Deep Brain Stimulation in Treatment-Resistant Depression: A Systematic Review and Meta-Analysis on Efficacy and Safety

Spiking activities in small neural networks induced by external forcing

Neurons in an excitable mode do not show spiking activity and, therefore, do not contribute to information transfer transmission and its processing. However, some external influences, coupling, or time delay can lead to the appearance of oscillations in individual systems or networks. The main goal of this paper is to uncover the connection parameters and parameters of external influences that lead to the arising of spiking behavior in a small network of locally coupled FitzHugh-Nagumo oscillators. In this study, we analyze the dynamics of a small network in the absence and presence of several types of external influences. First, we consider the impact of periodic-pulse exposure generated as a periodic sequence of Gaussian pulses. Second, we show what behavior can be induced by far less regular pulsed influence (Lévy noise) and its special case called white Gaussian noise. For all types of influences, we have identified the appropriate parameters (local coupling strength, intensity, and frequency) that induce spiking activity in the small network.

Efficacy of Deep Brain Stimulation for Treatment-Resistant Depression: Systematic Review and Meta-Analysis

BACKGROUND

Treatment-resistant depression affects about 30% of individuals with major depressive disorder. Deep brain stimulation is an investigational intervention for treatment-resistant depression with varied results. We undertook this meta-analysis to synthesize outcome data across trial designs, anatomical targets, and institutions to better establish efficacy and side-effect profiles.

METHODS

We conducted a systematic PubMed review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Seven randomized controlled trials (n = 198) and 8 open-label trials (n = 77) were included spanning 2009 to 2020. Outcome measures included Hamilton Depression Rating Scale or Montgomery-Åsberg Depression Rating Scale scores, as well as response and remission rates over time. Outcomes were tracked at the last follow-up and quantified as a time course using model-based network meta-analysis. Linear mixed models were fit to individual patient data to identify covariates.

RESULTS

Deep brain stimulation achieved 47% improvement in long-term depression scale scores, with an estimated time to reach 50% improvement of around 23 months. There were no significant subgroup effects of stimulation target, time of last follow-up, sex, age of disease onset, or duration of disease, but open-label trials showed significantly greater treatment effects than randomized controlled trials. Long-term (12-60 month) response and remission rates were 48% and 35%, respectively. The time course of improvement with active stimulation could not be adequately distinguished from that with sham stimulation, when available.

CONCLUSIONS

Deep brain stimulation produces significant chronic improvement in symptoms of treatment-resistant depression. However, the limited sham-controlled data do not demonstrate significant improvement over placebo. Future advancements in stimulation optimization and careful blinding and placebo schemes are important next steps for this therapy.

Pain-Insomnia-Depression Syndrome: Triangular Relationships, Pathobiological Correlations, Current Treatment Modalities, and Future Direction

Pain-insomnia-depression syndrome (PIDS) is a complex triad of chronic pain, insomnia, and depression that has profound effects on an individual's quality of life and mental health. The pathobiological context of PIDS involves complex neurobiological and physiological mechanisms, including alterations in neurotransmitter systems and impaired pain processing pathways. The first-line therapeutic approaches for the treatment of chronic pain, depression, and insomnia are a combination of pharmacological and non-pharmacological therapies. In cases where patients do not respond adequately to these treatments, additional interventions such as deep brain stimulation (DBS) may be required. Despite advances in understanding and treatment, there are still gaps in knowledge that need to be addressed. To improve our understanding, future research should focus on conducting longitudinal studies to uncover temporal associations, identify biomarkers and genetic markers associated with PIDS, examine the influence of psychosocial factors on treatment responses, and develop innovative interventions that address the complex nature of PIDS. The aim of this study is to provide a comprehensive overview of these components and to discuss their underlying pathobiological relationships.

Rapid and long-lasting effects of subcutaneous esketamine on suicidality: An open-label study in patients with treatment-resistant depression

Therapeutics for suicide management is limited, taking weeks to work. This open-label clinical trial with 18 treatment-resistant depressive patients tested subcutaneous esketamine (8 weekly sessions) for suicidality. We noted a rapid and enduring effect of subcutaneous esketamine, lasting from one week to six months post-treatment, assessed by the Beck Inventory for Suicidality (BSI). There was an immediate drop in suicidality, 24 h following the initial dose, which persisted for seven days throughout the eight-week dosing period. Additionally, this study is the first to examine a six-month follow-up after multiple administrations of subcutaneous esketamine, finding consistently lower levels of suicidality throughout this duration. Conversely, suicidality also was measured along the 8-weeks of treatment by a psychiatrist using the Montgomery-Asberg Depression Rating Scale (MADRS), which showed significant reduction only after two treatment sessions expanding until the last session. Moreover, notably, 61% of patients achieved remission on suicidality (MADRS). These results suggest that weekly subcutaneous esketamine injections offer a cost-effective approach that induces a rapid and sustained response to anti-suicide treatment. This sets the stage for further, more controlled studies to corroborate our initial observations regarding the effects of SC esketamine on suicidality. Registered trial at: https://ensaiosclinicos.gov.br/rg/RBR-1072m6nv.

