Fronto-central resting-state 15-29 Hz transient beta events change with therapeutic transcranial magnetic stimulation for posttraumatic stress disorder and major depressive disorder

Dysfunctional oscillatory bursting patterns underlie working memory deficits in adolescents with ADHD

Identifying neural markers of clinical symptom fluctuations is prerequisite to developing more precise brain-targeted treatments in psychiatry. We have recently shown that working memory (WM) in healthy adults is dependent on the rise and fall interplay between alpha/beta and gamma bursts within frontoparietal regions, and that deviations in these patterns lead to WM performance errors. However, it is not known whether such bursting deviations underlie clinically relevant WM-related symptoms or clinical status in individuals with WM deficits. In adolescents (n=27) with attention deficit hyperactivity disorder (ADHD), we investigated WM-related dynamics between alpha/beta and gamma bursts in relation to clinical status fluctuations. Participants repeatedly completed a visual Sternberg spatial working memory task during EEG recording as part of their participation in two research studies (n=224 person-sessions). Source localizing EEG data to each participant's structural MRI, the rate and volume of alpha, beta, and gamma bursts were examined within the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC). Alpha/beta and gamma bursts at the DLPFC and PPC displayed complimentary roles in WM processes. Alpha/beta bursting decreased during stimuli encoding and increased during the delay, while gamma bursting was elevated during encoding and decreased during the delay. Deviations in bursting patterns were associated with WM errors and clinical symptoms. We conclude that dysfunctional alpha/beta and gamma burst dynamics within the frontoparietal region underlie both intra-individual WM performance and WM symptom fluctuations in adolescents with ADHD. Such burst dynamics reflect a novel target and biomarker for WM-related treatment development.

Transcranial Magnetic Stimulation for Posttraumatic Stress Disorder and Generalized Anxiety Disorder

Posttraumatic stress disorder (PTSD) and generalized anxiety disorder (GAD) are debilitating psychiatric disorders. While treatments are often effective, many patients do not adequately respond or experience significant side effects. Transcranial magnetic stimulation (TMS) is an emerging approach for treating PTSD and GAD. Several randomized clinical trials have demonstrated that TMS over the dorsolateral prefrontal cortex may be efficacious in reducing psychiatric symptoms; however, results are inconsistent regarding whether any parameter or treatment paradigm is superior. Other RCTs have targeted novel brain regions using newer TMS modalities. Combining TMS with psychotherapy may augment response in patients with PTSD, yet results are inconclusive. Little research has been done on TMS in combination with psychotherapy for GAD, indicating a need for further investigation. Future studies may assess TMS parameter optimization for enhancing effectiveness and improving therapeutic response duration. Identifying response biomarkers through functional magnetic resonance imaging and electroencephalography may offer a means to predict and monitor clinical response as precision methods to improve treatment response.

Multiband EEG signature decoded using machine learning for predicting rTMS treatment response in major depression

Major depressive disorder (MDD) is a global health challenge with high prevalence. Further, many diagnosed with MDD are treatment resistant to traditional antidepressants. Repetitive transcranial magnetic stimulation (rTMS) offers promise as an alternative solution, but identifying objective biomarkers for predicting treatment response remains underexplored. Electroencephalographic (EEG) recordings are a cost-effective neuroimaging approach, but traditional EEG analysis methods often do not consider patient-specific variations and fail to capture complex neuronal dynamics. To address this, we propose a data-driven approach combining iterated masking empirical mode decomposition (itEMD) and sparse Bayesian learning (SBL). Our results demonstrated significant prediction of rTMS outcomes using this approach (Protocol 1: r=0.40, p<0.01; Protocol 2: r=0.26, p<0.05). From the decomposition, we obtained three key oscillations: IMF-Alpha, IMF-Beta, and the remaining residue. We also identified key spatial patterns associated with treatment outcomes for two rTMS protocols: for Protocol 1 (10Hz left DLPFC), important areas include the left frontal and parietal regions, while for Protocol 2 (1Hz right DLPFC), the left and frontal, left parietal regions are crucial. Additionally, our exploratory analysis found few significant correlations between oscillation specific predictive features and personality measures. This study highlights the potential of machine learning-driven EEG analysis for personalized MDD treatment prediction, offering a pathway for improved patient outcomes.

The effect of repetitive transcranial magnetic stimulation on the Hamilton Depression Rating Scale-17 criterion in patients with major depressive disorder without psychotic features: a systematic review and meta-analysis of intervention studies

AIM

In line with the publication of clinical information related to the therapeutic process of repetitive transcranial magnetic stimulation (rTMS) and the updating of relevant treatment guidelines, the present meta-analysis study was designed and conducted to determine the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features.

