subregions. Despite these differences in response amplitude, reliability at each target is unknown. Here we quantified within-session reliability of dlPFC EL-TEPs after TMS to six left dlPFC subregions in 15 healthy subjects. We evaluated reliability (concordance correlation coefficient [CCC]) across targets, time windows, quantification methods, regions of interest, sensor- vs. source-space, and number of trials. On average, the medial target was most reliable (CCC = 0.78) and the most anterior target was least reliable (CCC = 0.24). However, all targets except the most anterior were reliable (CCC > 0.7) using at least one combination of the analytical parameters tested. Longer (20 to 60 ms) and later (30 to 60 ms) windows increased reliability compared to earlier and shorter windows. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials at a medial dlPFC target. Overall, medial dlPFC targeting, wider windows, and peak-to-peak quantification improved reliability. With careful selection of target and analytic parameters, highly reliable EL-TEPs can be extracted from the dlPFC after only a small number of trials.

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.

Poor sleep quality in schizophrenia patients: A systematic review and meta-analyses of epidemiological and case-control studies

OBJECTIVE

Poor sleep quality is common in patients with schizophrenia but estimated prevalence rates in this population have been mixed. This systematic review and meta-analysis examined the prevalence of poor sleep quality in schizophrenia samples and moderators of prevalence from epidemiological studies as well as the risk of poor sleep quality in schizophrenia patients based on case-control studies.

METHODS

Both international (PubMed, Web of Science, PsycINFO, EMBASE) and Chinese databases [Chinese Nation knowledge Infrastructure (CNKI) and WANFANG] were systematically searched. Studies that estimated the prevalence of poor sleep quality in schizophrenia were analyzed using a random effects model. Funnel plots and Egger's tests were used to assess publication bias. Statistical analyses were performed using R software.

RESULTS

In total, 23 epidemiological studies and nine case-control studies were included. Based on the epidemiological studies, the pooled overall prevalence of poor sleep quality was 63.4 % [95 % confidence interval (CI): 57.0 %-69.9 %]. Additionally, based on the nine case-control studies, schizophrenia patients had a significantly higher risk for poor sleep quality compared to healthy controls [odd ratio (OR) = 4.5; 95%CI: 2.4-8.3; P < 0.0001].

CONCLUSION

Poor sleep quality is common among schizophrenia patients. Considering negative outcomes caused by poor sleep quality, regular screening on poor sleep quality should be conducted and effective interventions should be provided to those in need.

Somatosensory input in the context of transcranial magnetic stimulation coupled with electroencephalography: An evidence-based overview

The transcranial evoked potential (TEP) is a powerful technique to investigate brain dynamics, but some methodological issues limit its interpretation. A possible contamination of the TEP by electroencephalographic (EEG) responses evoked by the somatosensory input generated by transcranial magnetic stimulation (TMS) has been postulated; nonetheless, a characterization of these responses is lacking. The aim of this work was to review current evidence about possible somatosensory evoked potentials (SEP) induced by sources of somatosensory input in the craniofacial region. Among these, only contraction of craniofacial muscle and stimulation of free cutaneous nerve endings may be able to induce EEG responses, but direct evidence is lacking due to experimental difficulties in isolating these inputs. Notably, EEG evoked activity in this context is represented by a N100/P200 complex, reflecting a saliency-related multimodal response, rather than specific activation of the primary somatosensory cortex. Strategies to minimize or remove these responses by EEG processing still yield uncertain results; therefore, data inspection is of paramount importance to judge a possible contamination of the TEP by multimodal potentials caused by somatosensory input.

Managing substance use in patients receiving therapeutic repetitive transcranial magnetic stimulation: A scoping review

Repetitive Transcranial Magnetic Stimulation (rTMS) is an invaluable treatment option for neuropsychiatric disorders. Co-occurring recreational and nonmedical substance use can be common in those presenting for rTMS treatment, and it is unknown how it may affect the safety and efficacy of rTMS for the treatment of currently approved neuropsychiatric indications. This scoping review aimed to map the literature on humans receiving rTMS and had a history of any type of substance use. The search identified 274 articles providing information on inclusion/exclusion criteria, withdrawal criteria, safety protocols, type of rTMS and treatment parameters, adverse events and effect on primary outcomes that related to substance use. There are neurophysiological effects of substance use on cortical excitability, although the relevance to clinical rTMS practice is unknown. The current literature supports the safety and feasibility of delivering rTMS to those who have co-occurring neuropsychiatric disorder and substance use. However, specific details on how varying degrees of substance use alters the safety, efficacy, and mechanisms of rTMS remains poorly described.

