Repetitive transcranial magnetic stimulation (rTMS) modulates time-varying electroencephalography (EEG) network in primary insomnia patients: a TMS-EEG study

HF-rTMS of the left DLPFC relieve headaches and enhance frontal-temporal connectivity in migraine

OBJECTIVE

Migraine is a neurological disorder linked to altered cortical excitability. High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) is a promising non-invasive method for modulating nociceptive circuits, yet its precise mechanisms remain unclear. This study applied HF-rTMS to the left dorsolateral prefrontal cortex (DLPFC) and assessed brain network changes using transcranial magnetic stimulation combined with electroencephalography (TMS-EEG).

METHODS

We analyzed dynamic brain connectivity in 15 migraine patients versus 15 healthy controls. A randomized, double-blind, sham-controlled trial evaluated a 14-day HF-rTMS (20 Hz) protocol in 28 migraine patients. Brain network reorganization and migraine severity, measured by the Visual Analog Scale (VAS) and monthly migraine days (MMD), were assessed both immediately after treatment and at a one-month follow-up.

RESULTS

Migraine patients exhibited reduced left DLPFC connectivity compared to healthy controls. HF-rTMS significantly increased frontal-temporal network connectivity, correlating with a marked reduction in VAS and MMD scores (p < 0.001).

CONCLUSION

These findings provide novel evidence that HF-rTMS targeting the left DLPFC effectively alleviates migraine symptoms by enhancing frontal-temporal cortical plasticity.

SIGNIFICANCE

This study highlights the potential of neuromodulation techniques in the treatment of migraine.

Efficiency and safety of continuous theta burst stimulation for primary insomnia: A randomized clinical trial

OBJECTIVES

Primary insomnia is a substantial public health burden, but current treatments for this disorder have limited effectiveness and adherence. Herein, we aimed to investigate the efficacy and safety of continuous theta burst stimulation (cTBS) for the treatment of primary insomnia.

METHODS

This two-armed, randomized, sham-controlled trial was conducted at Peking University Sixth Hospital and local community clinics. A total of 46 patients with primary insomnia were recruited and randomly allocated to either the cTBS group or sham group. Forty-one patients completed 10 sessions of cTBS or sham intervention and follow-up assessments.

RESULTS

After the intervention, the severity of insomnia was significantly lower in the cTBS group than in the sham group, with a large effect size (Cohen's d = -1.938). Additionally, 52.4 % of patients in the cTBS group achieved a response (Insomnia Severity Index score reduction ≥8), whereas only 4 % of patients in the sham group achieved a response. The duration of objective total sleep time and slow-wave sleep were higher in the cTBS group than in the sham group. The degree of anxiety was lower in the cTBS group than in the sham group. There were no significant differences in depression, sleepiness, or cognitive function between the cTBS and sham groups. During follow-up, the sleep quality of the cTBS group significantly improved and remained stable at the 6-month follow-up.

CONCLUSION

In this randomized clinical trial, cTBS improved insomnia symptoms and was generally well tolerated, thus supporting the further development of cTBS for the treatment of primary insomnia.

Effect of combined treatment with transcranial direct current stimulation and repetitive transcranial magnetic stimulation compared to monotherapy for the treatment of chronic insomnia: a randomised, double-blind, parallel-group, controlled trial

BACKGROUND

Chronic insomnia increases the risk of various health problems and mental illness. Existing research suggests promise for both transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) in treating chronic insomnia individually. However, the combined effects of tDCS and rTMS on this condition remain unclear. This study aimed to verify the efficacy and safety of tDCS combined with rTMS for the treatment of adult patients with chronic insomnia.

METHODS

This was a randomised double-blind parallel-group controlled study. Overall, 157 participants with chronic insomnia were randomly assigned to one of three neurotherapy regimens: tDCS + rTMS, sham tDCS + rTMS, or tDCS + sham rTMS. All groups received 20 treatment sessions over 4 consecutive weeks. The primary outcome was the change in patients' sleep as assessed by the Pittsburgh Sleep Quality Index (PSQI) at 2 weeks, 4 weeks, and 3 months of follow-up. The secondary outcome was the assessment of different dimensions of depression and anxiety in patients through the Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA), as well as the occurrence of adverse events.

RESULTS

Throughout the intervention and after the 3-month follow-up, the tDCS + rTMS group had significantly reduced total PSQI scores compared with the other two groups [tDCS + rTMS, 9.21 vs. sham tDCS + rTMS, 10.03; difference - 1.10; 95% confidence interval (CI), - 1.82 to - 0.38; p = 0.003; tDCS + rTMS, 9.21 vs. tDCS + sham rTMS, 10.76; difference - 2.14; 95% CI, - 2.90 to - 1.38; p < 0.001; sham tDCS + rTMS, 10.03 vs. tDCS + sham rTMS, 10.76; difference - 1.04; 95% CI, - 1.82 to - 0.26; p = 0.010), indicating improved overall sleep quality. Total HAMD and insomnia factor scores were significantly lower in the tDCS + rTMS group than in the other two groups after treatment (p < 0.05). Notably, no adverse events or serious adverse reactions were observed during the study period.

CONCLUSIONS

Combining tDCS with rTMS effectively relieved insomnia symptoms, achieving a significant therapeutic effect after 2-week of intervention, and demonstrating the persistence of treatment effects in later follow-up, emphasising the advantages of combination therapy in improving treatment stability and long-term benefits, reflecting the rapid and effective augmentation of combination therapy. This combined therapy may serve as a safe and effective treatment for adults with chronic insomnia.

TRIAL REGISTRATION

This study was registered as a clinical trial with the China Clinical Trial Registration Center (ChiCTR2100052681).

Can Neuromodulation Improve Sleep and Psychiatric Symptoms?

PURPOSE OF REVIEW

In this review, we evaluate recent studies that employ neuromodulation, in the form of non-invasive brain stimulation, to improve sleep in both healthy participants, and patients with psychiatric disorders. We review studies using transcranial electrical stimulation, transcranial magnetic stimulation, and closed-loop auditory stimulation, and consider both subjective and objective measures of sleep improvement.