A silicon diode-based optoelectronic interface for bidirectional neural modulation

The development of advanced neural modulation techniques is crucial to neuroscience research and neuroengineering applications. Recently, optical-based, nongenetic modulation approaches have been actively investigated to remotely interrogate the nervous system with high precision. Here, we show that a thin-film, silicon (Si)-based diode device is capable to bidirectionally regulate in vitro and in vivo neural activities upon adjusted illumination. When exposed to high-power and short-pulsed light, the Si diode generates photothermal effects, evoking neuron depolarization and enhancing intracellular calcium dynamics. Conversely, low-power and long-pulsed light on the Si diode hyperpolarizes neurons and reduces calcium activities. Furthermore, the Si diode film mounted on the brain of living mice can activate or suppress cortical activities under varied irradiation conditions. The presented material and device strategies reveal an innovated optoelectronic interface for precise neural modulations.

Impact of pulse exposure on chimera state in ensemble of FitzHugh-Nagumo systems

In this article, we consider the influence of a periodic sequence of Gaussian pulses on a chimera state in a ring of coupled FitzHugh-Nagumo systems. We found that on the way to complete spatial synchronization, one can observe a number of variations of chimera states that are not typical for the parameter range under consideration. For example, the following modes were found: breathing chimera, chimera with intermittency in the incoherent part, traveling chimera with strong intermittency, and others. For comparison, here we also consider the impact of a harmonic influence on the same chimera, and to preserve the generality of the conclusions, we compare the regimes caused by both a purely positive harmonic influence and a positive-negative one.

Cost-effectiveness and threshold analysis of deep brain stimulation vs. treatment-as-usual for treatment-resistant depression

Treatment-resistant depression (TRD) affects approximately 2.8 million people in the U.S. with estimated annual healthcare costs of $43.8 billion. Deep brain stimulation (DBS) is currently an investigational intervention for TRD. We used a decision-analytic model to compare cost-effectiveness of DBS to treatment-as-usual (TAU) for TRD. Because this therapy is not FDA approved or in common use, our goal was to establish an effectiveness threshold that trials would need to demonstrate for this therapy to be cost-effective. Remission and complication rates were determined from review of relevant studies. We used published utility scores to reflect quality of life after treatment. Medicare reimbursement rates and health economics data were used to approximate costs. We performed Monte Carlo (MC) simulations and probabilistic sensitivity analyses to estimate incremental cost-effectiveness ratios (ICER; USD/quality-adjusted life year [QALY]) at a 5-year time horizon. Cost-effectiveness was defined using willingness-to-pay (WTP) thresholds of $100,000/QALY and $50,000/QALY for moderate and definitive cost-effectiveness, respectively. We included 274 patients across 16 studies from 2009-2021 who underwent DBS for TRD and had ≥12 months follow-up in our model inputs. From a healthcare sector perspective, DBS using non-rechargeable devices (DBS-pc) would require 55% and 85% remission, while DBS using rechargeable devices (DBS-rc) would require 11% and 19% remission for moderate and definitive cost-effectiveness, respectively. From a societal perspective, DBS-pc would require 35% and 46% remission, while DBS-rc would require 8% and 10% remission for moderate and definitive cost-effectiveness, respectively. DBS-pc will unlikely be cost-effective at any time horizon without transformative improvements in battery longevity. If remission rates ≥8-19% are achieved, DBS-rc will likely be more cost-effective than TAU for TRD, with further increasing cost-effectiveness beyond 5 years.

Deep Brain Stimulation of the Medial Forebrain Bundle for Treatment-Resistant Depression: A Systematic Review Focused on the Long-Term Antidepressive Effect

OBJECTIVE

Major depression affects millions of people worldwide and has important social and economic consequences. Since up to 30% of patients do not respond to several lines of antidepressive drugs, deep brain stimulation (DBS) has been evaluated for the management of treatment-resistant depression (TRD). The superolateral branch of the medial forebrain bundle (slMFB) appears as a "hypothesis-driven target" because of its role in the reward-seeking system, which is dysfunctional in depression. Although initial results of slMFB-DBS from open-label studies were promising and characterized by a rapid clinical response, long-term outcomes of neurostimulation for TRD deserve particular attention. Therefore, we performed a systematic review focused on the long-term outcome of slMFB-DBS.

MATERIALS AND METHODS

A literature search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria was conducted to identify all studies reporting changes in depression scores after one-year follow-up and beyond. Patient, disease, surgical, and outcome data were extracted for statistical analysis. The Montgomery-Åsberg Depression Rating Scale (ΔMADRS) was used as the clinical outcome, defined as percentage reduction from baseline to follow-up evaluation. Responders' and remitters' rates were also calculated.

RESULTS

From 56 studies screened for review, six studies comprising 34 patients met the inclusion criteria and were analyzed. After one year of active stimulation, ΔMADRS was 60.7% ± 4%; responders' and remitters' rates were 83.8% and 61.5%, respectively. At the last follow-up, four to five years after the implantation, ΔMADRS reached 74.7% ± 4.6%. The most common side effects were stimulation related and reversible with parameter adjustments.