Graph Analysis of TMS-EEG Connectivity Reveals Hemispheric Differences following Occipital Stimulation

(1) Background: Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) provides a unique opportunity to investigate brain connectivity. However, possible hemispheric asymmetries in signal propagation dynamics following occipital TMS have not been investigated. (2) Methods: Eighteen healthy participants underwent occipital single-pulse TMS at two different EEG sites, corresponding to early visual areas. We used a state-of-the-art Bayesian estimation approach to accurately estimate TMS-evoked potentials (TEPs) from EEG data, which has not been previously used in this context. To capture the rapid dynamics of information flow patterns, we implemented a self-tuning optimized Kalman (STOK) filter in conjunction with the information partial directed coherence (iPDC) measure, enabling us to derive time-varying connectivity matrices. Subsequently, graph analysis was conducted to assess key network properties, providing insight into the overall network organization of the brain network. (3) Results: Our findings revealed distinct lateralized effects on effective brain connectivity and graph networks after TMS stimulation, with left stimulation facilitating enhanced communication between contralateral frontal regions and right stimulation promoting increased intra-hemispheric ipsilateral connectivity, as evidenced by statistical test (p < 0.001). (4) Conclusions: The identified hemispheric differences in terms of connectivity provide novel insights into brain networks involved in visual information processing, revealing the hemispheric specificity of neural responses to occipital stimulation.

Effects of transcranial magnetic stimulation (TMS) current direction and pulse waveform on cortico-cortical connectivity: A registered report TMS-EEG study

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) are a promising proxy for measuring effective connectivity, that is, the directed transmission of physiological signals along cortico-cortical tracts, and for developing connectivity-based biomarkers. A crucial point is how stimulation parameters may affect TEPs, as they may contribute to the general variability of findings across studies. Here, we manipulated two TMS parameters (i.e. current direction and pulse waveform) while measuring (a) an early TEP component reflecting contralateral inhibition of motor areas, namely, M1-P15, as an operative model of interhemispheric cortico-cortical connectivity, and (b) motor-evoked potentials (MEP) for the corticospinal pathway. Our results showed that these two TMS parameters are crucial to evoke the M1-P15, influencing its amplitude, latency, and replicability. Specifically, (a) M1-P15 amplitude was strongly affected by current direction in monophasic stimulation; (b) M1-P15 latency was significantly modulated by current direction for monophasic and biphasic pulses. The replicability of M1-P15 was substantial for the same stimulation condition. At the same time, it was poor when stimulation parameters were changed, suggesting that these factors must be controlled to obtain stable single-subject measures. Finally, MEP latency was modulated by current direction, whereas non-statistically significant changes were evident for amplitude. Overall, our study highlights the importance of TMS parameters for early TEP responses recording and suggests controlling their impact in developing connectivity biomarkers from TEPs. Moreover, these results point out that the excitability of the corticospinal tract, which is commonly used as a reference to set TMS intensity, may not correspond to the excitability of cortico-cortical pathways.

Repetitive Transcranial Magnetic Stimulation (rTMS) in Mild Cognitive Impairment: Effects on Cognitive Functions-A Systematic Review

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique also used as a non-pharmacological intervention against cognitive impairment. The purpose of the present review was to summarize what is currently known about the effectiveness of rTMS intervention on different cognitive domains in patients with mild cognitive impairment (MCI) and to address potential neuromodulation approaches in combination with electroencephalography (EEG) and neuroimaging, especially functional magnetic resonance imaging (fMRI). In this systematic review, we consulted three main databases (PubMed, Science Direct, and Scopus), and Google Scholar was selected for the gray literature search. The PRISMA flowchart drove the studies' inclusion. The selection process ensured that only high-quality studies were included; after removing duplicate papers, explicit ratings were given based on the quality classification as high (A), moderate (B), or low (C), considering factors such as risks of bias, inaccuracies, inconsistencies, lack of direction, and publication bias. Seven full-text articles fulfilled the stated inclusion, reporting five double-blind, randomized, sham-controlled studies, a case study, and a randomized crossover trial. The results of the reviewed studies suggested that rTMS in MCI patients is safe and effective for enhancing cognitive functions, thus making it a potential therapeutic approach for MCI patients. Changes in functional connectivity within the default mode network (DMN) after targeted rTMS could represent a valuable indicator of treatment response. Finally, high-frequency rTMS over the dorsolateral prefrontal cortex (DLPFC) has been shown to significantly enhance cognitive functions, such as executive performance, together with the increase of functional connectivity within frontoparietal networks. The main limitations were the number of included studies and the exclusion of studies using intermittent theta-burst stimulation, used in studies on Alzheimer's disease. Therefore, neuroimaging techniques in combination with rTMS have been shown to be useful for future network-based, fMRI-guided therapeutic approaches.

Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex

Background

We currently lack a robust and reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC), a region heavily implicated in psychiatric disorders. We recently found that the strength of early and local dlPFC single pulse transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely depending on the anatomical subregion probed, with more medial regions eliciting stronger responses than anterolateral sites. Despite these differences in amplitude of response, the reliability at each target is not known.

Objective

To evaluate the reliability of EL-TEPs across the dlPFC.

Methods

In 15 healthy subjects, we quantified within-session reliability of dlPFC EL-TEPs after single pulse TMS to six dlPFC subregions. We evaluated the concordance correlation coefficient (CCC) across targets and analytical parameters including time window, quantification method, region of interest, sensor-vs. source-space, and number of trials.

Results

At least one target in the anterior and posterior dlPFC produced reliable EL-TEPs (CCC>0.7). The medial target was most reliable (CCC = 0.78) and the most anterior target was least reliable (CCC = 0.24). ROI size and type (sensor vs. source space) did not affect reliability. Longer (20-60 ms, CCC = 0.62) and later (30-60 ms, CCC = 0.61) time windows resulted in higher reliability compared to earlier and shorter (20-40 ms, CCC 0.43; 20-50 ms, CCC = 0.55) time windows. Peak-to-peak quantification resulted in higher reliability than the mean of the absolute amplitude. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials for a medial dlPFC target.

Conclusions

Medial TMS location, wider time window (20-60ms), and peak-to-peak quantification improved reliability. Highly reliable EL-TEPs can be extracted from dlPFC after only a small number of trials.

Highlights

Medial dlPFC target improved EL-TEP reliability compared to anterior targets.After optimizing analytical parameters, at least one anterior and one posterior target was reliable (CCC>0.7).Longer (20-60 ms) and later (30-60 ms) time windows were more reliable than earlier and shorter (20-40 ms or 20-50 ms) latencies.Peak-to-peak quantification resulted in higher reliability compared to the mean of the absolute amplitude.As low as 25 trials can yield reliable EL-TEPs from the dlPFC.

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.

Cortical inhibition on TMS-EEG: interstimulus interval effect on short-interval paired-pulse

In mental disorders, paired-pulse (PP) transcranial magnetic stimulation and electroencephalography (TMS-EEG) recordings usage is increasing to directly evaluate the cortical inhibition of motor and nonmotor regions. One of the most common measures to assess the inhibition is the short-interval cortical inhibition (SICI), which depends on the interstimulus interval (ISI). This measure has been widely used in the motor cortex. However, the number of studies that evaluate other nonmotor regions, such as the dorsolateral prefrontal cortex (DLPFC), are increasing and there is still little knowledge on how the ISI affects those areas.In this pilot study, six subjects underwent a SICI protocol over the DLPFC using ISI values of 2 and 4ms with the aim of comparing them. TMS-EEG signals for both ISIs were characterized regarding the amplitude and latency of the TMS-evoked potentials (TEP) P60 and N100. Whereas the variation of cortical inhibition between ISIs is almost significant for N100, with higher inhibition for an ISI of 2ms, for TEP P60 the variation was not appreciable. Findings are in accordance with the ones in the state-of-the-art obtained in the motor cortex and suggest that a greater inhibition is likely to be produced with an ISI of 2ms.Clinical relevance- This pilot study indicates that cortical inhibition might be better assessed when DLPFC is stimulated with an ISI of 2ms in the SICI protocol.

