Dorsolateral prefrontal transcranial magnetic stimulation in patients with major depression locally affects alpha power of REM sleep

Non-linear processing and reinforcement learning to predict rTMS treatment response in depression

BACKGROUND

Forecasting the efficacy of repetitive transcranial magnetic stimulation (rTMS) therapy can lead to substantial time and cost savings by preventing futile treatments. To achieve this objective, we've formulated a machine learning approach aimed at categorizing patients with major depressive disorder (MDD) into two groups: individuals who respond (R) positively to rTMS treatment and those who do not respond (NR).

METHODS

Preceding the commencement of treatment, we obtained resting-state EEG data from 106 patients diagnosed with MDD, employing 32 electrodes for data collection. These patients then underwent a 7-week course of rTMS therapy, and 54 of them exhibited positive responses to the treatment. Employing Independent Component Analysis (ICA) on the EEG data, we successfully pinpointed relevant brain sources that could potentially serve as markers of neural activity within the dorsolateral prefrontal cortex (DLPFC). These identified sources were further scrutinized to estimate the sources of activity within the sensor domain. Then, we integrated supplementary physiological data and implemented specific criteria to yield more realistic estimations when compared to conventional EEG analysis. In the end, we selected components corresponding to the DLPFC region within the sensor domain. Features were derived from the time-series data of these relevant independent components. To identify the most significant features, we used Reinforcement Learning (RL). In categorizing patients into two groups - R and NR to rTMS treatment - we utilized three distinct classification algorithms including K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Multilayer Perceptron (MLP). We assessed the performance of these classifiers through a ten-fold cross-validation method. Additionally, we conducted a statistical test to evaluate the discriminative capacity of these features between responders and non-responders, opening the door for further exploration in this field.

RESULTS

We identified EEG features that can anticipate the response to rTMS treatment. The most robust discriminators included EEG beta power, the sum of bispectrum diagonal elements in the delta and beta frequency bands. When these features were combined into a single vector, the classification of responders and non-responders achieved impressive performance, with an accuracy of 95.28 %, specificity at 94.23 %, sensitivity reaching 96.29 %, and precision standing at 94.54 %, all achieved using SVM.

CONCLUSIONS

The results of this study suggest that the proposed approach, utilizing power, non-linear, and bispectral features extracted from relevant independent component time-series, has the capability to forecast the treatment outcome of rTMS for MDD patients based solely on a single pre-treatment EEG recording session. The achieved findings demonstrate the superior performance of our method compared to previous techniques.

Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study

Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5-4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8-12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.

Machine learning approaches and non-linear processing of extracted components in frontal region to predict rTMS treatment response in major depressive disorder

Predicting the therapeutic result of repetitive transcranial magnetic stimulation (rTMS) treatment could save time and costs as ineffective treatment can be avoided. To this end, we presented a machine-learning-based strategy for classifying patients with major depression disorder (MDD) into responders (R) and nonresponders (NR) to rTMS treatment. Resting state EEG data were recorded using 32 electrodes from 88 MDD patients before treatment. Then, patients underwent 7 weeks of rTMS, and 46 of them responded to treatment. By applying Independent Component Analysis (ICA) on EEG, we identified the relevant brain sources as possible indicators of neural activity in the dorsolateral prefrontal cortex (DLPFC). This was served through estimating the generators of activity in the sensor domain. Subsequently, we added physiological information and placed certain terms and conditions to offer a far more realistic estimation than the classic EEG. Ultimately, those components mapped in accordance with the region of the DLPFC in the sensor domain were chosen. Features extracted from the relevant ICs time series included permutation entropy (PE), fractal dimension (FD), Lempel-Ziv Complexity (LZC), power spectral density, correlation dimension (CD), features based on bispectrum, frontal and prefrontal cordance, and a combination of them. The most relevant features were selected by a Genetic Algorithm (GA). For classifying two groups of R and NR, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Multilayer Perceptron (MLP) were applied to predict rTMS treatment response. To evaluate the performance of classifiers, a 10-fold cross-validation method was employed. A statistical test was used to assess the capability of features in differentiating R and NR for further research. EEG characteristics that can predict rTMS treatment response were discovered. The strongest discriminative indicators were EEG beta power, the sum of bispectrum diagonal elements in delta and beta bands, and CD. The Combined feature vector classified R and NR with a high performance of 94.31% accuracy, 92.85% specificity, 95.65% sensitivity, and 92.85% precision using SVM. This result indicates that our proposed method with power and nonlinear and bispectral features from relevant ICs time-series can predict the treatment outcome of rTMS for MDD patients only by one session pretreatment EEG recording. The obtained results show that the proposed method outperforms previous methods.