CONCLUSIONS

slMFB-DBS appears to have a strong antidepressive effect that increases over the years. Nevertheless, to date, the overall number of patients receiving implantations is limited, and the slMFB-DBS surgical technique seems to have an important impact on the clinical outcome. Further multicentric studies in a larger population are needed to confirm slMFB-DBS clinical outcomes.

Novel Approaches Toward Studying Change: Implications for Understanding and Treating Psychopathology

In this article, the authors critically evaluate contemporary models of psychopathology and therapies, underscoring the limitations of traditional symptom-based classification approaches in mental health. The authors introduce a paradigm shift in the field, toward a process-oriented and dynamic systems approach to psychotherapy that offers deeper insights into the complex interplay of symptoms and individual experiences in psychopathology. These approaches offer a more personalized and effective understanding and treatment of mental health issues, moving beyond static and 1-dimensional views. The authors discuss the implications for clinical practice, emphasizing improved assessment, diagnosis, and tailored treatment strategies.

Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis

Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising prediction accuracies. This systematic review and meta-analysis evaluates these studies, considering their risk of bias through the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We examined the predictive performance of features derived from rs-FC, identified features with the highest predictive value, and assessed the employed machine learning pipelines. We searched the electronic databases Scopus, PubMed and PsycINFO on the 12th of December 2022, which resulted in 13 included studies. The mean balanced accuracy for predicting treatment outcome was 77% (95% CI: [72%- 83%]). rs-FC of the dorsolateral prefrontal cortex had high predictive value in most studies. However, a high risk of bias was identified in all studies, compromising interpretability. Methodological recommendations are provided based on a comprehensive exploration of the studies' machine learning pipelines, and potential fruitful developments are discussed.

Outcome differences between males and females undergoing deep brain stimulation for treatment-resistant depression: systematic review and individual patient data meta-analysis

BACKGROUND

Treatment-resistant depression (TRD) occurs more commonly in women. Deep brain stimulation (DBS) is an emerging treatment for TRD, and its efficacy continues to be explored. However, differences in treatment outcomes between males and females have yet to be explored in formal analysis.

METHODS

A PRISMA-compliant systematic review of DBS for TRD studies was conducted. Patient-level data were independently extracted by two authors. Treatment response was defined as a 50 % or greater reduction in depression score. Percent change in depression scores by gender were evaluated using random-effects analyses.

RESULTS

Of 737 records, 19 studies (129 patients) met inclusion criteria. The mean reduction in depression score for females was 57.7 % (95 % CI, 64.33 %-51.13 %), whereas for males it was 35.2 % (95 % CI, 45.12 %-25.23 %) (p < 0.0001). Females were more likely to respond to DBS for TRD when compared to males (OR = 2.44, 95 % CI 1.06, 1.95). These differences varied in significance when stratified by DBS anatomical target, age, and timeframe for responder classification.

LIMITATIONS

Studies included were open-label trials with small sample sizes.

CONCLUSIONS

Our findings suggest that females with TRD respond at higher rates to DBS treatment than males. Further research is needed to elucidate the implications of these results, which may include connectomic sexual dimorphism, depression phenotype variations, or unrecognized symptom reporting differences. Methodological standardization of outcome scales, granular demographic data, and individual subject outcomes would allow for more robust comparisons between trials.

Deep brain stimulation for refractory major depressive disorder: a comprehensive review

Deep brain stimulation (DBS) has emerged as a promising treatment for select patients with refractory major depressive disorder (MDD). The clinical effectiveness of DBS for MDD has been demonstrated in meta-analyses, open-label studies, and a few controlled studies. However, randomized controlled trials have yielded mixed outcomes, highlighting challenges that must be addressed prior to widespread adoption of DBS for MDD. These challenges include tracking MDD symptoms objectively to evaluate the clinical effectiveness of DBS with sensitivity and specificity, identifying the patient population that is most likely to benefit from DBS, selecting the optimal patient-specific surgical target and stimulation parameters, and understanding the mechanisms underpinning the therapeutic benefits of DBS in the context of MDD pathophysiology. In this review, we provide an overview of the latest clinical evidence of MDD DBS effectiveness and the recent technological advancements that could transform our understanding of MDD pathophysiology, improve the clinical outcomes for MDD DBS, and establish a path forward to develop more effective neuromodulation therapies to alleviate depressive symptoms.

Alternative metrics for characterizing longer-term clinical outcomes in difficult-to-treat depression: II. Sensitivity to treatment effects

OBJECTIVE

Characteristics of difficult-to-treat depression (DTD), including infrequent symptom remission and poor durability of benefit, compel reconsideration of the outcome metrics historically used to gauge the effectiveness of antidepressant interventions.

METHODS

Self-report and clinician assessments of depression symptom severity were obtained regularly over a 2-year period in a difficult-to-treat depression registry sample receiving treatment as usual (TAU), with or without vagus nerve stimulation (VNS). Alternative outcome metrics for characterizing symptom change were compared in effect size and discriminating power in distinguishing the vagus nerve stimulation + treatment as usual and treatment as usual treatment groups. We expected metrics based on remission status to produce weaker between-group separation than those based on the classifications of partial response or response and metrics that integrate information over time to produce greater separation than those based on single endpoint assessment.