TMS-evoked potential in the dorsolateral prefrontal cortex to assess the severity of depression disease: a TMS-EEG study

Objective: The combined use of transcranial magnetic stimulation and electroencephalography (TMS-EEG), as a powerful technique that can non-invasively probe the state of the brain, can be used as a method to study neurophysiological markers in the field of psychiatric disorders and discover potential diagnostic predictors. This study used TMS-evoked potentials (TEPs) to study the cortical activity of patients with major depressive disorder depression (MDD) and the correlation with clinical symptoms to provide an electrophysiological basis for the clinical diagnosis. Methods: A total of 41 patients and 42 healthy controls were recruited to study. Using TMS-EEG techniques to measure the left dorsolateral prefrontal cortex (DLPFC) 's TEP index and evaluate the clinical symptoms of MDD patients using the Hamilton Depression Scale-24 (HAMD-24). Results: MDD subjects performing TMS-EEG on the DLPFC showed lower cortical excitability P60 index levels than healthy controls. Further analysis revealed that the degree of P60 excitability within the DLPFC of MDD patients was significantly negatively correlated with the severity of depression. Conclusion: The low levels of P60 exhibited in DLPFC reflect low excitability in MDD; the P60 component can be used as a biomarker for MDD in clinical assessment tools.

Orbitofrontal cortex-hippocampus potentiation mediates relief for depression: A randomized double-blind trial and TMS-EEG study

It has been 15 years since repetitive transcranial magnetic stimulation (rTMS) targeting the dorsolateral prefrontal cortex (DLPFC) was approved by the FDA for clinical depression treatment. Yet, the underlying mechanisms for rTMS-induced depression relief are not fully elucidated. This study analyzes TMS-electroencephalogram (EEG) data from 64 healthy control (HC) subjects and 53 patients with major depressive disorder (MDD) before and after rTMS treatment. Prior to treatment, patients with MDD have lower activity in the DLPFC, the hippocampus (HPC), the orbitofrontal cortex (OFC), and DLPFC-OFC connectivity compared with HCs. Following active rTMS treatment, patients with MDD show a significant increase in the DLPFC, HPC, and OFC. Notably, the increase in HPC activity is specifically associated with amelioration of depressive symptoms but not anxiety or sleep quality. The orbitofrontal-hippocampal pathway plays a crucial role in mediating depression relief following rTMS treatment. These findings suggest potential alternative targets for brain stimulation therapy against depression (chictr.org.cn: ChiCTR2100052007).

A review of critical brain oscillations in depression and the efficacy of transcranial magnetic stimulation treatment

Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta burst stimulation (iTBS) have been proven effective non-invasive treatments for patients with drug-resistant major depressive disorder (MDD). However, some depressed patients do not respond to these treatments. Therefore, the investigation of reliable and valid brain oscillations as potential indices for facilitating the precision of diagnosis and treatment protocols has become a critical issue. The current review focuses on brain oscillations that, mostly based on EEG power analysis and connectivity, distinguish between MDD and controls, responders and non-responders, and potential depression severity indices, prognostic indicators, and potential biomarkers for rTMS or iTBS treatment. The possible roles of each biomarker and the potential reasons for heterogeneous results are discussed, and the directions of future studies are proposed.

TMS-evoked responses are driven by recurrent large-scale network dynamics

A compelling way to disentangle the complexity of the brain is to measure the effects of spatially and temporally synchronized systematic perturbations. In humans, this can be non-invasively achieved by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Spatiotemporally complex and long-lasting TMS-EEG evoked potential (TEP) waveforms are believed to result from recurrent, re-entrant activity that propagates broadly across multiple cortical and subcortical regions, dispersing from and later re-converging on, the primary stimulation site. However, if we loosely understand the TEP of a TMS-stimulated region as the impulse response function of a noisy underdamped harmonic oscillator, then multiple later activity components (waveform peaks) should be expected even for an isolated network node in the complete absence of recurrent inputs. Thus emerges a critically important question for basic and clinical research on human brain dynamics: what parts of the TEP are due to purely local dynamics, what parts are due to reverberant, re-entrant network activity, and how can we distinguish between the two? To disentangle this, we used source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from 100 ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics. The novel discoveries and new software technologies introduced here should be of broad utility in basic and clinical neuroscience research.

The potential of electroencephalography coherence to predict the outcome of repetitive transcranial magnetic stimulation in insomnia disorder

BACKGROUND

It is unknown whether repetitive Transcranial Magnetic Stimulation (rTMS) could improve sleep quality by modulating electroencephalography (EEG) connectivity of insomnia disorder (ID) patients. Great heterogeneity had been found in the clinical outcomes of rTMS for ID. The study aimed to investigate the potential mechanisms of rTMS therapy for ID and develop models to predict clinical outcomes.

