Elsevier

Sleep Medicine

Volume 56, April 2019, Pages 157-163
Sleep Medicine

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

https://doi.org/10.1016/j.sleep.2019.01.007Get rights and content

Highlights

  • Low frequency rTMS has significant positive effects on the treatment of PI that can last for at least one month.

  • PI patients show abnormal changes of time-varying EEG networks compared with healthy controls.

  • rTMS neuromodulation treatment could reverse this EEG networks abnormity.

Abstract

Introduction

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive method, and its application in the treatment of primary insomnia (PI) is poorly researched. PI is considered to be a functional disorder with abnormal brain network connections. TMS combined electroencephalography (EEG) is a valuable method for directly probing excitability and dynamic connectivity of different regions in the brain. We aimed to investigate the therapeutic efficacy of rTMS and its impact on brain network connections in PI patients.

Methods

Twenty patients with PI were recruited in this study and received 1 Hz rTMS treatment for 14 consecutive days. The severity of symptoms was evaluated using the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI) and the Epworth Sleepiness Scale (ESS). Twenty minutes TMS-EEG were performed before and immediately after treatment. EEG data was collected by 10-20 EEG system with the sample rate of 1024 Hz. Time-varying EEG network was analyzed using the adaptive directed transfer function. The EEG network results of patients were compared with those of 20 healthy subjects.

Results

In the present study, we found that PSQI, ISI, and ESS ratings of the patients decreased significantly (P<0.05) after rTMS treatment, and the improvement in ratings lasted one month. Compared with healthy subjects, single-pulse TMS targeting right posterior parietal cortex of PI patients before therapy showed excessive information outflow from the left occipital region, the frontal mid-line region and the right posterior temporal region, in succession. Meanwhile, inadequate information outflow was seen in the right central region, right parietal region, as well as in the right temporal region. Compared with prior treatment, PI patients showed increased information outflow in the left temporal region and decreased information outflow in the frontal mid-line region.

Conclusion

Low frequency rTMS targeting the right posterior parietal cortex has significant positive effects on the treatment of PI that can last for at least one month and can reverse abnormal changes of time-varying EEG networks.

Introduction

Insomnia is a common disorder that has significant long-term health consequences. Primary insomnia (PI) is one of the most prevalent chronic sleep disorders [1] and is not attributable to a medical, psychiatric, or environmental cause [2]. It is refers to the difficulty of falling asleep or maintaining sleep for at least one month [3]. Epidemiologically, 10% of the adult population experiences chronic insomnia. Moreover, in the future PI is predicted to rises to 25% globally [4]. Previous studies have shown that patients with PI may present with a variety of psychiatric disorders [5]. In addition, PI is known to be associated with impaired neuropsychological performance [6]. This has been recognized as an important public health issue, which has increased the burden on social and health expense [7]. Yet, despite its large socio-economic and physical impacts, its efficacy and safety issues may largely limit the clinical application of currently available treatment strategies.

At present, pharmacological and cognitive behavioral treatments (CBT) for PI are used [8]. Medications that are used have developed over time, but the optimal treatment program of the most commonly used strategies produce undesired side effects. However, in the past three years, the potential relationship between the use of sedative hypnotics for insomnia and increased mortality has become a topic of major controversy. Several retrospective cohort researches have already looked at the daily intake of 10 mg zolpidem, and have associated it to an overall increased risk of cancer and falls [9], [10].

CBT is a multimodal treatment that combines many behavioral and cognitive interventions including sleep hygiene, stimulus control, sleep restriction, relaxation training, and cognitive restructuring [11]. Currently, a hierarchy comprising five levels of CBT stepped care is suggested; furthermore, for professional and pragmatic reasons, it is always applied by nurses and therapists [12]. However, because of the shortage of local therapist that have the necessary training, CBT is not widely available. Moreover, in many countries, CBT can be expensive for PI patients to afford and can be seen as financially unsustainable for clinicians because of restrictions due to medical insurance [13].