Layer III pyramidal cells in the prefrontal cortex reveal morphological changes in subjects with depression, schizophrenia, and suicide

Brodmann Area 46 (BA46) has long been regarded as a hotspot of disease pathology in individuals with schizophrenia (SCH) and major depressive disorder (MDD). Pyramidal neurons in layer III of the Brodmann Area 46 (BA46) project to other cortical regions and play a fundamental role in corticocortical and thalamocortical circuits. The AutoCUTS-LM pipeline was used to study the 3-dimensional structural morphology and spatial organization of pyramidal cells. Using quantitative light microscopy, we used stereology to calculate the entire volume of layer III in BA46 and the total number and density of pyramidal cells. Volume tensors estimated by the planar rotator quantified the volume, shape, and nucleus displacement of pyramidal cells. All of these assessments were carried out in four groups of subjects: controls (C, n = 10), SCH (n = 10), MDD (n = 8), and suicide subjects with a history of depression (SU, n = 11). SCH subjects had a significantly lower somal volume, total number, and density of pyramidal neurons when compared to C and tended to show a volume reduction in layer III of BA46. When comparing MDD subjects with C, the measured parameters were inclined to follow SCH, although there was only a significant reduction in pyramidal total cell number. While no morphometric differences were observed between SU and MDD, SU had a significantly higher total number of pyramidal cells and nucleus displacement than SCH. Finally, no differences in the spatial organization of pyramidal cells were found among groups. These results suggest that despite significant morphological alterations in layer III of BA46, which may impair prefrontal connections in people with SCH and MDD, the spatial organization of pyramidal cells remains the same across the four groups and suggests no defects in neuronal migration. The increased understanding of pyramidal cell biology may provide the cellular basis for symptoms and neuroimaging observations in SCH and MDD patients.

Using multisession tDCS stimulation as an early intervention on memory bias processing in subthreshold depression

Transcranial direct current stimulation (tDCS) as an intervention tool has gained promising results in major depression disorder. However, studies related to subthreshold depression's (SD) cognitive deficits and neuromodulation approaches for the treatment of SD are still rare. We adopted Beck's cognitive model of depression and tested the tDCS stimulation effects on attentional and memory deficits on SD. First, this was a single-blinded, randomized, sham-controlled clinical trial to determine a 13-day tDCS modulation effect on 49 SD (27: Stimulation; 22: Sham) and 17 healthy controls. Second, the intervention effects of the consecutive and single-session tDCS were compared. Furthermore, the attentional and memory biases were explored in SD. Anodal tDCS was administrated over left dorsolateral prefrontal cortex for 13 consecutive days. Attentional and memory bias were assessed through a modified Sternberg task and a dot-probe task on the 1st, 2nd, and 15th day while their EEG was being recorded. After the 13-day tDCS stimulation (not after single-session stimulation), we found reduced memory bias (Stimulation vs. Sham, p = .02, r²  = .09) and decreased mid-frontal alpha power (p < .01, r²  = .13). In contrast, tDCS did not affect any attentional related behavioral or neural indexes (all ps > .15). Finally, reduced depressive symptoms (e.g., BDI score) were found for both groups. The criteria of SD varied across studies; the efficacy of this protocol should be tested in elderly patients. Our study suggests memory bias of SD can be modulated by the multisession tDCS and alpha power could serve as a neural index for intervention.

High-frequency Repetitive Transcranial Magnetic Stimulation (rTMS) Accelerates onset Time of Beneficial Treating Effects and Improves Clinical Symptoms of Depression

BACKGROUND

In recent years, more and more patients with depression demonstrate suicidal intention and suicidal behavior.

OBJECTIVE

To evaluate the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in treating depression with suicidal ideation.

METHODS

Eighty-nine depression patients with suicide intention were administrated drugs combined with four weeks of Active rTMS (n=40) or sham (n=49) rTMS treatment. The 24-item Hamilton Depression Rating Scale for Depression (HAMD-24) and Self-rating Idea of Suicide Scale (SIOSS) were used to evaluate suicide risk and depression severity at baseline, weeks 2 and 4. A 25% reduction in HAMD-24 score from baseline was defined as treatment response. More than a 20% reduction in HAMD-24 score from baseline within the first 2 weeks of treatment was defined as an early improvement.

RESULTS

No statistical significance was found for baseline sociodemographic and illness characteristics between the two groups (P >0.05). There was a significant difference for HAMD-24 and SIOSS scores between the two groups at weeks 2 and 4. Active rTMS group demonstrated a more significant score reduction compared to the Sham rTMS group at weeks 2 and 4. There was a significantly greater number of patients with early improvement observed in the Active rTMS group compared to those in the Sham rTMS group at weeks 2 (P <0.05). There was a significant difference in responder rates between the two groups at weeks 4 for HAMD-24 scores (P <0.05).

CONCLUSION

rTMS could accelerate the onset time of beneficial treating effects and improve clinical symptoms of depression. During the treatment course, cognitive disorder, sleep disorder, anxiety/ somatization, retardation, and hopelessness symptoms were improved dramatically, and suicidal ideation was reduced.

Local and Transient Changes of Sleep Spindle Density During Series of Prefrontal Repetitive Transcranial Magnetic Stimulation in Patients With a Major Depressive Episode