RECENT FINDINGS

Neuromodulation can alter neuronal activity underlying sleep. However, few studies utilizing neuromodulation report improvements in objective measures of sleep. Enhancements in subjective measures of sleep quality are replicable, however, many studies conducted in this field suffer from methodological limitations, and the placebo effect is robust. Currently, evidence that neuromodulation can effectively enhance sleep is lacking. For the field to advance, methodological issues must be resolved, and the full range of objective measures of sleep architecture, alongside subjective measures of sleep quality, must be reported. Additionally, validation of effective modulation of neuronal activity should be done with neuroimaging.

Efficacy of non-invasive brain stimulation for post-stroke sleep disorders: a systematic review and meta-analysis

Objective

This study aimed to systematically assess the clinical efficacy of non-invasive brain stimulation (NIBS) for treating post-stroke sleep disorders (PSSD).

Methods

We conducted thorough literature search across multiple databases, including PubMed, Web of Science, EmBase, Cochrane Library, Scopus, China Biology Medicine (CBM); China National Knowledge Infrastructure (CNKI); Technology Periodical Database (VIP), and Wanfang Database, focusing on RCTs examining NIBS for PSSD. Meta-analyses were performed using RevMan 5.4 and Stata 14.

Results

Eighteen articles were reviewed, including 16 on repetitive Transcranial Magnetic Stimulation (rTMS), one on Theta Burst Stimulation (TBS), and two on transcranial Direct Current Stimulation (tDCS). Meta-analysis results indicated that rTMS within NIBS significantly improved the Pittsburgh Sleep Quality Index (PSQI) score (MD = -1.85, 95% CI [-2.99, -0.71], p < 0.05), the 17-item Hamilton Depression Rating Scale (HAMD-17) score [MD = -2.85, 95% CI (-3.40, -2.30), p < 0.05], and serum brain-derived neurotrophic factor (BDNF) levels [MD = 4.19, 95% CI (2.70, 5.69), p < 0.05], while reducing the incidence of adverse reactions [RR = 0.36, 95% CI (0.23, 0.55), p < 0.05]. TBS significantly improved the PSQI score in patients with PSSD (p < 0.05). Conversely, tDCS significantly improved the HAMD-17 score in PSSD patients [MD = -1.52, 95% CI (-3.41, -0.64), p < 0.05]. Additionally, rTMS improved sleep parameters, including Stage 2 sleep (S2%) and combined Stage 3 and 4 sleep (S3 + S4%) (p < 0.05), while tDCS improved total sleep time (TST) and sleep efficiency (SE) (p < 0.05).Subgroup analysis results indicated: (1) Both LF-rTMS and HF-rTMS improved PSQI scores (p < 0.05). (2) Both rTMS combined with medication and rTMS alone improved PSQI scores (p < 0.05). Compared to the sham/blank group, the rTMS group showed improvements in SE, sleep latency (SL), S1%, S3 + S4%, and REM sleep (REM%). The rTMS combined with medication group showed improved SL compared to the medication-only group (p < 0.05).

Conclusion

NIBS effectively improves sleep quality, structure, depression levels, and BDNF levels in PSSD patients, while also being safe. Further investigations into the potential of NIBS in PSSD treatment may provide valuable insights for clinical applications.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, CRD42023485317.

Improvements in Sleep Quality in Patients With Major Depressive and Generalized Anxiety Disorders Treated With Individualized, Parcel-Guided Transcranial Magnetic Stimulation

INTRODUCTION

Poor quality sleep has often been cited as a cause of lowered quality of life in patients with affective disorders such as major depressive disorder (MDD) and generalized anxiety disorder (GAD). As sleep and affective disorders are affected by multi-network interactions, we hypothesize that the modulation of the central executive network (CEN), salience, and default mode networks (DMNs) through individualized repetitive transcranial magnetic stimulation (rTMS) may improve sleep and quality of life.

METHODS

A retrospective analysis from 2020 to 2023 was conducted in patients with affective disorders at Cingulum Health. Multiple targets were selected based on anomalies detected from individual, functional connectivity networks from a machine-learning connectivity software. rTMS was conducted with accelerated continuous or intermittent theta burst stimulation (TBS) based on the anomaly detected. Pittsburgh Sleep Quality Index (PSQI), EuroQol (EQ5D), Beck's Depression Inventory (BDI), and the General Anxiety Disorder-7 (GAD-7) questionnaires were administered prior to, after, and at follow-up of rTMS.

RESULTS

Twenty-seven patients were identified, and the most common diagnoses were MDD (41%) or MDD with GAD (41%). All patients had at least one rTMS target in the CEN. The most common target (19 patients) was L8Av in the dorsolateral prefrontal cortex (dlPFC). Patients experienced significant improvements in sleep, quality of life, depressive, and anxiety symptoms after rTMS and during follow-up. Improvements in sleep correlated with quality of life at follow-up.

CONCLUSION

This study suggests that personalized, parcel-guided rTMS is safe and may provide sustained improvements in sleep, quality of life, and affective symptoms for patients with affective disorders.

Objective sleep enhancement in Parkinson's disease: A sham-controlled trial of low-frequency repetitive transcranial magnetic stimulation over the right dorsolateral prefrontal cortex

INTRODUCTION

Parkinson's disease (PD) is often accompanied by sleep disturbances, impacting patients' quality of life. While repetitive transcranial magnetic stimulation (rTMS) shows promise in improving self-reported sleep quality, its effects on objective sleep architecture in PD remain understudied. Sleep disturbances, including rapid eye movement (REM) and slow-wave sleep disturbances, correlate with cognitive decline and motor symptoms. This study investigated the effect of low-frequency rTMS targeting the right dorsolateral prefrontal cortex (DLPFC) modifying objective sleep architecture and explored symptom improvement mechanisms in PD patients.

METHODS

In this randomized, double-blind, sham-controlled trial, 67 PD patients received 10 consecutive days of 1-Hz rTMS over the right DLPFC. Polysomnography assessed sleep microstructure, while electroencephalogram recordings evaluated power spectral density and sleep spindle activity. Clinical scales measured sleep quality, motor symptoms, and cognition at baseline, post-treatment, and 3 months post-rTMS.

RESULTS

The rTMS group exhibited improvements in sleep quality, motor symptoms, and cognition post-treatment, persisting at the 3-month follow-up. There was a notable increase in the REM sleep proportion post-rTMS. The rTMS group exhibited elevated low-frequency (0.5-2 Hz) slow-wave electroencephalogram spectral density during non-REM sleep. Cognitive enhancement correlated with increased lower delta power, while motor symptom progression correlated with spindle frequency and slow-wave sleep percentage changes.