METHODS

In Study 1, 50 ID patients were randomly divided into active and sham groups, and subjected to 20 sessions of treatment with 1 Hz rTMS over the left dorsolateral prefrontal cortex. EEG during awake, Polysomnography, and clinical assessment were collected and analyzed before and after rTMS. In Study 2, 120 ID patients were subjected to active rTMS stimulation and were then separated into optimal and sub-optimal groups due to the median of Pittsburgh Sleep Quality Index reduction rate. Machine learning models were developed based on baseline EEG coherence to predict rTMS treatment effects.

RESULTS

In Study 1, decreased EEG coherence in theta and alpha bands were observed after rTMS treatment, and changes in theta band (F7-O1) coherence were correlated with changes in sleep efficiency. In Study 2, baseline EEG coherence in theta, alpha, and beta bands showed the potential to predict the treatment effects of rTMS for ID.

CONCLUSION

rTMS improved sleep quality of ID patients by modulating the abnormal EEG coherence. Baseline EEG coherence between certain channels in theta, alpha, and beta bands could act as potential biomarkers to predict the therapeutic effects.

Therapeutics for Substance-Using Women: The Need to Elucidate Sex-Specific Targets for Better-Tailored Treatments

In the last decade, alcohol consumption in the US has risen by 84% in women compared with 35% in men. Furthermore, research has shown that sex- and gender-related differences may disadvantage women in terms of developing a range of psychological, cognitive, and medical problems considerably earlier in their drinking history than men, and despite consuming a similar quantity of substances. While this "telescoping" process has been acknowledged in the literature, a concomitant understanding of the underlying biobehavioral mechanisms, and an increase in the development of specific treatments tailored to women, has not occurred. In the current chapter we focus on understanding why the need for personalized, sex-specific medications is imperative, and highlight some of the potential sex-specific gonadal and stress-related adaptations underpinning the accelerated progress from controlled to compulsive drug and alcohol seeking in women. We additionally discuss the efficacy of these mechanisms as novel targets for medications development, using exogenous progesterone and guanfacine as examples. Finally, we assess some of the challenges faced and progress made in terms of developing innovative medications in women. We suggest that agents such as exogenous progesterone and adrenergic medications, such as guanfacine, may provide some efficacy in terms of attenuating stress-induced craving for several substances, as well as improving the ability to emotionally regulate in the face of stress, preferentially in women. However, to fully leverage the potential of these therapeutics in substance-using women, greater focus needs to the placed on reducing barriers to treatment and research by encouraging women into clinical trials.

Characterizing cortical responses to short-term multidisciplinary intensive rehabilitation treatment in patients with Parkinson’s disease: A transcranial magnetic stimulation and electroencephalography study

Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is a powerful non-invasive tool for qualifying the neurophysiological effects of interventions by recording TMS-induced cortical activation with high temporal resolution and generates reproducible and reliable waves of activity without participant cooperation. Cortical dysfunction contributes to the pathogenesis of the clinical symptoms of Parkinson’s disease (PD). Here, we examined changes in cortical activity in patients with PD following multidisciplinary intensive rehabilitation treatment (MIRT). Forty-eight patients with PD received 2 weeks of MIRT. The cortical response was examined following single-pulse TMS over the primary motor cortex by 64-channel EEG, and clinical symptoms were assessed before and after MIRT. TMS-evoked potentials were quantified by the global mean field power, as well as oscillatory power in theta, alpha, beta, and gamma bands, and their clinical correlations were calculated. After MIRT, motor and non-motor symptoms improved in 22 responders, and only non-motor function was enhanced in 26 non-responders. Primary motor cortex stimulation reduced global mean field power amplitudes in responders but not significantly in non-responders. Oscillations exhibited attenuated power in the theta, beta, and gamma bands in responders but only reduced gamma power in non-responders. Associations were observed between beta oscillations and motor function and between gamma oscillations and non-motor symptoms. Our results suggest that motor function enhancement by MIRT may be due to beta oscillatory power modulation and that alterations in cortical plasticity in the primary motor cortex contribute to PD recovery.

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.

The role of neuronavigation in TMS-EEG studies: current applications and future perspectives

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring non-invasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMS-EEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during acquisition, is key for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neuronavigation system can help in reproducing the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neuronavigation in TMS-EEG studies is also key to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.

Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review

Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

Background

Transcranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined.

Objective

To develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG).

Methods

We developed an automated closed-loop TMS–EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS–EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject.

Results

The validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses.

Conclusion

Optimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity.