METHODS

In this study, a systematic search was conducted in electronic databases such as PubMed [Medline], Scopus, Web of Science, Embase, Ovid, Cochrane Library, and ClinicalTrials. gov using relevant keywords. The search period in this study was from January 2000 to January 2022, which was updated until May 2023. Randomized controlled trials (RCTs) that determined the effect of repetitive transcranial magnetic stimulation (rTMS) on the Hamilton Depression Rating Scale-17 (HDRS-17) criterion in patients with major depressive disorder (MDD) without psychotic features were included in the analysis. The quality of the included RCTs was assessed using the Cochrane Risk of Bias checklist. Statistical analyses were performed using STATA (Version 16) and RevMan (Version 5).

RESULTS

Following the combination of results from 16 clinical trial studies in the present meta-analysis, it was found that the mean Hamilton Depression Rating Scale-17 (HDRS-17) in patients with major depressive disorder (MDD) decreases by an average of 1.46 units (SMD: -1.46; % 95 CI: -1.65, -1.27, I square: 45.74%; P heterogeneity: 0.56). Subgroup analysis results indicated that the standardized mean difference of Hamilton Depression Rating Scale-17 (HDRS-17) varied based on the number of treatment sessions: patients receiving 10 or fewer repetitive transcranial magnetic stimulation (rTMS) sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 2.60 units (SMD: -2.60; % 95 CI: -2.86, -2.33, I square: 55.12%; P heterogeneity: 0.55), while those receiving 11 to 20 sessions showed a mean Hamilton Depression Rating Scale-17 (HDRS-17) reduction of 0.28 units (SMD: -0.28; % 95 CI: -0.65, -0.09, I square: 39.91%; P heterogeneity: 0.89).

CONCLUSION

In conclusion, our meta-analysis demonstrates the efficacy of repetitive transcranial magnetic stimulation (rTMS) in reducing depressive symptoms in major depressive disorder (MDD) patients. The complex results of subgroup analysis revealed insight on the possible benefits of a more focused strategy with fewer sessions, as well as the impact of treatment session frequency. These findings add to our understanding of repetitive transcranial magnetic stimulation (rTMS) as a therapeutic intervention for the treatment of major depressive illnesses.

Advances in Repetitive Transcranial Magnetic Stimulation for the Treatment of Post-traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that develops and persists after an individual experiences a major traumatic or life-threatening event. While pharmacological treatment and psychological interventions can alleviate some symptoms, pharmacotherapy is time-consuming with low patient compliance, and psychological interventions are costly. Repetitive Transcranial Magnetic Stimulation (rTMS) is a safe and effective technique for treating PTSD, with advantages such as high compliance, low cost, and simplicity of implementation. It can even simultaneously improve depressive symptoms in some patients. Current research indicates that high-frequency rTMS shows better therapeutic effects compared to low-frequency rTMS, with no significant difference in the likelihood of adverse reactions between the two. Theta Burst Stimulation (TBS) exhibits similar efficacy to high-frequency rTMS, with shorter duration and significant improvement in depressive symptoms. However, it carries a slightly higher risk of adverse reactions compared to traditional high-frequency rTMS. Combining rTMS with psychological therapy appears to be more effective in improving PTSD symptoms, with early onset of effects and longer duration, albeit at higher cost and requiring individualized patient control. The most common adverse effect of treatment is headache, which can be improved by stopping treatment or using analgesics. Despite these encouraging data, several aspects remain unknown. Given the highly heterogeneous nature of PTSD, defining unique treatment methods for this patient population is quite challenging. There are also considerable differences between trials regarding stimulation parameters, therapeutic effects, and the role of combined psychological therapy, which future research needs to address.

Beta: bursts of cognition

Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.

Frontoparietal beta event characteristics are associated with early life stress and psychiatric symptoms in adults

Recent work has found that the presence of transient, oscillatory burst-like events, particularly within the beta band (15-29 Hz), is more closely tied to disease state and behavior across species than traditional electroencephalography (EEG) power metrics. This study sought to examine whether features of beta events over frontoparietal electrodes were associated with early life stress (ELS) and the related clinical presentation. Eighteen adults with documented ELS (n = 18; ELS + ) and eighteen adults without documented ELS (n = 18; ELS-) completed eyes-closed resting state EEG as part of their participation in a larger childhood stress study. The rate, power, duration, and frequency span of transient oscillatory events were calculated within the beta band at five frontoparietal electrodes. ELS variables were positively associated with beta event rate at Fp2 and beta event duration at Pz, in that greater ELS was associated with higher resting rates and longer durations. These beta event characteristics were used to successfully distinguish between ELS + and ELS- groups. In an independent clinical dataset (n = 25), beta event power at Pz was positively correlated with ELS. Beta events deserve ongoing investigation as a potential disease marker of ELS and subsequent psychiatric treatment outcomes.