CONCLUSION

Low-frequency rTMS targeting the right DLPFC holds promise for improving clinical symptoms and modulating sleep architecture in PD. These findings suggest a link between symptom improvement and sleep structure enhancement, highlighting the need for further investigation into the therapeutic potential of rTMS in PD management.

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.

Efficacy of transcranial photobiomodulation in the treatment for major depressive disorder: A TMS-EEG and pilot study

BACKGROUND

Major depressive disorder (MDD) was a prevalent mental condition that may be accompanied by decreased excitability of left frontal pole (FP) and abnormal brain connections. An 820 nm tPBM can induce an increase in stimulated cortical excitability. The purpose of our study was to establish how clinical symptoms and time-varying brain network connectivity of MDD were affected by transcranial photobiomodulation (tPBM).

METHODS

A total of 11 patients with MDD received 820 nm tPBM targeting the left FP for 14 consecutive days. The severity of symptoms was evaluated by neuropsychological assessments at baseline, after treatment, 4-week and 8-week follow-up; 8-min transcranial magnetic stimulation combined electroencephalography (TMS-EEG) was performed for five healthy controls and five patients with MDD before and after treatment, and time-varying EEG network was analyzed using the adaptive-directed transfer function.

RESULTS

All of scales scores in the 11 patients decreased significantly after 14-day tPBM (p < .01) and remained at 8-week follow-up. The time-varying brain network analysis suggested that the brain regions with enhanced connection information outflow in MDD became gradually more similar to healthy controls after treatment.

CONCLUSIONS

This study showed that tPBM of the left FP could improve symptoms of patients with MDD and normalize the abnormal network connections.

The role of the left dorsolateral prefrontal cortex in conflict control during insomnia disorder

BACKGROUND

Patients with insomnia are often accompanied by cognitive dysfunction, which seriously affects the quality of life of patients. Repetitive transcranial magnetic stimulation (rTMS) can induce brain neuroplasticity, regulate brain cognitive function and inhibitory control ability.

OBJECTIVE

To explore the intervention effect of rTMS on conflict control and sleep quality in patients with insomnia.

METHODS

In this single-blind, randomized controlled trial, 39 people with insomnia disorder were randomly divided into real stimulation group and sham stimulation group. The stimulation parameters were stimulation frequency 1 Hz, stimulation intensity 80 % resting motor threshold (RMT), total pulse number 1500 times, time 25 min, and the whole course of treatment lasted 7 days. The Insomnia Severity Index(ISI)、Pittsburgh Sleep Quality Index(PSQI)、Multidimensional Fatigue Inventory(MFI) and Beck Anxiety Inventory(BAI) were assessed at pretest (baseline) and posttest (day 7 after intervention), and the color-word stroop task was used to measure the conflict control ability of the subjects.

RESULTS

The sleep quality, correct rate and reaction time of the posttest in the real stimulus group were higher than those in the pretest. However, there was no significant difference between the pretest and posttest in the sham stimulation group.

CONCLUSIONS

rTMS stimulation of the left dorsolateral prefrontal cortex (LDLPFC) in patients with insomnia can significantly improve the conflict control ability and sleep quality of patients with insomnia.

Inferring Neural Communication Dynamics from Field Potentials Using Graph Diffusion Autoregression

Estimating dynamic network communication is attracting increased attention, spurred by rapid advancements in multi-site neural recording technologies and efforts to better understand cognitive processes. Yet, traditional methods, which infer communication from statistical dependencies among distributed neural recordings, face core limitations: they do not model neural interactions in a biologically plausible way, neglect spatial information from the recording setup, and yield predominantly static estimates that cannot capture rapid changes in the brain. To address these issues, we introduce a graph diffusion autoregressive model. Designed for distributed field potential recordings, our model combines vector autoregression with a network communication process to produce a high-resolution communication signal. We successfully validated the model on simulated neural activity and recordings from subdural and intracortical micro-electrode arrays placed in macaque sensorimotor cortex demonstrating its ability to describe rapid communication dynamics induced by optogenetic stimulation, changes in resting state communication, and the trial-by-trial variability during a reach task.

Efficacy of non-pharmacological interventions for sleep quality in Parkinson's disease: a systematic review and network meta-analysis

Background

Sleep disorders are one of the most common non-motor symptoms in PD. It can cause a notable decrease in quality of life and functioning in PD patients, as well as place a huge burden on both patients and caregivers. Currently, there are numerous non-pharmacological interventions available to improve sleep quality in PD, with disagreement as to which intervention is most effective. This network meta-analysis was performed to compare and rank non-pharmacological interventions to explore their efficacy in improving sleep quality in PD and to select the best interventions, with a view to providing references and bases for the development of clinical treatments and care programs.

Methods

The PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang databases were searched from inception to December 6, 2023. Two authors independently screened all studies, extracted the data, and evaluated risk of bias of included studies. STATA software version 17.0 was used to conduct the network meta-analysis.

Results

Our network meta-analysis included 29 studies involving 1,477 participants and 16 non-pharmacological interventions. Although most nonpharmacological interventions showed non-significant effects, the surface under the cumulative ranking curve (SUCRA) values indicated that the best non-pharmacological intervention for sleep disorders was massage therapy (97.3%), followed by music therapy (94.2%), and Treadmill training (85.7%).

Conclusion

Massage therapy can be considered as an effective therapy for improving sleep quality in patients with PD. Due to limited quantity and quality of the included studies, more high quality studies are required to verify the conclusions of this network meta-analysis.

Systematic review registration

identifier CRD42023429339, PROSPERO (york.ac.uk).