•

Closed-loop set-up for guiding TMS with brain activity feedback.

•

Automatic stimulus orientation optimization based on TMS-evoked EEG responses.

•

Adjusting TMS parameters electronically allows fast and effortless procedures.

•

TMS-evoked EEG responses depend on the stimulus orientation.

Bridging the gap: TMS-EEG from Lab to Clinic

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has reached technological maturity and has been an object of significant scientific interest for over two decades. Ιn parallel, accumulating evidence highlights the potential of TMS-EEG as a useful tool in the field of clinical neurosciences. Nevertheless, its clinical utility has not yet been established, partly because technical and methodological limitations have created a gap between an evolving scientific tool and standard clinical practice. Here we review some of the identified gaps that still prevent TMS-EEG moving from science laboratories to clinical practice. The principal and partly overlapping gaps include: 1) complex and laborious application, 2) difficulty in obtaining high-quality signals, 3) suboptimal accuracy and reliability, and 4) insufficient understanding of the neurobiological substrate of the responses. All these four aspects need to be satisfactorily addressed for the method to become clinically applicable and enter the diagnostic and therapeutic arena. In the current review, we identify steps that might be taken to address these issues and discuss promising recent studies providing tools to aid bridging the gaps.

Increased both cortical activation and functional connectivity after transcranial direct current stimulation in patients with post-stroke: A functional near-infrared spectroscopy study

BACKGROUND

Previous studies have shown that cognitive impairment is common after stroke. Transcranial direct current stimulation (tDCS) is a promising tool for rehabilitating cognitive impairment. This study aimed to investigate the effects of tDCS on the rehabilitation of cognitive impairment in patients with stroke.

METHODS

Twenty-two mild-moderate post-stroke patients with cognitive impairments were treated with 14 tDCS sessions. A total of 14 healthy individuals were included in the control group. Cognitive function was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Cortical activation was assessed using functional near-infrared spectroscopy (fNIRS) during the verbal fluency task (VFT).

RESULTS

The cognitive function of patients with stroke, as assessed by the MMSE and MoCA scores, was lower than that of healthy individuals but improved after tDCS. The cortical activation of patients with stroke was lower than that of healthy individuals in the left superior temporal cortex (lSTC), right superior temporal cortex (rSTC), right dorsolateral prefrontal cortex (rDLPFC), right ventrolateral prefrontal cortex (rVLPFC), and left ventrolateral prefrontal cortex (lVLPFC) cortical regions. Cortical activation increased in the lSTC cortex after tDCS. The functional connectivity (FC) between the cerebral hemispheres of patients with stroke was lower than that of healthy individuals but increased after tDCS.

CONCLUSION

The cognitive and brain functions of patients with mild-to-moderate stroke were damaged but recovered to a degree after tDCS. Increased cortical activation and increased FC between the bilateral cerebral hemispheres measured by fNIRS are promising biomarkers to assess the effectiveness of tDCS in stroke.

Concurrent TMS-fMRI: Technical Challenges, Developments, and Overview of Previous Studies

Transcranial magnetic stimulation (TMS) is a promising treatment modality for psychiatric and neurological disorders. Repetitive TMS (rTMS) is widely used for the treatment of psychiatric and neurological diseases, such as depression, motor stroke, and neuropathic pain. However, the underlying mechanisms of rTMS-mediated neuronal modulation are not fully understood. In this respect, concurrent or simultaneous TMS-fMRI, in which TMS is applied during functional magnetic resonance imaging (fMRI), is a viable tool to gain insights, as it enables an investigation of the immediate effects of TMS. Concurrent application of TMS during neuroimaging usually causes severe artifacts due to magnetic field inhomogeneities induced by TMS. However, by carefully interleaving the TMS pulses with MR signal acquisition in the way that these are far enough apart, we can avoid any image distortions. While the very first feasibility studies date back to the 1990s, recent developments in coil hardware and acquisition techniques have boosted the number of TMS-fMRI applications. As such, a concurrent application requires expertise in both TMS and MRI mechanisms and sequencing, and the hurdle of initial technical set up and maintenance remains high. This review gives a comprehensive overview of concurrent TMS-fMRI techniques by collecting (1) basic information, (2) technical challenges and developments, (3) an overview of findings reported so far using concurrent TMS-fMRI, and (4) current limitations and our suggestions for improvement. By sharing this review, we hope to attract the interest of researchers from various backgrounds and create an educational knowledge base.

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.