Bursting with Potential: How Sensorimotor Beta Bursts Develop from Infancy to Adulthood

Beta activity is thought to play a critical role in sensorimotor processes. However, little is known about how activity in this frequency band develops. Here, we investigated the developmental trajectory of sensorimotor beta activity from infancy to adulthood. We recorded EEG from 9-month-old, 12-month-old, and adult humans (male and female) while they observed and executed grasping movements. We analyzed "beta burst" activity using a novel method that combines time-frequency decomposition and principal component analysis. We then examined the changes in burst rate and waveform motifs along the selected principal components. Our results reveal systematic changes in beta activity during action execution across development. We found a decrease in beta burst rate during movement execution in all age groups, with the greatest decrease observed in adults. Additionally, we identified three principal components that defined waveform motifs that systematically changed throughout the trial. We found that bursts with waveform shapes closer to the median waveform were not rate-modulated, whereas those with waveform shapes further from the median were differentially rate-modulated. Interestingly, the decrease in the rate of certain burst motifs occurred earlier during movement and was more lateralized in adults than in infants, suggesting that the rate modulation of specific types of beta bursts becomes increasingly refined with age.SIGNIFICANCE STATEMENT We demonstrate that, like in adults, sensorimotor beta activity in infants during reaching and grasping movements occurs in bursts, not oscillations like thought traditionally. Furthermore, different beta waveform shapes were differentially modulated with age, including more lateralization in adults. Aberrant beta activity characterizes various developmental disorders and motor difficulties linked to early brain injury, so looking at burst waveform shape could provide more sensitivity for early identification and treatment of affected individuals before any behavioral symptoms emerge. More generally, comparison of beta burst activity in typical versus atypical motor development will also be instrumental in teasing apart the mechanistic functional roles of different types of beta bursts.

Pre-treatment frontal beta events are associated with executive dysfunction improvement after repetitive transcranial magnetic stimulation for depression: A preliminary report

Repetitive transcranial magnetic stimulation (rTMS) is an established clinical treatment for major depressive disorder (MDD) that has also been found to improve aspects of executive functioning. The objective of this study was to examine whether oscillatory burst-like events within the beta band (15-29 Hz) prior to treatment could predict subsequent change in self-reported executive dysfunction (EDF) across a clinical course of rTMS for MDD. Twenty-eight adults (64% female) with MDD completed the self-report Frontal Systems Behavior Scale (FrSBe) and provided eyes-closed resting-state electroencephalography (EEG) before and after a clinical course of rTMS therapy for primary MDD. The rate, power, duration, and frequency span of transient EEG measured oscillatory beta events were calculated. Events within delta/theta and alpha bands were examined to assess for beta specificity. After controlling for improvement in primary depressive symptoms, a lower rate of beta events at F3, Fz, F4, and Cz prior to rTMS treatment was associated with a larger improvement in EDF after rTMS treatment. In addition, a decrease in beta event rate at Fz pre-to-post treatment was associated with a larger improvement in EDF after treatment. Results were largely specific to the beta band. In this study, the rate of frontrocentral beta events prior to treatment significantly predicted the likelihood of subsequent improvement in EDF symptoms following a clinical course of rTMS for MDD. These preliminary findings suggest the potential utility of EEG measured beta events and rTMS for targeting EDF across an array of neuropsychiatric disorders.

A Study of Brain Function Characteristics of Service Members at High Risk for Accidents in the Military

Military accidents are often associated with stress and depressive psychological conditions among soldiers, and they often fail to adapt to military life. Therefore, this study analyzes whether there are differences in EEG and pulse wave indices between general soldiers and three groups of soldiers who have not adapted to military life and are at risk of accidents. Data collection was carried out using a questionnaire and a device that can measure EEG and pulse waves, and data analysis was performed using SPSS. The results showed that the concentration level and brain activity indices were higher in the general soldiers and the soldiers in the first stage of accident risk. The body stress index was higher for each stage of accident risk, and the physical vitality index was higher for general soldiers. Therefore, it can be seen that soldiers who have not adapted to military life and are at risk of accidents have somewhat lower concentration and brain activity than general soldiers, and have symptoms of stress and lethargy. The results of this study will contribute to reducing human accidents through EEG and pulse wave measurements not only in the military but also in occupations with a high risk of accidents such as construction.