RESULTS

Metrics based on remission status had smaller effect size and poorer discrimination in separating the treatment groups than metrics based on partial response or response classifications. Metrics that integrated information over the 2-year observation period had stronger performance characteristics than those based on symptom scores at single endpoint assessment. For both the clinician-rated and self-report depression ratings, the metrics with the strongest performance characteristics were the median percentage change in symptom scores over the observation period and the proportion of the observation period in partial response or better.

CONCLUSION

In difficult-to-treat depression, integrative symptom severity-based and time-based measures are sensitive and informative outcomes for assessing between-group treatment effects, while metrics based on remission status are not.

Characterization and closed-loop control of infrared thalamocortical stimulation produces spatially constrained single-unit responses

Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson's disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to midinfrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in rat thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning (RL) for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS.

Brain-derived neurotrophic factor/tropomyosin receptor kinase B signaling in spinal muscular atrophy and amyotrophic lateral sclerosis

Tropomyosin receptor kinase B (TrkB) and its primary ligand brain-derived neurotrophic factor (BDNF) are expressed in the neuromuscular system, where they affect neuronal survival, differentiation, and functions. Changes in BDNF levels and full-length TrkB (TrkB-FL) signaling have been revealed in spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS), two common forms of motor neuron diseases that are characterized by defective neuromuscular junctions in early disease stages and subsequently progressive muscle weakness. This review summarizes the current understanding of BDNF/TrkB-FL-related research in SMA and ALS, with an emphasis on their alterations in the neuromuscular system and possible BDNF/TrkB-FL-targeting therapeutic strategies. The limitations of current studies and future directions are also discussed, giving the hope of discovering novel and effective treatments.

Deep Brain Stimulation (DBS) in Treatment-Resistant Depression (TRD): Hope and Concern

In this chapter, we explore the historical evolution, current applications, and future directions of Deep Brain Stimulation (DBS) for Treatment-Resistant Depression (TRD). We begin by highlighting the early efforts of neurologists and neurosurgeons who laid the foundations for today's DBS techniques, moving from controversial lobotomies to the precision of stereotactic surgery. We focus on the advent of DBS, emphasizing its emergence as a significant breakthrough for movement disorders and its extension to psychiatric conditions, including TRD. We provide an overview of the neural networks implicated in depression, detailing the rationale for the choice of common DBS targets. We also cover the technical aspects of DBS, from electrode placement to programming and parameter selection. We then critically review the evidence from clinical trials and open-label studies, acknowledging the mixed outcomes and the challenges posed by placebo effects and trial design. Safety and ethical considerations are also discussed. Finally, we explore innovative directions for DBS research, including the potential of closed-loop systems, dual stimulation strategies, and noninvasive alternatives like ultrasound neuromodulation. In the last section, we outline recommendations for future DBS studies, including the use of alternative designs for placebo control, the collection of neural and behavioral recordings, and the application of machine-learning approaches.

Monitoring time domain characteristics of Parkinson's disease using 3D memristive neuromorphic system

Introduction

Parkinson's disease (PD) is a neurodegenerative disorder affecting millions of patients. Closed-Loop Deep Brain Stimulation (CL-DBS) is a therapy that can alleviate the symptoms of PD. The CL-DBS system consists of an electrode sending electrical stimulation signals to a specific region of the brain and a battery-powered stimulator implanted in the chest. The electrical stimuli in CL-DBS systems need to be adjusted in real-time in accordance with the state of PD symptoms. Therefore, fast and precise monitoring of PD symptoms is a critical function for CL-DBS systems. However, the current CL-DBS techniques suffer from high computational demands for real-time PD symptom monitoring, which are not feasible for implanted and wearable medical devices.

Methods

In this paper, we present an energy-efficient neuromorphic PD symptom detector using memristive three-dimensional integrated circuits (3D-ICs). The excessive oscillation at beta frequencies (13-35 Hz) at the subthalamic nucleus (STN) is used as a biomarker of PD symptoms.

Results

Simulation results demonstrate that our neuromorphic PD detector, implemented with an 8-layer spiking Long Short-Term Memory (S-LSTM), excels in recognizing PD symptoms, achieving a training accuracy of 99.74% and a validation accuracy of 99.52% for a 75%-25% data split. Furthermore, we evaluated the improvement of our neuromorphic CL-DBS detector using NeuroSIM. The chip area, latency, energy, and power consumption of our CL-DBS detector were reduced by 47.4%, 66.63%, 65.6%, and 67.5%, respectively, for monolithic 3D-ICs. Similarly, for heterogeneous 3D-ICs, employing memristive synapses to replace traditional Static Random Access Memory (SRAM) resulted in reductions of 44.8%, 64.75%, 65.28%, and 67.7% in chip area, latency, and power usage.

Discussion

This study introduces a novel approach for PD symptom evaluation by directly utilizing spiking signals from neural activities in the time domain. This method significantly reduces the time and energy required for signal conversion compared to traditional frequency domain approaches. The study pioneers the use of neuromorphic computing and memristors in designing CL-DBS systems, surpassing SRAM-based designs in chip design area, latency, and energy efficiency. Lastly, the proposed neuromorphic PD detector demonstrates high resilience to timing variations in brain neural signals, as confirmed by robustness analysis.