The neuromodulatory effects of brain stimulation therapies notably involving repetitive transcranial magnetic stimulation (rTMS) on nocturnal sleep, which is critically disturbed in major depression and other neuropsychiatric disorders, remain largely undetermined. We have previously reported in major depression patients that prefrontal rTMS sessions enhanced their slow wave activity (SWA) power, but not their sigma power which is related to sleep spindle activity, for electrodes located nearby the stimulation site. In the present study, we focused on measuring the spindle density to investigate cumulative effects of prefrontal rTMS sessions on the sleep spindle activity. Fourteen male inpatients diagnosed with medication-resistant unipolar or bipolar depression were recruited and subjected to 10 daily rTMS sessions targeting the left dorsolateral prefrontal cortex (DLPFC). All-night polysomnography (PSG) data was acquired at four time points: Adaptation, Baseline, Post-1 (follow-up after the fifth rTMS session), and Post-2 (follow-up after the tenth rTMS session). Clinical and cognitive evaluations were longitudinally performed at Baseline, Post-1, and Post-2 time points to explore associations with the spindle density changes. The PSG data from 12 of 14 patients was analyzed to identify sleep spindles across the sleep stages II–IV at four electrode sites: F3 (frontal spindle near the stimulation site), F4 (contralateral homologous frontal region), P3 (parietal spindle in the hemisphere ipsilateral to the stimulation site), and P4 (contralateral parietal region). Statistical analysis by two-way ANOVA revealed that spindle density at F3 increased at Post-1 but decreased at Post-2 time points. Moreover, the local and transient increase of spindle density at F3 was associated with the previously reported SWA power increase at F3, possibly reflecting a shared mechanism of thalamocortical synchronization locally enhanced by diurnal prefrontal rTMS sessions. Clinical and cognitive correlations were not observed in this dataset. These findings suggest that diurnal rTMS sessions transiently modulate nocturnal sleep spindle activity at the stimulation site, although clinical and cognitive effects of the local changes warrant further investigation.

Effects of transcranial magnetic stimulation on sleep quality and mood in patients with major depressive disorder

STUDY OBJECTIVES

It is unknown whether sleep quality improvements after repetitive transcranial magnetic stimulation (rTMS) are inherent to the intervention or related to improvements in depressive symptoms. This retrospective study examined sleep quality in patients with major depressive disorder (MDD) before and after treatment with rTMS, adjusting for age, sex, sedative-hypnotic use, number of rTMS treatments, depression severity and changes in depressive symptoms.

METHODS

Adults with MDD underwent a six-week course of 10 Hz rTMS over the left dorsolateral prefrontal cortex (DLPFC). Patients completed the Patient Health Questionnaire-9 (PHQ-9) depression rating scale and Pittsburgh Sleep Quality Index (PSQI) before and after treatment. To limit confounding, analysis of depressive symptoms occurred without item 3 (the sleep item) of the PHQ-9.

RESULTS

Twenty-one patients completed the study, with a mean (± standard deviation) baseline PSQI score of 12.0 (±3.8), compared to 10.5 (±4.3) post-treatment (p = 0.01). The mean baseline PHQ-9 score without item 3 was 17.3 (±3.0), compared to 12.2 (±4.9) post-treatment (p = 0.0001). PSQI and modified PHQ-9 changes were uncorrelated in non-adjusted and adjusted linear regression models, as well as in Spearman's rank-order correlation.

CONCLUSIONS

Mood and sleep quality improved independently following rTMS treatment, even after adjusting for age, sex, sedative-hypnotic use, number of rTMS treatments and depression severity. These findings suggest that rTMS exerts direct effects on both mood and sleep in patients with MDD.

Clinical and demographic predictors of response to anodal tDCS treatment in major depression disorder (MDD)

Transcranial direct current stimulation (tDCS) of the prefrontal cortex is known as a promising intervention in major depression disorder (MDD). However, limited information on predictors of therapeutic response to tDCS are available. This study aimed to investigate clinical and demographic predictors of therapeutic response in patients taking no medications. For this purpose, the required data were collected from 2 independent tDCS trials on 116 MDD patients. Accordingly, 84 patients underwent 10 sessions of 2 mA tDCS daily each one lasted for 20 min and 32 patients received 10 twice sessions of 2 mA tDCS daily each one lasted for 20 min. Anodal electrode was located over the left dorsolateral prefrontal cortex (DLPFC), and cathode was over the right supraorbital region. Depression symptoms and the underlying clinical dimensions were assessed using the Beck Depression Inventory (BDI-II) at baseline and after the tDCS treatment. Of the included 116 patients, 47.4% showed an antidepressant response. Results of logistic regression analysis showed that the reduction in BDI-II scores after tDCS was associated with the baseline values of cognitive-affective symptoms factor, loss of pleasure, loss of interest, and sleep problems. Pronounced sleep disturbances and cognitive-affective symptoms were identified as the potential clinical predictors of response to tDCS. However, more prospective tDCS studies are necessary to validate the predictive value of the derived model.

Characterizing Cortical Oscillatory Responses in Major Depressive Disorder Before and After Convulsive Therapy: A TMS-EEG Study

BACKGROUND

Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a powerful technique for interrogating neural circuit dysfunction in psychiatric disorders. Here, we utilized time-frequency analyses to characterize differences in neural oscillatory dynamics between subjects with major depressive disorder (MDD) and healthy controls (HC). We further examined changes in TMS-related oscillatory power following convulsive therapy.

METHODS

Oscillatory power was examined following TMS over the dorsolateral prefrontal and motor cortices (DLPFC and M1) in 38 MDD subjects, and 22 HCs. We further investigated how these responses changed in the MDD group following an acute course of convulsive therapy (either magnetic seizure therapy [MST, n = 24] or electroconvulsive therapy [ECT, n = 14]).

RESULTS

Prior to treatment, MDD subjects exhibited increased oscillatory power within delta, theta, and alpha frequency bands with TMS-EEG over the DLPFC, but showed no differences to HCs with stimulation over M1. Following MST, DLPFC stimulation revealed attenuated baseline-normalized power in the delta and theta bands, with reductions in the delta, theta, and alpha power following ECT. TMS over M1 revealed reduced delta and theta power following ECT, with no changes observed following MST. An association was also observed between the treatment- induced change in alpha power and depression severity score.