Predicting response to repetitive transcranial magnetic stimulation in patients with chronic insomnia disorder using electroencephalography: A pilot study

Predicting responsvienss to repetitive transcranial magnetic stimulation (rTMS) can facilitate personalized treatments with improved efficacy; however, predictive features related to this response are still lacking. We explored whether resting-state electroencephalography (rsEEG) functional connectivity measured at baseline or during treatment could predict the response to 10-day rTMS targeted to the right dorsolateral prefrontal cortex (DLPFC) in 36 patients with chronic insomnia disorder (CID). Pre- and post-treatment rsEEG scans and the Pittsburgh Sleep Quality Index (PSQI) were evaluated, with an additional rsEEG scan conducted after four rTMS sessions. Machine-learning approaches were employed to assess the ability of each connectivity measure to distinguish between responders (PSQI improvement > 25%) and non-responders (PSQI improvement ≤ 25%). Furthermore, we analyzed the connectivity trends of the two subgroups throughout the treatment. Our results revealed that the machine learning model based on baseline theta connectivity achieved the highest accuracy (AUC = 0.843) in predicting treatment response. Decreased baseline connectivity at the stimulated site was associated with higher responsiveness to TMS, emphasizing the significance of functional connectivity characteristics in rTMS treatment. These findings enhance the clinical application of EEG functional connectivity markers in predicting treatment outcomes.

Electroencephalography microstates as novel functional biomarkers for insomnia disorder

Background

Insomnia disorder (ID) is one of the most common mental disorders. Research on ID focuses on exploring its mechanism of disease, novel treatments and treatment outcome prediction. An emerging technique in this field is the use of electroencephalography (EEG) microstates, which offer a new method of EEG feature extraction that incorporates information from both temporal and spatial dimensions.

Aims

To explore the electrophysiological mechanisms of repetitive transcranial magnetic stimulation (rTMS) for ID treatment and use baseline microstate metrics for the prediction of its efficacy.

Methods

This study included 60 patients with ID and 40 age-matched and gender-matched good sleep controls (GSC). Their resting-state EEG microstates were analysed, and the Pittsburgh Sleep Quality Index (PSQI) and polysomnography (PSG) were collected to assess sleep quality. The 60 patients with ID were equally divided into active and sham groups to receive rTMS for 20 days to test whether rTMS had a moderating effect on abnormal microstates in patients with ID. Furthermore, in an independent group of 90 patients with ID who received rTMS treatment, patients were divided into optimal and suboptimal groups based on their median PSQI reduction rate. Baseline EEG microstates were used to build a machine-learning predictive model for the effects of rTMS treatment.

Results

The class D microstate was less frequent and contribute in patients with ID, and these abnormalities were associated with sleep onset latency as measured by PSG. Additionally, the abnormalities were partially reversed to the levels observed in the GSC group following rTMS treatment. The baseline microstate characteristics could predict the therapeutic effect of ID after 20 days of rTMS, with an accuracy of 80.13%.

Conclusions

Our study highlights the value of EEG microstates as functional biomarkers of ID and provides a new perspective for studying the neurophysiological mechanisms of ID. In addition, we predicted the therapeutic effect of rTMS on ID based on the baseline microstates of patients with ID. This finding carries great practical significance for the selection of therapeutic options for patients with ID.

Brain stimulation techniques as novel treatment options for insomnia: A systematic review

Despite the success of cognitive behavioural therapy for insomnia and recent advances in pharmacotherapy, many patients with insomnia do not sufficiently respond to available treatments. This systematic review aims to present the state of science regarding the use of brain stimulation approaches in treating insomnia. To this end, we searched MEDLINE, Embase and PsycINFO from inception to 24 March 2023. We evaluated studies that compared conditions of active stimulation with a control condition or group. Outcome measures included standardized insomnia questionnaires and/or polysomnography in adults with a clinical diagnosis of insomnia. Our search identified 17 controlled trials that met inclusion criteria, and assessed a total of 967 participants using repetitive transcranial magnetic stimulation, transcranial electric stimulation, transcutaneous auricular vagus nerve stimulation or forehead cooling. No trials using other techniques such as deep brain stimulation, vestibular stimulation or auditory stimulation met the inclusion criteria. While several studies report improvements of subjective and objective sleep parameters for different repetitive transcranial magnetic stimulation and transcranial electric stimulation protocols, important methodological limitations and risk of bias limit their interpretability. A forehead cooling study found no significant group differences in the primary endpoints, but better sleep initiation in the active condition. Two transcutaneous auricular vagus nerve stimulation trials found no superiority of active stimulation for most outcome measures. Although modulating sleep through brain stimulation appears feasible, gaps in the prevailing models of sleep physiology and insomnia pathophysiology remain to be filled. Optimized stimulation protocols and proof of superiority over reliable sham conditions are indispensable before brain stimulation becomes a viable treatment option for insomnia.

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.

Using TMS-EEG to assess the effects of neuromodulation techniques: a narrative review

Over the past decades, among all the non-invasive brain stimulation (NIBS) techniques, those aiming for neuromodulatory protocols have gained special attention. The traditional neurophysiological outcome to estimate the neuromodulatory effect is the motor evoked potential (MEP), the impact of NIBS techniques is commonly estimated as the change in MEP amplitude. This approach has several limitations: first, the use of MEP limits the evaluation of stimulation to the motor cortex excluding all the other brain areas. Second, MEP is an indirect measure of brain activity and is influenced by several factors. To overcome these limitations several studies have used new outcomes to measure brain changes after neuromodulation techniques with the concurrent use of transcranial magnetic stimulation (TMS) and electroencephalogram (EEG). In the present review, we examine studies that use TMS-EEG before and after a single session of neuromodulatory TMS. Then, we focused our literature research on the description of the different metrics derived from TMS-EEG to measure the effect of neuromodulation.

Recovery of clinical, cognitive and cortical activity measures following mild traumatic brain injury (mTBI): A longitudinal investigation

The mechanisms that underpin recovery following mild traumatic brain injury (mTBI) remain poorly understood. Identifying neurophysiological markers and their functional significance is necessary to develop diagnostic and prognostic indicators of recovery. The current study assessed 30 participants in the subacute phase of mTBI (10-31 days post-injury) and 28 demographically matched controls. Participants also completed 3 month (mTBI: N = 21, control: N = 25) and 6 month (mTBI: N = 15, control: N = 25) follow up sessions to track recovery. At each time point, a battery of clinical, cognitive, and neurophysiological assessments was completed. Neurophysiological measures included resting-state electroencephalography (EEG) and transcranial magnetic stimulation combined with EEG (TMS-EEG). Outcome measures were analysed using mixed linear models (MLM). Group differences in mood, post-concussion symptoms and resting-state EEG resolved by 3 months, and recovery was maintained at 6 months. On TMS-EEG derived neurophysiological measures of cortical reactivity, group differences ameliorated at 3 months but re-emerged at 6 months, while on measures of fatigue, group differences persisted across all time points. Persistent neurophysiological changes and greater fatigue in the absence of measurable cognitive impairment may suggest the impact of mTBI on neuronal communication may leads to increased neural effort to maintain efficient function. Neurophysiological measures to track recovery may help identify both temporally optimal windows and therapeutic targets for the development of new treatments in mTBI.