Biomarkers predict the efficacy of closed-loop rTMS treatment for refractory depression

Transcranial magnetic stimulation (TMS) is a non-invasive FDA-approved therapy for major depressive disorder (MDD), specifically for treatment-resistant depression (TRD). Though offering promise for those with TRD, its effectiveness is less than one in two patients (i.e., less than 50%). Limits on efficacy may be due to individual patient variability, but to date, there are no established biomarkers or measures of target engagement that can predict efficacy. Additionally, TMS efficacy is typically not assessed until a six-week treatment ends, precluding interim re-evaluations of the treatment. Here, we report results using a closed-loop phase-locked repetitive TMS (rTMS) treatment that synchronizes the delivery of rTMS based on the timing of the pulses relative to a patient's individual electroencephalographic (EEG) prefrontal alpha oscillation indexed by functional magnetic resonance imaging (fMRI). Among responders, synchronized rTMS produces two systematic changes in brain dynamics: a reduction in global cortical excitability and enhanced phase entrainment of cortical dynamics. These effects predict clinical outcomes in the synchronized treatment group but not in an active-treatment unsynchronized control group. The systematic decrease in excitability and increase in entrainment correlated with treatment efficacy at the endpoint and intermediate weeks during the synchronized treatment. Specifically, we show that weekly biomarker tracking enables efficacy prediction and dynamic adjustments through a treatment course, improving the overall response rates. This innovative approach advances the prospects of individualized medicine in MDD and holds potential for application in other neuropsychiatric disorders.

Spatially specific, closed-loop infrared thalamocortical deep brain stimulation

Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson's disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically-mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to mid-infrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm. INS has been shown to provide spatially constrained responses in cortical neurons and, unlike other optical techniques, does not require genetic modification of the neural target. We show that INS produces graded, biophysically relevant single-unit responses with robust information transfer in thalamocortical circuits. Importantly, we show that cortical spread of activation from thalamic INS produces more spatially constrained response profiles than conventional electrical stimulation. Owing to observed spatial precision of INS, we used deep reinforcement learning for closed-loop control of thalamocortical circuits, creating real-time representations of stimulus-response dynamics while driving cortical neurons to precise firing patterns. Our data suggest that INS can serve as a targeted and dynamic stimulation paradigm for both open and closed-loop DBS.

Increased entrainment and decreased excitability predict efficacious treatment of closed-loop phase-locked rTMS for treatment-resistant depression

Transcranial magnetic stimulation (TMS) is an FDA-approved therapy for major depressive disorder (MDD), specifically for patients who have treatment-resistant depression (TRD). However, TMS produces response or remission in about 50% of patients but is ineffective for the other 50%. Limits on efficacy may be due to individual patient variability, but to date, there are no good biomarkers or measures of target engagement. In addition, TMS efficacy is typically not assessed until a six-week treatment ends, precluding the evaluation of intermediate improvements during the treatment duration. Here, we report on results using a closed-loop phase-locked repetitive TMS (rTMS) treatment that synchronizes the delivery of rTMS based on the timing of the pulses relative to a patient's individual electroencephalographic (EEG) prefrontal alpha oscillation informed by functional magnetic resonance imaging (fMRI). We find that, in responders, synchronized delivery of rTMS produces two systematic changes in brain dynamics. The first change is a decrease in global cortical excitability, and the second is an increase in the phase entrainment of cortical dynamics. These two effects predict clinical outcomes in the synchronized treatment group but not in an active-treatment unsynchronized control group. The systematic decrease in excitability and increase in entrainment correlated with treatment efficacy at the endpoint and intermediate weeks during the synchronized treatment. Specifically, we show that weekly tracking of these biomarkers allows for efficacy prediction and potential of dynamic adjustments through a treatment course, improving the overall response rates.

Functional connectomics in depression: insights into therapies

Depression is a common mental disorder characterized by heterogeneous cognitive and behavioral symptoms. The emerging research paradigm of functional connectomics has provided a quantitative theoretical framework and analytic tools for parsing variations in the organization and function of brain networks in depression. In this review, we first discuss recent progress in depression-associated functional connectome variations. We then discuss treatment-specific brain network outcomes in depression and propose a hypothetical model highlighting the advantages and uniqueness of each treatment in relation to the modulation of specific brain network connectivity and symptoms of depression. Finally, we look to the future promise of combining multiple treatment types in clinical practice, using multisite datasets and multimodal neuroimaging approaches, and identifying biological depression subtypes.

Formalizing psychological interventions through network control theory

Despite the growing deployment of network representation to comprehend psychological phenomena, the question of whether and how networks can effectively describe the effects of psychological interventions remains elusive. Network control theory, the engineering study of networked interventions, has recently emerged as a viable methodology to characterize and guide interventions. However, there is a scarcity of empirical studies testing the extent to which it can be useful within a psychological context. In this paper, we investigate a representative psychological intervention experiment, use network control theory to model the intervention and predict its effect. Using this data, we showed that: (1) the observed psychological effect, in terms of sensitivity and specificity, relates to the regional network control theoretic metrics (average and modal controllability), (2) the size of change following intervention negatively correlates with a whole-network topology that quantifies the "ease" of change as described by control theory (control energy), and (3) responses after intervention can be predicted based on formal results from control theory. These insights assert that network control theory has significant potential as a tool for investigating psychological interventions. Drawing on this specific example and the overarching framework of network control theory, we further elaborate on the conceptualization of psychological interventions, methodological considerations, and future directions in this burgeoning field.