LIMITATIONS

Limitations include the modest sample size, open-label MST and ECT treatment designs, and lack of a placebo condition.

CONCLUSIONS

These results provide evidence of alterations in TMS-related oscillatory activity in MDD, and further suggest modulation of oscillatory power following ECT and MST.

Repetitive Transcranial Magnetic Stimulation for Treatment-Resistant Depression: Recent Critical Advances in Patient Care

PURPOSE

Transcranial magnetic stimulation (TMS) is an evidence-based treatment for pharmacoresistant major depressive disorder (MDD). In the last decade, the field has seen significant advances in the understanding and use of this new technology. This review aims to describe the large, randomized controlled studies leading to the modern use of rTMS for MDD. It also includes a special section briefly discussing the use of these technologies during the COVID-19 pandemic.

RECENT FINDINGS

Several new approaches and technologies are emerging in this field, including novel approaches to reduce treatment time and potentially yield new approaches to optimize and maximize clinical outcomes. Of these, theta burst TMS now has evidence indicating it is non-inferior to standard TMS and provides significant advantages in administration. Recent studies also indicate that neuroimaging and related approaches may be able to improve TMS targeting methods and potentially identify those patients most likely to respond to stimulation.

SUMMARY

While new data is promising, significant research remains to be done to individualize and optimize TMS procedures. Emerging new approaches, such as accelerated TMS and advanced targeting methods, require additional replication and demonstration of real-world clinical utility. Cautious administration of TMS during the pandemic is possible with careful attention to safety procedures.

The Relationship of Transcranial Magnetic Stimulation With Sleep and Plasticity

Neuroplasticity is an area of expanding interest in psychiatry. Plasticity and metaplasticity are processes contributing to the scaling up and down of neuronal connections, and they are involved with changes in learning, memory, mood, and sleep. Effective mood treatments, including repetitive transcranial magnetic stimulation (rTMS), are reputed to work via changes in neuronal circuitry. This article explores the interrelatedness of sleep, plasticity, and rTMS treatment. A PubMed-based literature review was conducted to identify all available studies examining the relationship of rTMS, plasticity, and sleep. Key words used in this search included "TMS," "transcranial magnetic stimulation," "plasticity," "metaplasticity," "sleep," and "insomnia." Depressed mood tends to be associated with impaired neural plasticity, while antidepressant treatments can augment neural plasticity. rTMS impacts plasticity, yielding long-lasting effects, with differing impacts on the waking and sleeping brain. Higher quality sleep promotes plasticity and learning. Reports on the sleep impact of high-frequency and low-frequency rTMS are mixed. The efficacy of rTMS may rely on brain plasticity manipulation, enhanced via the stimulation of neural circuits. Total sleep time and sleep continuity are sleep qualities that are likely necessary but insufficient for the homeostatic plasticity driven by slow-wave sleep. Understanding the relationship between sleep and rTMS treatment is likely critical to enhancing outcomes.

Sleep quality improves during treatment with repetitive transcranial magnetic stimulation (rTMS) in patients with cocaine use disorder: a retrospective observational study

BACKGROUND

Sleep disturbance is a prominent and common complaint in people with cocaine use disorder (CUD), either during intake or withdrawal. Repetitive transcranial magnetic stimulation (rTMS) has shown promise as a treatment for CUD. Thus, we evaluated the relationship between self-perceived sleep quality and cocaine use pattern variables in outpatients with CUD undergoing an rTMS protocol targeted at the left dorsolateral prefrontal cortex.

METHODS

This is a retrospective observational study including 87 patients diagnosed with CUD according to the DSM-5 criteria. Scores in Pittsburgh Sleep Quality Index (PSQI), Cocaine Craving Questionnaire (CCQ), Beck Depression Inventory-II (BDI-II), Self-rating Anxiety Scale (SAS), and Symptoms checklist 90-Revised (outcome used: Global Severity Index, GSI) were recorded at baseline, and after 5, 30, 60, and 90 days of rTMS treatment. Cocaine use was assessed by self-report and regular urine screens.

RESULTS

Sleep disturbances (PSQI scores > 5) were common in patients at baseline (mean ± SD; PSQI score baseline: 9.24 ± 3.89; PSQI > 5 in 88.5% of patients). PSQI scores significantly improved after rTMS treatment (PSQI score Day 90: 6.12 ± 3.32). Significant and consistent improvements were also seen in craving and in negative-affect symptoms compared to baseline. Considering the lack of a control group, in order to help the conceptualization of the outcomes, we compared the results to a wait-list group (n = 10). No significant improvements were observed in the wait-list group in any of the outcome measures.

CONCLUSIONS

The present findings support the therapeutic role of rTMS interventions for reducing cocaine use and accompanying symptoms such as sleep disturbance and negative-affect symptoms.

TRIAL REGISTRATION

ClinicalTrials.gov.NCT03733821.

Cannabinoids as an Emerging Therapy for Posttraumatic Stress Disorder and Substance Use Disorders

Posttraumatic Stress Disorder (PTSD) is a leading psychiatric disorder that mainly affects military and veteran populations but can occur in anyone affected by trauma. PTSD treatment remains difficult for physicians because most patients with PTSD do not respond to current pharmacological treatment. Psychotherapy is effective, but time consuming and expensive. Substance use disorder is often concurrent with PTSD, which leads to a significant challenge for PTSD treatment. Cannabis has recently received widespread attention for the potential to help many patient populations. Cannabis has been reported as a coping tool for patients with PTSD and preliminary legalization data indicate Cannabis use may reduce the use of more harmful drugs, such as opioids. Rigorous clinical studies of Cannabis could establish whether Cannabis-based medicines can be integrated into treatment regimens for both PTSD and substance use disorder patients.