820-nm Transcranial Near-infrared Stimulation on the Left DLPFC Relieved Anxiety: A Randomized, Double-blind, Sham-controlled Study

OBJECTIVE

Generalized anxiety disorder (GAD) is a chronic mood disease associated with abnormal brain network connections, including decreased activity in the left dorsolateral prefrontal cortex (DLPFC). Cortical excitability can be increased with 820-nm transcranial near-infrared stimulation (tNIRS), while transcranial magnetic stimulation with electroencephalography (TMS-EEG) can help evaluate time-varying brain network connectivity. A randomized, double-blind, sham-controlled trial was conducted to assess the efficacy of tNIRS on the left DLPFC and the impact on time-varying brain network connections in GAD patients.

METHODS

A total of 36 GAD patients were randomized to receive active or sham tNIRS for 2 weeks. Clinical psychological scales were assessed before, after, and at the 2-, 4-, and 8-week follow-ups. TMS-EEG was performed for 20minutes before and immediately after tNIRS treatment. The healthy controls did not receive tNIRS and only had TMS-EEG data collected once in the resting state.

RESULTS

The Hamilton Anxiety Scale (HAMA) scores of the active stimulation group decreased post-treatment compared with the sham group (P=0.021). The HAMA scores of the active stimulation group at the 2-, 4-, and 8-week follow-up assessments were lower than those before treatment (P<0.05). The time-varying EEG network pattern showed an information outflow from the left DLPFC and the left posterior temporal region after active treatment.

CONCLUSION

Herein, 820-nm tNIRS targeting the left DLPFC had significant positive effects on therapy for GAD that lasted at least 2 months. tNIRS may reverse the abnormality of time-varying brain network connections in GAD.

Effects on resting-state EEG phase-amplitude coupling in insomnia disorder patients following 1 Hz left dorsolateral prefrontal cortex rTMS

Despite burgeoning evidence for cortical hyperarousal in insomnia disorder, the existing results on electroencephalography spectral features are highly heterogeneous. Phase-amplitude coupling, which refers to the modulation of the low-frequency phase to a high-frequency amplitude, is probably a more sensitive quantitative measure for characterizing abnormal neural oscillations and explaining the therapeutic effect of repetitive transcranial magnetic stimulation in the treatment of patients with insomnia disorder. Sixty insomnia disorder patients were randomly divided into the active and sham treatment groups to receive 4 weeks of repetitive transcranial magnetic stimulation treatment. Behavioral assessments, resting-state electroencephalography recordings, and sleep polysomnography recordings were performed before and after repetitive transcranial magnetic stimulation treatment. Forty good sleeper controls underwent the same assessment. We demonstrated that phase-amplitude coupling values in the frontal and temporal lobes were weaker in Insomnia disorder patients than in those with good sleeper controls at baseline and that phase-amplitude coupling values near the intervention area were significantly enhanced after active repetitive transcranial magnetic stimulation treatment. Furthermore, the enhancement of phase-amplitude coupling values was significantly correlated with the improvement of sleep quality. This study revealed the potential of phase-amplitude coupling in assessing the severity of insomnia disorder and the efficacy of repetitive transcranial magnetic stimulation treatment, providing new insights on the abnormal physiological mechanisms and future treatments for insomnia disorder.

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.

Functional connectivity changes are correlated with sleep improvement in chronic insomnia patients after rTMS treatment

Background

Repetitive transcranial magnetic stimulation (rTMS) has been increasingly used as a treatment modality for chronic insomnia disorder (CID). However, our understanding of the mechanisms underlying the efficacy of rTMS is limited.

Objective

This study aimed to investigate rTMS-induced alterations in resting-state functional connectivity and to find potential connectivity biomarkers for predicting and tracking clinical outcomes after rTMS.

Methods

Thirty-seven patients with CID received a 10-session low frequency rTMS treatment applied to the right dorsolateral prefrontal cortex. Before and after treatment, the patients underwent resting-state electroencephalography recordings and a sleep quality assessment using the Pittsburgh Sleep Quality Index (PSQI).

Results

After treatment, rTMS significantly increased the connectivity of 34 connectomes in the lower alpha frequency band (8-10 Hz). Additionally, alterations in functional connectivity between the left insula and the left inferior eye junction, as well as between the left insula and medial prefrontal cortex, were associated with a decrease in PSQI score. Further, the correlation between the functional connectivity and PSQI persisted 1 month after the completion of rTMS as evidenced by subsequent electroencephalography (EEG) recordings and the PSQI assessment.

Conclusion

Based on these results, we established a link between alterations in functional connectivity and clinical outcomes of rTMS, which suggested that EEG-derived functional connectivity changes were associated with clinical improvement of rTMS in treating CID. These findings provide preliminary evidence that rTMS may improve insomnia symptoms by modifying functional connectivity, which can be used to inform prospective clinical trials and potentially for treatment optimization.

Theta-Burst Stimulation Combined With Virtual-Reality Reconsolidation Intervention for Methamphetamine Use Disorder: Study Protocol for a Randomized-Controlled Trial

Background

Craving associated with drug-related memory is one of the key factors that induce the relapse of methamphetamine (MA). Disruption or modulation of the reconsolidation of drug-related memory may serve as an option for clinical treatment of MA addiction. This protocol proposes to use virtual reality (VR) to retrieve drug-associated memory and then use transcranial magnetic stimulation (TMS) at the neural circuit that encodes the reward value of drug cues to provide a non-invasive intervention during reconsolidation. We aim to evaluate the effectiveness of TMS treatment after VR retrieval on the reduction of cue reactivity and craving of MA.