Surgical treatment methods in the course of psychiatric disorders: Deep brain stimulation-Novel insights and indications

Deep brain stimulation (DBS) is a relatively dated treatment procedure that emerged in the late 1980s. Nonetheless, numerous studies are being carried out to examine its influence on the human brain and develop new treatment indications. This systematic review aims to summarize the current state of knowledge referring to DBS, investigate novel insights into its indications, and discuss the technical aspects and rationale behind DBS application. In particular, we sought to subject to scrutiny the application of DBS specifically in anorexia nervosa (AN), various addiction types, depression, and obsessive-compulsive disorders (OCDs). The method is supposed to offer promising results, especially in pharmacologically resistant forms of the upper-mentioned psychiatric disorders. Moreover, further insight has been provided into the historical notions of the method and differences in the surgical approach in specific disease entities. Furthermore, we mark the possible influence of comorbidities on treatment results. Our review consists of articles and studies found on PubMed, Google Scholar, Cochrane, and Scopus, which were then analyzed with scrutiny in the identification process, including the most resourceful ones. After methodological quality and risk of bias assessment, a total of 53 studies were included. To this date, DBS's usefulness in the treatment of AN, OCDs, depression, and addictions has been proven, despite an ongoing debate concerning the technical aspects and parameters when applying DBS. To the best of our knowledge, we have not found any paper that would recapitulate the current state of DBS in the context of psychiatric disorders with an addition of technical insights.

Development of Korea Neuroethics Guidelines

BACKGROUND

Advances in neuroscience and neurotechnology provide great benefits to humans though unknown challenges may arise. We should address these challenges using new standards as well as existing ones. Novel standards should include ethical, legal, and social aspects which would be appropriate for advancing neuroscience and technology. Therefore, the Korea Neuroethics Guidelines were developed by stakeholders related to neuroscience and neurotechnology, including experts, policy makers, and the public in the Republic of Korea.

METHOD

The guidelines were drafted by neuroethics experts, were disclosed at a public hearing, and were subsequently revised by opinions of various stakeholders.

RESULTS

The guidelines are composed of twelve issues; humanity or human dignity, individual personality and identity, social justice, safety, sociocultural prejudice and public communication, misuse of technology, responsibility for the use of neuroscience and technology, specificity according to the purpose of using neurotechnology, autonomy, privacy and personal information, research, and enhancement.

CONCLUSION

Although the guidelines may require a more detailed discussion after future advances in neuroscience and technology or changes in socio-cultural milieu, the development of the Korea Neuroethics Guidelines is a milestone for the scientific community and society in general for the ongoing development in neuroscience and neurotechnology.

Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles: Pandora's Box Has Been Opened

BACKGROUND

Artificial intelligence (AI) has advanced substantially in recent years, transforming many industries and improving the way people live and work. In scientific research, AI can enhance the quality and efficiency of data analysis and publication. However, AI has also opened up the possibility of generating high-quality fraudulent papers that are difficult to detect, raising important questions about the integrity of scientific research and the trustworthiness of published papers.

OBJECTIVE

The aim of this study was to investigate the capabilities of current AI language models in generating high-quality fraudulent medical articles. We hypothesized that modern AI models can create highly convincing fraudulent papers that can easily deceive readers and even experienced researchers.

METHODS

This proof-of-concept study used ChatGPT (Chat Generative Pre-trained Transformer) powered by the GPT-3 (Generative Pre-trained Transformer 3) language model to generate a fraudulent scientific article related to neurosurgery. GPT-3 is a large language model developed by OpenAI that uses deep learning algorithms to generate human-like text in response to prompts given by users. The model was trained on a massive corpus of text from the internet and is capable of generating high-quality text in a variety of languages and on various topics. The authors posed questions and prompts to the model and refined them iteratively as the model generated the responses. The goal was to create a completely fabricated article including the abstract, introduction, material and methods, discussion, references, charts, etc. Once the article was generated, it was reviewed for accuracy and coherence by experts in the fields of neurosurgery, psychiatry, and statistics and compared to existing similar articles.

RESULTS

The study found that the AI language model can create a highly convincing fraudulent article that resembled a genuine scientific paper in terms of word usage, sentence structure, and overall composition. The AI-generated article included standard sections such as introduction, material and methods, results, and discussion, as well a data sheet. It consisted of 1992 words and 17 citations, and the whole process of article creation took approximately 1 hour without any special training of the human user. However, there were some concerns and specific mistakes identified in the generated article, specifically in the references.

CONCLUSIONS

The study demonstrates the potential of current AI language models to generate completely fabricated scientific articles. Although the papers look sophisticated and seemingly flawless, expert readers may identify semantic inaccuracies and errors upon closer inspection. We highlight the need for increased vigilance and better detection methods to combat the potential misuse of AI in scientific research. At the same time, it is important to recognize the potential benefits of using AI language models in genuine scientific writing and research, such as manuscript preparation and language editing.