Improvement in hypersomnia with high frequency repetitive transcranial magnetic stimulation in depressed adolescents: Preliminary evidence from an open-label study

STUDY OBJECTIVES

Sleep disruption is a significant symptom of major depressive disorder (MDD). To our knowledge, no prior work has examined the impact of repetitive transcranial magnetic stimulation (rTMS) on sleep disturbances in adolescents with MDD.

METHODS

Seventeen adolescents with treatment-resistant depression received 30 daily sessions of 10-Hz rTMS applied to the left dorsolateral prefrontal cortex (L-DLPFC). Clinical symptoms were assessed at baseline; after 10, 20, and 30 treatments; and at a 6-month follow-up visit. Insomnia was measured with a 3-item subscale of the Quick Inventory of Depressive Symptomatology-Adolescent (17 Item)-Self Report (QIDS-A₁₇-SR). Hypersomnia was measured with a single QIDS-A₁₇-SR item. Depression severity was rated with the Children's Depression Rating Scale, Revised (CDRS-R). The effect of rTMS on sleep was examined via linear mixed model analyses, with fixed effects of time (as a proxy of treatment), depression severity, age, and hypnotic medication use.

RESULTS

No significant main effect of time was observed on the insomnia subscale (F_4,43.442 = 1.078, p = 0 .379). However, there was a significant main effect of time on the QIDS-A₁₇-SR hypersomnia score (F_4,46.124 = 2.733, p = 0 .040), with significant improvement from baseline to treatment 10 (p_adj = 0.019) and from baseline to 6-month follow-up (p_adj = 0.044). In exploratory sensitivity analyses, response/nonresponse to rTMS for overall depressive symptoms had no significant effect on sleep outcomes.

CONCLUSIONS

rTMS may have intrinsic effects on hypersomnia apart from its antidepressant effects in depressed adolescents. Future work should utilize sham controls and objective, quantitative measurements of sleep architecture to assess effects of rTMS in depressed adolescents.

CLINICAL TRIAL REGISTRY

Clinicaltrials.gov identifiers are NCT00587639, NCT01502033, NCT01804270.

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal

BACKGROUND

Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS) treatment is an important purpose that eliminates financial and psychological consequences of applying inefficient therapy. To achieve this goal we proposed a method based on machine learning to classify responders (R) and non- responders (NR) to rTMS treatment for major depression disorder (MDD) patients.

METHODS

19 electrodes resting state EEG was recorded from 46 MDD patients before treatment. Then patients underwent 7 weeks of rTMS, and 23 of them responded to treatment. Features extracted from EEG include Lempel-Ziv complexity (LZC), Katz fractal dimension (KFD), correlation dimension (CD), the power spectral density, features based on bispectrum, frontal and prefrontal cordance and combination of them. The most relevant features were selected by the minimal-redundancy-maximal-relevance (mRMR) feature selection algorithm. For classifying two groups of R and NR, k-nearest neighbors (KNN) were applied. The performance of the proposed method was evaluated by leave-1-out cross-validation. For further study, the capability of features in differentiating R and NR was investigated by a statistical test.

RESULTS

Effective EEG features for prediction of rTMS treatment response were found. EEG beta power, the sum of bispectrum diagonal elements in delta and beta bands and CD were the most discriminative features. Power of beta classified R and NR with the high performance of 91.3% accuracy, 91.3% specificity, and 91.3% sensitivity.

LIMITATIONS

Lack of large sample size restricted our method for using in clinical applications.

CONCLUSION

This considerable high accuracy indicates that our proposed method with power and some of the nonlinear and bispectral features can lead to promising results in predicting treatment outcome of rTMS for MDD patients only by one session pretreatment EEG recording.

Clinical Improvements in Comorbid Gambling/Cocaine Use Disorder (GD/CUD) Patients Undergoing Repetitive Transcranial Magnetic Stimulation (rTMS)

(1) Background: Pathological gambling behaviors may coexist with cocaine use disorder (CUD), underlying common pathogenic mechanisms. Repetitive transcranial magnetic stimulation (rTMS) has shown promise as a therapeutic intervention for CUD. In this case series, we evaluated the clinical effects of rTMS protocol stimulating the left dorsolateral prefrontal cortex (DLPFC) on the pattern of gambling and cocaine use. (2) Methods: Gambling severity, craving for cocaine, sleep, and other negative affect symptoms were recorded in seven patients with a diagnosis of gambling disorder (South Oaks Gambling Screen (SOGS) >5), in comorbidity with CUD, using the following scales: Gambling-Symptom Assessment Scale (G-SAS), Cocaine Craving Questionnaire (CCQ), Beck Depression Inventory-II (BDI-II), Self-rating Anxiety Scale (SAS), and Symptoms checklist-90 (SCL-90). The measures were assessed before the rTMS treatment and after 5, 30, and 60 days of treatment. Patterns of gambling and cocaine use were assessed by self-report and regular urine screens. (3) Results: Gambling severity at baseline ranged from mild to severe (mean ± Standard Error of the Mean (SEM), G-SAS score baseline: 24.42 ± 2.79). G-SAS scores significantly improved after treatment (G-SAS score Day 60: 2.66 ± 1.08). Compared to baseline, consistent improvements were significantly seen in craving for cocaine and in negative-affect symptoms. (4) Conclusions: The present findings provide unprecedent insights into the potential role of rTMS as a therapeutic intervention for reducing both gambling and cocaine use in patients with a dual diagnosis.