Methods

This is a randomized, double-blind, sham-controlled, parallel group trial, targeting participants with MA use disorder aged from 18 to 45 years old. Forty-five eligible volunteers in Shanxi Drug Rehabilitation Center will be recruited and be randomly allocated into three parallel groups, receiving either 1) MA-related cues retrieval in VR combined with active TMS (MA VR scene + TBS) or 2) sham TMS (MA VR scene + sham TBS), or 3) neutral cues retrieval in VR combined with active TMS (neutral VR scene + TBS). Two sessions of post-VR-retrieval TBS will be scheduled on two separate days within 1 week. The primary outcome will detect the memory-related activity by the electroencephalography (EEG) reactivity to drug cues in VR scenes. Secondary outcomes are the self-reported MA craving in VR scene, the physiological parameter (cue-induced heart rate) and the scores of psychological questionnaires including anxiety, depression, and mood. All primary and secondary outcomes will be assessed at baseline, 1-week, and 1-month post-intervention. Assessments will be compared between the groups of 1) MA VR scene + TBS, 2) MA VR scene + sham TBS and 3) neutral VR scene + TBS.

Discussion

This will be the first study to examine whether the TMS modulation after VR retrieval can reduce self-reported craving and drug-related cue reactivity. It will promote the understanding of the neural circuit mechanism of the reconsolidation-based intervention and provide an effective treatment for MA use disorder patients.

Clinical Trial Registration

[Chinese Clinical Trial Registry], identifier [ChiCTR1900026902]. Registered on 26 October 2019.

Constructing Time-varying Directed EEG network by Multivariate Nonparametric Dynamical Granger Causality

Time-varying directed electroencephalography (EEG) network is the potential tool for studying the dynamical causality among brain areas at a millisecond level; which conduces to understanding how our brain effectively adapts to information processing, giving inspiration to causality- and brain-inspired machine learning. Currently, its construction still mainly relies on the parametric approach such as multivariate adaptive autoregressive (MVAAR), represented by the most widely used adaptive directed transfer function (ADTF). Restricted by the model assumption, the corresponding performance largely depends on the MVAAR modeling which usually encounters difficulty in fitting complex spectral features. In this study, we proposed to construct EEG directed network with multivariate nonparametric dynamical Granger causality (mndGC) method that infers the causality of a network, instead, in a data-driven way directly and therefore avoids the trap in the model-dependent parametric approach. Comparisons between mndGC and ADTF were conducted both with simulation and real data application. Simulation study demonstrated the superiority of mndGC both in noise resistance and capturing the instantaneous directed network changes. When applying to the real motor imagery (MI) data set, distinguishable network characters between left- and right-hand MI during different MI stages were better revealed by mndGC. Our study extends the nonparametric causality exploration and provides practical suggestions for the time-varying directed EEG network analysis.

Improved Functional Organization in Patients With Primary Insomnia After Individually-Targeted Transcranial Magnetic Stimulation

Primary insomnia (PI) is among the most prevalent sleep-related disorders and has a far-reaching impact on daytime functioning. Repetitive transcranial magnetic stimulation (rTMS) has drawn attention because of its effectiveness and safety. The purpose of the current study was to detect changes in the topological organization of whole-brain functional networks and to determine their associations with the clinical treatment effects of rTMS. Resting-state functional magnetic resonance imaging (rsfMRI) data from 32 patients with PI were collected and compared with findings from 32 age- and gender-matched healthy controls (HCs). The patients were treated with Stanford accelerated intelligent neuromodulation therapy, which is a recently validated neuroscience-informed accelerated intermittent theta-burst stimulation protocol. Graph theoretical analysis was used to construct functional connectivity matrices and to extract the attribute features of small-world networks in insomnia. Scores on the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index, Self-Rating Anxiety Scale, Self-Rating Depression Scale, and the associations between these clinical characteristics and functional metrics, were the primary outcomes. At baseline, the patients with PI showed inefficient small-world property and aberrant functional segregation and functional integration compared with the HCs. These properties showed renormalization after individualized rTMS treatment. Furthermore, low functional connectivity between the right insula and left medial frontal gyrus correlated with improvement in ISI scores. We highlight functional network dysfunctions in PI patients and provide evidence into the pathophysiological mechanisms involved and the possible mode of action of rTMS.

Sleep Disturbances and Their Association With Quality of Life in Older Psychiatric Patients During the COVID-19 Pandemic

AIMS

The negative effect of the COVID-19 pandemic on sleep quality of clinically stable psychiatric patients is unknown. This study examined the prevalence of sleep disturbances and their association with quality of life (QOL) in clinically stable older psychiatric patients during the COVID-19 pandemic.

METHODS

This multicenter, cross-sectional study involved older patients attending maintenance treatment at outpatient departments of four major psychiatric hospitals in China. Patients' socio-demographic and clinical characteristics were collected. Sleep disturbances, depressive symptoms, and QOL were assessed with the Insomnia Severity Index, the 9-item Patient Health Questionnaire, and 2 items of the World Health Organization Quality of Life-Brief version, respectively. Binary logistic regression analysis was conducted to examine the independent associations of socio-demographic and clinical variables with sleep disturbances, while the association between sleep disturbances and QOL was explored with analysis of covariance.

RESULTS

A total of 941 patients were recruited. The prevalence of sleep disturbances was 57.1% (95% CI: 53.9-60.2%). Analysis of covariance revealed that QOL was significantly lower in patients with sleep disturbances compared to those without. Multivariate logistic regression analysis showed that sleep disturbances were positively and independently associated with more severe depressive symptoms (OR = 1.32, 95% CI: 1.26-1.37). Compared to patients with major depressive disorder, those with other psychiatric diagnoses had a significantly higher prevalence of sleep disturbances (OR = 1.44, 95% CI: 1.00-2.08).

CONCLUSION

Sleep disturbances were common among clinically stable older psychiatric patients during the COVID-19 pandemic. Considering the negative association with QOL, this subpopulation needs regular assessment and timely treatment to reduce their sleep disturbances and improve their QOL.

Transcranial magnetic stimulation for sleep disorders in Alzheimer's disease: A double-blind, randomized, and sham-controlled pilot study

BACKGROUND

Sleep disorders are commonly comorbid with Alzheimer's disease (AD), And these disorders interfere with each other in many aspects. To date, pharmacological treatments for sleep disorders are still limited, and studies investigating repetitive transcranial magnetic stimulation (rTMS) for sleep disorders in AD are still lacking.