The Role of Family Members in Psychiatric Deep Brain Stimulation Trials: More Than Psychosocial Support

Family members can provide crucial support to individuals participating in clinical trials. In research on the "newest frontier" of Deep Brain Stimulation (DBS)-the use of DBS for psychiatric conditions-family member support is frequently listed as a criterion for trial enrollment. Despite the significance of family members, qualitative ethics research on DBS for psychiatric conditions has focused almost exclusively on the perspectives and experiences of DBS recipients. This qualitative study is one of the first to include both DBS recipients and their family members as interview participants. Using dyadic thematic analysis-an approach that takes both the individuals and the relationship as units of analyses-this study analyzes the complex ways in which family relationships can affect DBS trial participation, and how DBS trial participation in turn influences family relationships. Based on these findings, we propose ways to improve study designs to better take family relationships into account, and better support family members in taking on the complex, essential roles that they play in DBS trials for psychiatric conditions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12152-023-09520-7.

Depression roundtable: Is there a role for BoNT?

Depression can occur in the context of major depressive disorder or bipolar disorder. There are many effective and well-tolerated treatment options for most patients experiencing major depressive episodes, but for patients with treatment-resistant major depressive disorder or bipolar depression, current pharmacologic and non-pharmacologic options can be less efficacious, well tolerated, or accessible. Botulinum neurotoxin (BoNT) offers a novel approach to treating depression that is both safe and well-tolerated. Several potential mechanisms of action in depression are theorized, and studies support the efficacy of BoNT in major depression. Early data suggests that BoNT may be efficacious in bipolar depression and further study is warranted.

Treatment resistant depression in elderly

Treatment refractory depression (TRD) in the elderly is a common psychiatric disorder with high comorbidity and mortality. Older adults with TRD often have complicated comorbidities and several predisposing risk factors, which may lead to neuropsychiatric dysfunction and poor response to treatment. Several hypotheses suggest the underlying mechanisms, including vascular, immunological, senescence, or abnormal protein deposition. Treatment strategies for TRD include optimization of current medication dose, augmentation, switching to an alternative agent or class, and combination of different antidepressant classes, as well as nonpharmacological adjuvant interventions such as biophysical stimulation and psychotherapy. In summary, treatment recommendations for TRD in the elderly favor a multimodal approach, combining pharmacological and nonpharmacological treatments.

The Wistar Kyoto Rat: A Model of Depression Traits

There is an ongoing debate about the value of animal research in psychiatry with valid lines of reasoning stating the limits of individual animal models compared to human psychiatric illnesses. Human depression is not a homogenous disorder; therefore, one cannot expect a single animal model to reflect depression heterogeneity. This limited review presents arguments that the Wistar Kyoto (WKY) rats show intrinsic depression traits. The phenotypes of WKY do not completely mirror those of human depression but clearly indicate characteristics that are common with it. WKYs present despair- like behavior, passive coping with stress, comorbid anxiety, and enhanced drug use compared to other routinely used inbred or outbred strains of rats. The commonly used tests identifying these phenotypes reflect exploratory, escape-oriented, and withdrawal-like behaviors. The WKYs consistently choose withdrawal or avoidance in novel environments and freezing behaviors in response to a challenge in these tests. The physiological response to a stressful environment is exaggerated in WKYs. Selective breeding generated two WKY substrains that are nearly isogenic but show clear behavioral differences, including that of depression-like behavior. WKY and its substrains may share characteristics of subgroups of depressed individuals with social withdrawal, low energy, weight loss, sleep disturbances, and specific cognitive dysfunction. The genomes of the WKY and WKY substrains contain variations that impact the function of many genes identified in recent human genetic studies of depression. Thus, these strains of rats share characteristics of human depression at both phenotypic and genetic levels, making them a model of depression traits.

Therapeutic potential of brain stimulation techniques in the treatment of mental, psychiatric, and cognitive disorders

Treatment for brain diseases has been disappointing because available medications have failed to produce clinical response across all the patients. Many patients either do not respond or show partial and inconsistent effect, and even in patients who respond to the medications have high relapse rates. Brain stimulation has been seen as an alternative and effective remedy. As a result, brain stimulation has become one of the most valuable therapeutic tools for combating against brain diseases. In last decade, studies with the application of brain stimulation techniques not only have grown exponentially but also have expanded to wide range of brain disorders. Brain stimulation involves passing electric currents into the cortical and subcortical area brain cells with the use of noninvasive as well as invasive methods to amend brain functions. Over time, technological advancements have evolved into the development of precise devices; however, at present, most used noninvasive techniques are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS), whereas the most common invasive technique is deep brain stimulation (DBS). In the current review, we will provide an overview of the potential of noninvasive (rTMS and tDCS) and invasive (DBS) brain stimulation techniques focusing on the treatment of mental, psychiatric, and cognitive disorders.