Repetitive transcranial magnetic stimulation (rTMS) is a type of non-medication treatment. Although rTMS has been shown to be effective in many neuropsychiatric disorders, for example, depression [14] and selected anxiety disorders, such as posttraumatic stress disorder [15] and obsessive compulsive disorder [16], the effectiveness of rTMS in treating PI has not been adequately addressed. Lanza et al., found that rTMS may be effective in neuromodulation in restless legs syndrome (RLS) [17], [18]. To date, there have only been a few published researches relating to rTMS for the treatment of PI. Our research group, led by Huang et al., demonstrated that 1 Hz rTMS to the right posterior parietal cortex is effective for both anxiety and insomnia symptoms in patients with comorbid GAD and insomnia [19]. However, neural substrates remain poorly understood.

At the time of this writing, the most useful method of studying brain network connections are functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). fMRI is based on the blood-oxygen-level dependent effect and has high spatial resolution but with low time resolution [20]. EEG signal mainly use directed transfer function [21] to observe brain connections, which has high time spatial. Currently, adapted directed transfer function (ADTF) [22] can reveal connections between different brain regions at different frequencies with time [23], [24], which is called a time-varying EEG network. Excitatory changes induced by various stimuli can also be expressed through brain network connections. Moreover, a single-pulse TMS (sTMS) does not only change the neural activity in the stimulated areas but modulates the excitability of interconnected distant sites [25]. Furthermore, a TMS pulse can induce a synchronization of distant cortical areas. Thus, it modulates the information, which processes and changes the functional connectivity patterns in specialized interconnected cortical modules [26]. TMS-EEG have been applied to study and quantify brain network connectivity [27].

Previous studies demonstrated the effectiveness of rTMS treatment and found that rTMS may be a potential tool for modifying neural activity in stimulated areas, as well as in functionally connected cortical regions [28], [29], more research should be focused on the mechanisms of neural network connectivity. Given the previous evidence of abnormal brain connections in PI patients, together with the findings of rTMS treatment of insomnia, we hypothesized that PI may be a brain functional disease with abnormal brain network connections, and that rTMS therapy may correct this network anomaly, and thus achieves a therapeutic effect. In the present study, we tested our hypothesis by stimulating the right posterior parietal cortex with a low frequency rTMS as well as by using ADTF analyses of TMS-EEG signals to investigate the changes of the time-varying EEG network before and after treatment, compared with the healthy control (HC) group.

Section snippets

Subjects

This study was approved by the Ethics Committee of Capital Medical University Xuanwu Hospital. All PI patients were outpatients from the Department of Neurology, Xuanwu Hospital, Capital Medical University. All HC were recruited by advertising. All participants provided written informed consent to participate in this study.

PI patients were recruited consecutively and required to meet the Diagnostic and Statistical Manual (DSM-V) of Mental Disorders by American Psychiatric Association. DSM-V

Neuropsychological characteristics

Neuropsychological data are shown in Table 2. As expected, patients with PI had higher PSQI, ESS and ISI scores than the HCs (P < 0.05), and significant decline after rTMS treatment and one month after treatment (Table 2).

Time-varying EEG network patterns

Based on the above time-varying network analysis, Fig. 1 and Fig. 2 show the corresponding time-varying EEG network patterns of PI patients before and after treatment as well as HCs.

In HCs, sTMS targeting the right posterior parietal cortex can induce a continuous increase of

Discussion

To the best of our knowledge, this study was the first to use low frequency rTMS to treat PI via stimulating the right posterior parietal region. The ADTF analysis of time-varying EEG network was performed to better understand the underlying neural connection mechanisms of PI patients. In the present study we found that low frequency rTMS stimulating the right posterior parietal cortex was effective to improve the symptoms of insomnia in PI patients, and that PI abnormal time-varying EEG

Conclusion

The present study was designed to determine the effectiveness of low frequency rTMS therapy for PI. We found that the curative effect lasted at least one month. PI patients showed abnormal changes of time-varying EEG networks. Our study revealed that excessive information outflow in the left posterior temporal region and frontal mid-line region; and inadequate information outflow in the right central, right parietal and right temporal regions. Low frequency rTMS treatment targeting the right

Acknowledgments

The study was supported in part by the Beijing Municipal Science and Technology Commission (No. Z161100002616001) and the National Natural Science Foundation (No. 81501119), of China.

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