METHOD

A single-center, randomized, double-blind, parallel-arm, and sham-controlled pilot study was conducted in AD patients with sleep disorders. Seventy subjects were randomly divided into the following two groups: the sham group (SG) and the intervention group (IG). We evaluated sleep changes using the Pittsburgh Sleep Quality Index (PSQI) before and after the intervention. We also assessed the patients' cognitive function by the Alzheimer's Disease Assessment Scale-Cognitive section (ADAS-Cog). The intervention period was four weeks, and the patients were followed up in the 8th week to test the persistence of the effect of the rTMS intervention.

RESULT

Significant differences in the PSQI scores were found between the SG and IG at the end of the 4-week intervention (P = 0.001) and the 8-week follow-up (P < 0.001). There was also significant improvement in ADAS-Cog scores (4 weeks: P = 0.048, 8 weeks: P = 0.038). Activities of daily living (ADL) did not significantly differ between the SG and IG.

CONCLUSION

rTMS can effectively ameliorate sleep disorders in AD patients.

Electroencephalographic connectivity predicts clinical response to repetitive transcranial magnetic stimulation in patients with insomnia disorder

BACKGROUND

Accumulating evidence suggests that low frequency repetitive transcranial magnetic stimulation (rTMS), which generally decreases cortical excitability and remodels plastic connectivity, improves sleep quality in patients with insomnia disorder. However, the effects of rTMS vary substantially across individuals and treatment is sometimes unsatisfactory, calling for biomarkers for predicting clinical outcomes.

OBJECTIVE

This study aimed to investigate whether functional connectivity of the target network in electroencephalography is associated with the clinical response to low frequency rTMS in patients with insomnia disorder.

METHODS

Twenty-five patients with insomnia disorder were subjected to 10 sessions of treatment with 1 Hz rTMS over the right dorsolateral prefrontal cortex. Resting-state electroencephalography was collected before rTMS. Pittsburgh Sleep Quality Index, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, and Mini-Mental State Exam were performed before and after rTMS treatment, with a follow-up after one month. Electroencephalographic connectivity was measured by the power envelope connectivity at the source level. Partial least squares regression identified models of connectivity that maximally accounted for the rTMS response.

RESULTS

Scores of Pittsburgh Sleep Quality Index, Hamilton Depression Rating Scale, and Hamilton Anxiety Rating Scale were decreased after rTMS and one-month later. Baseline weaker connectivity of a network in the beta and alpha bands between a brain region approximating the stimulated right dorsolateral prefrontal cortex and areas located in the frontal, insular, and limbic cortices was associated with a greater change in Pittsburgh Sleep Quality Index and Hamilton Depression Rating Scale following rTMS.

CONCLUSIONS

Low frequency rTMS could improve sleep quality and depressive moods in patients with insomnia disorder. Moreover, electroencephalographic functional connectivity would potentially be a robust biomarker for predicting the therapeutic effects.

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

The etiology of psychiatric disorders remains largely unknown. The exploration of the neurobiological mechanisms of mental illness helps improve diagnostic efficacy and develop new therapies. This review focuses on the application of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) in various mental diseases, including major depressive disorder, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, substance use disorder, and insomnia. First, we summarize the commonly used protocols and output measures of TMS-EEG; then, we review the literature exploring the alterations in neural patterns, particularly cortical excitability, plasticity, and connectivity alterations, and studies that predict treatment responses and clinical states in mental disorders using TMS-EEG. Finally, we discuss the potential mechanisms underlying TMS-EEG in establishing biomarkers for psychiatric disorders and future research directions.

Transcranial magnetic stimulation therapeutic applications on sleep and insomnia: a review

Repetitive transcranial magnetic stimulation (rTMS) is a neuromodulatory technique approved by the US Food and Drug Administration for use in treatment-resistant major depressive disorder. It works by generating localized magnetic fields that create depolarizing electrical currents in neurons a few centimeters below the scalp. This localized effect is believed to stimulate neural plasticity, activate compensatory processes, and influence cortical excitability. Additionally, rTMS has been used in a variety of clinical trials for neurological and psychiatric conditions such as anxiety, post-traumatic stress disorder and epilepsy. Beneficial effects in sleep parameters have been documented in these trials, as well as in major depressive disorder, and have led to an interest in using rTMS in the field of sleep medicine for specific disorders such as insomnia, hypersomnia, and restless legs syndrome. It is unknown whether rTMS has intrinsically beneficial properties when applied to primary sleep disorders, or if it only acts on sleep through mood disorders. This narrative review sought to examine available literature regarding the application of rTMS for sleep disorder to identify knowledge gaps and inform future study design. The literature in this area remains scarce, with few randomized clinical trials on rTMS and insomnia. Available studies have found mixed results, with some studies reporting subjective sleep improvement while objective improvement is less consistent. Due to the heterogeneity of results and the variations in rTMS protocols, no definitive conclusions have been reached, signaling the need for further research.

Repetitive Transcranial Magnetic Stimulation Modulates Frontal and Temporal Time-Varying EEG Network in Generalized Anxiety Disorder: A Pilot Study

Generalized Anxiety Disorder (GAD) is a highly prevalent yet poorly understood chronic mental disorder. Previous studies have associated GAD with excessive activation of the right dorsolateral prefrontal cortex (DLPFC). This study aimed to investigate the effect of low-frequency repetitive transcranial magnetic stimulation (repetitive TMS, rTMS) targeting the right DLPFC on clinical symptoms and TMS-evoked time-varying brain network connectivity in patients with GAD. Eleven patients with GAD received 1 Hz rTMS treatment targeting the right DLPFC for 10 days. The severity of the clinical symptoms was evaluated using the Hamilton Anxiety Scale (HAMA) and the Hamilton Depression Scale (HAMD) at baseline, right after treatment, and at the one-month follow-up. Co-registration of single-pulse TMS (targeting the right DLPFC) and electroencephalography (TMS-EEG) was performed pre- and post-treatment in these patients and 11 healthy controls. Time-varying brain network connectivity was analyzed using the adaptive directed transfer function. The scores of HAMA and HAMD significantly decreased after low-frequency rTMS treatment, and these improvements in ratings remained at the one-month follow-up. Analyses of the time-varying EEG network in the healthy controls showed a continuous weakened connection information outflow in the left frontal and mid-temporal regions. Compared with the healthy controls, the patients with GAD showed weakened connection information outflow in the left frontal pole and the posterior temporal pole at baseline. After 10-day rTMS treatment, the network patterns showed weakened connection information outflow in the left frontal and temporal regions. The time-varying EEG network changes induced by TMS perturbation targeting right DLPFC in patients with GAD were characterized by insufficient information outflow in the left frontal and temporal regions. Low-frequency rTMS targeting the right DLPFC reversed these abnormalities and improved the clinical symptoms of GAD.