Efficacy and Safety of Electroconvulsive Therapy in Patients With Deep Brain Stimulation: Literature Review, Case Report for Patient With Essential Tremor, and Practical Recommendations

AIM

Deep brain stimulation (DBS) has proven to be an effective therapy of some treatment-resistant psychiatric disorders and movement disorders. Comorbid depressive symptoms are common and difficult to manage. Treatment with electroconvulsive therapy (ECT) may be required. There are few published cases describing the safety and efficacy of ECT for patients with DBS implants, and there are no available guidelines for administration of ECT in patients with DBS and mood disorders. The current study had 3 aims: (i) to conduct a systematic review of case reports on patients with DBS implants who received ECT; (ii) to report the case of a 69-year-old man with a DBS implant for essential tremor, who required ECT; and (iii) to provide practical recommendations for ECT in patients with DBS implants.

METHODS

We conducted a systematic review, in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, of existing case reports on patients with DBS implants administered ECT for psychiatric disorders.

RESULTS

Our search yielded 25 cases of ECT in patients implanted with DBS systems. In addition, we here describe successful ECT management of major depressive disorder in a patient treated by DBS. We also set forth ECT management guidelines based on points of consensus. The 2 most important practical recommendations are to make sure the DBS system is set to 0 V and turned off before ECT, and to avoid sites near the DBS electrodes.

CONCLUSIONS

Electroconvulsive therapy may be an effective and safe treatment for DBS patients with MDD.

Neuromodulation Treatments of Pathological Anxiety in Anxiety Disorders, Stressor-Related Disorders, and Major Depressive Disorder: A Dimensional Systematic Review and Meta-Analysis

Background

Pathological anxiety is responsible for major functional impairments and resistance to conventional treatments in anxiety disorders (ADs), posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Focal neuromodulation therapies such as transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) are being developed to treat those disorders.

Methods

We performed a dimensional systematic review and meta-analysis to assess the evidence of the efficacy of TMS, tDCS and DBS in reducing anxiety symptoms across ADs, PTSD and MDD. Reports were identified through systematic searches in PubMed/Medline, Scopus and Cochrane library (inception to November 2020), followed by review according to the PRISMA guidelines. Controlled clinical trials examining the effectiveness of brain stimulation techniques on generic anxiety symptoms in patients with ADs, PTSD or MDD were selected.

Results

Nineteen studies (RCTs) met inclusion criteria, which included 589 participants. Overall, focal brain activity modulation interventions were associated with greater reduction of anxiety levels than controls [SMD: -0.56 (95% CI, -0.93 to-0.20, I 2 = 77%]. Subgroup analyses revealed positive effects for TMS across disorders, and of focal neuromodulation in generalized anxiety disorder and PTSD. Rates of clinical responses and remission were higher in the active conditions. However, the risk of bias was high in most studies.

Conclusions

There is moderate quality evidence for the efficacy of neuromodulation in treating pathological anxiety.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=233084, identifier: PROSPERO CRD42021233084. It was submitted on January 29th, 2021, and registered on March 1st, 2021. No amendment was made to the recorded protocol. A change was applied for the subgroup analyses based on target brain regions, we added the putative nature (excitatory/inhibitory) of brain activity modulation.

Brain stimulation and other biological non-pharmacological interventions in mental disorders: An umbrella review

BACKGROUND

The degree of efficacy, safety, quality, and certainty of meta-analytic evidence of biological non-pharmacological treatments in mental disorders is unclear.

METHODS

We conducted an umbrella review (PubMed/Cochrane Library/PsycINFO-04-Jul-2021, PROSPERO/CRD42020158827) for meta-analyses of randomized controlled trials (RCTs) on deep brain stimulation (DBS), transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), electro-convulsive therapy (ECT), and others. Co-primary outcomes were standardized mean differences (SMD) of disease-specific symptoms, and acceptability (for all-cause discontinuation). Evidence was assessed with AMSTAR/AMSTAR-Content/GRADE.

RESULTS

We selected 102 meta-analyses. Effective interventions compared to sham were in depressive disorders: ECT (SMD=0.91/GRADE=moderate), TMS (SMD=0.51/GRADE=moderate), tDCS (SMD=0.46/GRADE=low), DBS (SMD=0.42/GRADE=very low), light therapy (SMD=0.41/GRADE=low); schizophrenia: ECT (SMD=0.88/GRADE=moderate), tDCS (SMD=0.45/GRADE=very low), TMS (prefrontal theta-burst, SMD=0.58/GRADE=low; left-temporoparietal, SMD=0.42/GRADE=low); substance use disorder: TMS (high frequency-dorsolateral-prefrontal-deep (SMD=1.16/GRADE=moderate), high frequency-left dorsolateral-prefrontal (SMD=0.77/GRADE=very low); OCD: DBS (SMD=0.89/GRADE=moderate), TMS (SMD=0.64/GRADE=very low); PTSD: TMS (SMD=0.46/GRADE=moderate); generalized anxiety disorder: TMS (SMD=0.68/GRADE=low); ADHD: tDCS (SMD=0.23/GRADE=moderate); autism: tDCS (SMD=0.97/GRADE=very low). No significant differences for acceptability emerged. Median AMSTAR/AMSTAR-Content was 8/2 (suggesting high-quality meta-analyses/low-quality RCTs), GRADE low.

DISCUSSION

Despite limited certainty, biological non-pharmacological interventions are effective and safe for numerous mental conditions. Results inform future research, and guidelines.

FUNDING

None.

Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury

DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.