Sleep-wake, cognitive and clinical correlates of treatment outcome with repetitive transcranial magnetic stimulation for young adults with depression

The utility of key phenotypes of depression in predicting response to repetitive transcranial magnetic stimulation (rTMS), namely sleep-wake behaviour, cognition and illness chronicity, has been understudied and not been extended to young samples. This study aimed to determine whether sleep-wake disturbance, cognition or depression chronicity are associated with rTMS outcome in young depressed adults. Sixteen depressed young adults diagnosed with mood disorders (aged 18-29 years) completed this open-label study. Neuronavigationally targeted high-frequency rTMS was administered at 110% of motor threshold on the left dorsolateral prefrontal cortex for 20 sessions over 4 weeks. Clinical, sleep-wake and cognitive assessments were undertaken pre- and post-treatment. Repeated-measures and correlational analyses determined pre- and post-treatment changes and predictors of treatment outcome. rTMS significantly reduced depression and anxiety. Better cognitive flexibility, verbal learning, later age of onset and greater number of depressive episodes were associated with better treatment outcome. There were no other significant/trend-level associations. rTMS had no effect on sleep-wake or cognitive measures. We provide the first evidence for the utility of cognitive flexibility and verbal learning in predicting rTMS outcome in depressed young adults. This research provides preliminary support for rTMS as an early intervention for depression and supports the need for sham-controlled trials.

Differentiating responders and non-responders to rTMS treatment for depression after one week using resting EEG connectivity measures

BACKGROUND

Non-response to repetitive transcranial magnetic stimulation (rTMS) treatment for depression is costly for both patients and clinics. Simple and cheap methods to predict response would reduce this burden. Resting EEG measures differentiate responders from non-responders, so may have utility for response prediction.

METHODS

Fifty patients with treatment resistant depression and 21 controls had resting electroencephalography (EEG) recorded at baseline (BL). Patients underwent 5-8 weeks of rTMS treatment, with EEG recordings repeated at week 1 (W1). Forty-two participants had valid BL and W1 EEG data, and 12 were responders. Responders and non-responders were compared at BL and W1 in measures of theta (4-8 Hz) and alpha (8-13 Hz) power and connectivity, frontal theta cordance and alpha peak frequency. Control group comparisons were made for measures that differed between responders and non-responders. A machine learning algorithm assessed the potential to differentiate responders from non-responders using EEG measures in combination with change in depression scores from BL to W1.

RESULTS

Responders showed elevated theta connectivity across BL and W1. No other EEG measures differed between groups. Responders could be distinguished from non-responders with a mean sensitivity of 0.84 (p = 0.001) and specificity of 0.89 (p = 0.002) using cross-validated machine learning classification on the combination of all EEG and mood measures.

LIMITATIONS

The low response rate limited our sample size to only 12 responders.

CONCLUSION

Resting theta connectivity at BL and W1 differ between responders and non-responders, and show potential for predicting response to rTMS treatment for depression.

Are there clinical and neurophysiologic predictive factors for a positive response to HF-rTMS in patients with treatment-resistant depression?

Better selection of patients with treatment-resistant depression for high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) would make the procedure more efficient. The objective of this study was to search for clinical and neurophysiologic predictors of therapeutic response with a special focus on the bipolar population. Forty patients (30 bipolar) underwent 20 daily sessions of HF-rTMS. Clinical outcome measures included the 21-item Hamilton Depression Rating Scale, the Beck Depression Inventory, the Clinical Global Impression, and the Patient Global Impression. Neurophysiologic measurements included repeated estimation of the motor threshold and cortical silent period. Improvement was obtained in all psychometric scales, with no difference between unipolar and bipolar patients. Longer duration of the illness, higher number of prior hospitalizations, and more disturbed activity were associated with a worse response to rTMS, and somatic anxiety, sleep disorders, and health worries were positive predictors. In bipolar patients, longer disease duration and therapy with mirtazapine, mianserin, trazodone, hydroxyzine, and promethazine were associated with a worse response. Sleep disturbances, higher baseline motor threshold, and longer cortical silent period predicted a better response. In this study, we found several clinical and neurophysiologic predictors of better/worse responses to the standard HF-rTMS protocol. Our preliminary data need to be reproduced.

Effective treatment of narcolepsy-like symptoms with high-frequency repetitive transcranial magnetic stimulation: A case report

RATIONALE

Narcolepsy is a rare sleep disorder with disrupted sleep-architecture. Clinical management of narcolepsy lies dominantly on symptom-driven pharmacotherapy. The treatment role of repetitive transcranial magnetic stimulation (rTMS) for narcolepsy remains unexplored.

PATIENT CONCERNS

In this paper, we present a case of a 14-year-old young girl with excessive daytime sleepiness (EDS), cataplexy and hypnagogic hallucinations.

DIAGNOSES

After excluding other possible medical conditions, this patient was primarily diagnosed with narcolepsy.

INTERVENTIONS

The patient received 25 sessions of high-frequency rTMS over the left dorsolateral prefrontal cortex (DLPFC).