The Management and Alternative Therapies for Comorbid Sleep Disorders in Epilepsy

BACKGROUND

There is a complex and interactive relationship between sleep and epilepsy. Sleep disorders are common in patients with epilepsy, and methods for managing sleep disorders in patients with epilepsy are limited.

OBJECTIVE

This review addresses the relationship among sleep, sleep disorders, and epilepsy, focusing on the management of sleep disorders in epilepsy, including some complementary and alternative therapies.

METHODS

The terms related to "sleep" and "epilepsy" were searched in "Pubmed" and "Cochrane Library".

RESULTS

Sleep stages differently affect both seizures and interictal epileptiform discharges. Seizures disrupt sleep architecture greatly, especially when occurring during sleep in the night. Insomnia and obstructive sleep apnea (OSA) are the most frequent types of comorbid sleep disorders in patients with epilepsy. Pharmacological agents with both anti-convulsant and sedative effects are the priorities for comorbid sleep disorders in epilepsy. Continuous positive airway pressure (CPAP) therapy is the most effective non-pharmacological method to improve OSA and reduce seizures. Complementary and alternative therapies such as Chinese traditional medicine, cognitive behavioral therapy, meditation, yoga, neurofeedback, and acupuncture may have benefits in reducing seizures and improving sleep quality simultaneously by alleviating stress and seizure triggers; however, evidence- based therapies are still deficient.

CONCLUSION

Management of sleep disorders in patients with epilepsy is challenging. Large-scale randomized controlled clinical trials are in demand to guide the treatments in the future.

Repetitive transcranial magnetic stimulation of the cerebellum improves ataxia and cerebello-fronto plasticity in multiple system atrophy: a randomized, double-blind, sham-controlled and TMS-EEG study

Cerebellar ataxia is the predominant motor feature of multiple system atrophy cerebellar subtype (MSA-C). Although repetitive transcranial magnetic stimulation (TMS) of the cerebellum is growingly applied in MSA, the mechanism is unknown. We examined dynamic connectivity changes of 20 patients with MSA and 25 healthy controls using TMS combined with electroencephalography. Observations that significantly decreased dynamic cerebello-frontal connectivity in patients have inspired attempts to modulate cerebellar connectivity in order to benefit MSA. We further explore the therapeutic potential of a 10-day treatment of cerebellar intermittent theta burst stimulation (iTBS) in MSA by a randomized, double-blind, sham-controlled trial. The functional reorganization of cerebellar networks was investigated after the end of treatment in active and sham groups. The severity of the symptoms was evaluated using the Scale for Assessment and Rating of Ataxia scores. Patients treated with active stimulation showed an improvement of cerebello-frontal connectivity and balance functions, as revealed by a significant decrease in the ataxia scores (P < 0.01). Importantly, the neural activity of frontal connectivity from 80 to 100 ms after a single TMS was significantly related to the severity of the disease. Our study provides new proof that cerebellar iTBS improves motor imbalance in MSA by acting on cerebello-cortical plasticity.

Altered response to repetitive transcranial magnetic stimulation in patients with chronic primary insomnia

BACKGROUND

We aimed at evaluating the amplitude changes of the motor evoked potentials (MEPs) induced by of low-frequency (LF) repetitive transcranial magnetic stimulation (rTMS) over the primary motor cortex (M1) in10 patients with primary insomnia (PI) and in 10 age-matched healthy controls.

METHODS

Median peak-to-peak MEP amplitudes were assessed in all subjects at three times: at baseline (T₀), after the first train of a single rTMS session (T₁), and after the whole rTMS procedure (T₂). This consists of 20 trains of 1 Hz stimulation with 50 stimuli per train and an intertrain interval of 30 s.

RESULTS

Resting motor threshold (RMT) and MEPs amplitude did not differ between the two groups at T₀. A reduction of MEP size was observed at both T₁ and T₂ in all subjects, but this was significantly less pronounced in patients than in control subjects.

CONCLUSIONS

The lack of MEP inhibition reflects an altered response to LF rTMS in patients with PI. These rTMS findings are indicative of an altered cortical plasticity in inhibitory circuits within M1 in PI. Subjects with PI exhibited an impairment of the LTD-like mechanisms induced by inhibitory rTMS, thus providing further support to the involvement of GABA neurotransmission in the pathophysiology of PI.

Linear and Nonlinear EEG-Based Functional Networks in Anxiety Disorders

Electrocortical network dynamics are integral to brain function. Linear and nonlinear connectivity applications enrich neurophysiological investigations into anxiety disorders. Discrete EEG-based connectivity networks are unfolding with some homogeneity for anxiety disorder subtypes. Attenuated delta/theta/beta connectivity networks, pertaining to anterior-posterior nodes, characterize panic disorder. Nonlinear measures suggest reduced connectivity of ACC as an executive neuro-regulator in germane "fear circuitry networks" might be more central than considered. Enhanced network complexity and theta network efficiency at rest define generalized anxiety disorder, with similar tonic hyperexcitability apparent in social anxiety disorder further extending to task-related/state functioning. Dysregulated alpha connectivity and integration of mPFC-ACC/mPFC-PCC relays implicated with attentional flexibility and choice execution/congruence neurocircuitry are observed in trait anxiety. Conversely, state anxiety appears to recruit converging delta and beta connectivity networks as panic, suggesting trait and state anxiety are modulated by discrete neurobiological mechanisms. Furthermore, EEG connectivity dynamics distinguish anxiety from depression, despite prevalent clinical comorbidity. Rethinking mechanisms implicated in the etiology, maintenance, and treatment of anxiety from the perspective of EEG network science across micro- and macroscales serves to shed light and move the field forward.