OUTCOMES

The symptoms of EDS and cataplexy significantly improved after rTMS treatment. Meanwhile, her score in the Epworth sleep scale (ESS) also remarkably decreased.

LESSONS

This case indicates that rTMS may be selected as a safe and effective alternative strategy for treating narcolepsy-like symptoms. Well-designed researches are warranted in future investigations on this topic.

Can neurophysiologic measures serve as biomarkers for the efficacy of repetitive transcranial magnetic stimulation treatment of major depressive disorder?

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for Major Depressive Disorder (MDD). There are clinical data that support the efficacy of many different approaches to rTMS treatment, and it remains unclear what combination of stimulation parameters is optimal to relieve depressive symptoms. Because of the costs and complexity of studies that would be necessary to explore and compare the large number of combinations of rTMS treatment parameters, it would be useful to establish reliable surrogate biomarkers of treatment efficacy that could be used to compare different approaches to treatment. This study reviews the evidence that neurophysiologic measures of cortical excitability could be used as biomarkers for screening different rTMS treatment paradigms. It examines evidence that: (1) changes in excitability are related to the mechanism of action of rTMS; (2) rTMS has consistent effects on measures of excitability that could constitute reliable biomarkers; and (3) changes in excitability are related to the outcomes of rTMS treatment of MDD. An increasing body of evidence indicates that these neurophysiologic measures have the potential to serve as reliable biomarkers for screening different approaches to rTMS treatment of MDD.

Opposite Impact of REM Sleep on Neurobehavioral Functioning in Children with Common Psychiatric Disorders Compared to Typically Developing Children

Rapid eye movement (REM) sleep has been shown to be related to many adaptive cognitive and behavioral functions. However, its precise functions are still elusive, particularly in developmental psychiatric disorders. The present study aims at investigating associations between polysomnographic (PSG) REM sleep measurements and neurobehavioral functions in children with common developmental psychiatric conditions compared to typically developing children (TDC). Twenty-four children with attention-deficit/hyperactivity disorder (ADHD), 21 with Tourette syndrome/tic disorder (TD), 21 with ADHD/TD comorbidity, and 22 TDC, matched for age and gender, underwent a two-night PSG, and their psychopathological scores and intelligence quotient (IQ) were assessed. Major PSG findings showed more REM sleep and shorter REM latency in the children with psychiatric disorders than in the TDC. Multiple regression analyses revealed that in groups with developmental psychopathology, REM sleep proportion correlated positively with scores of inattention and negatively with performance IQ. In contrast, in the group of TDC, REM sleep proportion correlated negatively with scores of inattention and positively with performance IQ. Whilst shorter REM latency was associated with greater inattention scores in children with psychopathology, no such an association existed in the group of TDC. Altogether, these results indicate an opposite impact of REM sleep on neurobehavioral functioning, related to presence or absence of developmental psychiatric disorders. Our findings suggest that during development, REM sleep functions may interact dissimilarly with different pathways of brain maturation.

The Effect of High-Frequency Repetitive Transcranial Magnetic Stimulation on Occupational Stress among Health Care Workers: A Pilot Study

OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) was approved by the Food and Drug Administration to alleviate symptoms of treatment-resistant depression. This study aimed to evaluate the effectiveness of rTMS treatment on alleviating occupational stress by evaluating clinical symptoms and quantitative electroencephalography (QEEG).

METHODS

Twenty-four health care workers were randomized to receive 12 sessions of active or sham rTMS delivered to the left dorsolateral prefrontal cortex (DLPFC). Each session consisted of 32 trains of 10 Hz repetitive TMS delivered in 5-second trains at 110% of the estimated prefrontal cortex threshold. Before and after the intervention, the Korean version of the occupational stress inventory (K-OSI), Beck's depression inventory (BDI), and Beck's anxiety inventory (BAI) were administered and EEG was performed using a 21-channel digital EEG system.

RESULTS

After TMS, the average scores for the affective responses to stressors on the personal strain questionnaire (PSQ) subscale of K-OSI and BDI decreased significantly for the active-TMS group compared to the sham-TMS group. Also, the active-TMS group showed a significantly greater decrease in relative alpha in the F3 electrode and a significantly greater increase in the F4 electrode.

CONCLUSION

High-frequency rTMS on the left DLPFC had stress-relieving and mood-elevating effects in health care workers, likely by stimulating the left frontal lobe.

Effects of repetitive transcranial magnetic stimulation of upper airway muscles during sleep in obstructive sleep apnea patients

We tested the hypothesis that stimulating the genioglossus by repetitive transcranial magnetic stimulation (rTMS) during the ascendant portion of the inspiratory flow of airflow-limited breaths would sustain the recruitment of upper airway dilator muscles over time and improve airway dynamics without arousing obstructive sleep apnea (OSA) patients. In a cross-sectional design, nine OSA patients underwent a rTMS trial during stable non-rapid eye movement (NREM) sleep. Submental muscle motor threshold (SUB) and motor-evoked potential were evaluated during wakefulness and sleep. During NREM sleep, maximal inspiratory flow, inspiratory volume, inspiratory time, shifts of electroencephalogram frequency, and pulse rate variability were assessed under three different stimulation paradigms completed at 1.2 sleep SUB stimulation output: 1) 5Hz-08 (stimulation frequency: 5 Hz; duration of train stimulation: 0.8 s); 2) 25Hz-02 (stimulation frequency: 25 Hz; duration of train stimulation: 0.2 s); and 3) 25Hz-04 (stimulation frequency: 25 Hz; duration of train stimulation: 0.4 s). SUB increased during NREM sleep (wakefulness: 23.8 ± 6.1%; NREM: 26.8 ± 5.2%; = 0.001). Two distinct airflow patterns were observed in response to rTMS: with and without initial airflow drops, without other airflow variables change regardless the stimulation paradigm applied. Finally, rTMS-induced cortical and/or autonomic arousal were observed in 36, 26, and 35% of all delivered rTMS trains during 5Hz-08, 25Hz-02, and 25Hz-04 stimulation paradigms, respectively. In conclusion, rTMS does not provide any airflow improvement of flow-limited breaths as seen with nonrepetitive TMS of upper airway dilator muscles. However, rTMS trains were free of arousals in the majority of cases.

PreSMA stimulation changes task-free functional connectivity in the fronto-basal-ganglia that correlates with response inhibition efficiency

Previous work using transcranial magnetic stimulation (TMS) demonstrated that the right presupplementary motor area (preSMA), a node in the fronto-basal-ganglia network, is critical for response inhibition. However, TMS influences interconnected regions, raising the possibility of a link between the preSMA activity and the functional connectivity within the network. To understand this relationship, we applied single-pulse TMS to the right preSMA during functional magnetic resonance imaging when the subjects were at rest to examine changes in neural activity and functional connectivity within the network in relation to the efficiency of response inhibition evaluated with a stop-signal task. The results showed that preSMA-TMS increased activation in the right inferior-frontal cortex (rIFC) and basal ganglia and modulated their task-free functional connectivity. Both the TMS-induced changes in the basal-ganglia activation and the functional connectivity between rIFC and left striatum, and of the overall network correlated with the efficiency of response inhibition and with the white-matter microstructure along the preSMA-rIFC pathway. These results suggest that the task-free functional and structural connectivity between the rIFCop and basal ganglia are critical to the efficiency of response inhibition. Hum Brain Mapp 37:3236-3249, 2016. © 2016 Wiley Periodicals, Inc.

Neurobiological mechanisms of repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex in depression: a systematic review

Depression is one of the most prevalent mental illnesses worldwide and a leading cause of disability, especially in the setting of treatment resistance. In recent years, repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising alternative strategy for treatment-resistant depression and its clinical efficacy has been investigated intensively across the world. However, the underlying neurobiological mechanisms of the antidepressant effect of rTMS are still not fully understood. This review aims to systematically synthesize the literature on the neurobiological mechanisms of treatment response to rTMS in patients with depression. Medline (1996-2014), Embase (1980-2014) and PsycINFO (1806-2014) were searched under set terms. Three authors reviewed each article and came to consensus on the inclusion and exclusion criteria. All eligible studies were reviewed, duplicates were removed, and data were extracted individually. Of 1647 articles identified, 66 studies met both inclusion and exclusion criteria. rTMS affects various biological factors that can be measured by current biological techniques. Although a number of studies have explored the neurobiological mechanisms of rTMS, a large variety of rTMS protocols and parameters limits the ability to synthesize these findings into a coherent understanding. However, a convergence of findings suggest that rTMS exerts its therapeutic effects by altering levels of various neurochemicals, electrophysiology as well as blood flow and activity in the brain in a frequency-dependent manner. More research is needed to delineate the neurobiological mechanisms of the antidepressant effect of rTMS. The incorporation of biological assessments into future rTMS clinical trials will help in this regard.

The Neurobiological Mechanisms and Treatments of REM Sleep Disturbances in Depression

Most depressed patients suffer from sleep abnormalities, which are one of the critical symptoms of depression. They are robust risk factors for the initiation and development of depression. Studies about sleep electroencephalograms have shown characteristic changes in depression such as reductions in non-rapid eye movement sleep production, disruptions of sleep continuity and disinhibition of rapid eye movement (REM) sleep. REM sleep alterations include a decrease in REM sleep latency, an increase in REM sleep duration and REM sleep density with respect to depressive episodes. Emotional brain processing dependent on the normal sleep-wake regulation seems to be failed in depression, which also promotes the development of clinical depression. Also, REM sleep alterations have been considered as biomarkers of depression. The disturbances of norepinephrine and serotonin systems may contribute to REM sleep abnormalities in depression. Lastly, this review also discusses the effects of different antidepressants on REM sleep disturbances in depression.

The EEG as an index of neuromodulator balance in memory and mental illness

There is a strong correlation between signature EEG frequency patterns and the relative levels of distinct neuromodulators. These associations become particularly evident during the sleep-wake cycle. The monoamine-acetylcholine balance hypothesis is a theory of neurophysiological markers of the EEG and a detailed description of the findings that support this proposal are presented in this paper. According to this model alpha rhythm reflects the relative predominance of cholinergic muscarinic signals and delta rhythm that of monoaminergic receptor effects. Both high voltage synchronized rhythms are likely mediated by inhibitory Gαi/o-mediated transduction of inhibitory interneurons. Cognitively, alpha and delta EEG measures are proposed to indicate automatic and flexible strategies, respectively. Sleep is associated with marked changes in relative neuromodulator levels corresponding to EEG markers of distinct stages. Sleep studies on memory consolidation present some of the strongest evidence yet for the respective roles of monoaminergic and cholinergic projections in declarative and non-declarative memory processes, a key theoretical premise for understanding the data. Affective dysregulation is reflected in altered EEG patterns during sleep.