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.

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder.

Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major depressive disorder (MDD), most studies to date have administered continuous or open-loop stimulation with promising but mixed results. One factor contributing to these mixed results may stem from when the stimulation is applied. Stimulation administration specific to high-symptom states in a personalized and responsive manner may be more effective at reducing symptoms compared to continuous stimulation and may avoid diminished therapeutic effects related to habituation. Additionally, a lower total duration of stimulation per day is advantageous for reducing device energy consumption. This protocol describes an experimental workflow using a chronically implanted neurostimulation device to achieve closed-loop stimulation for individuals with treatment-refractory MDD. This paradigm hinges on determining a patient-specific neural biomarker that is related to states of high symptoms and programming the device detectors, such that stimulation is triggered by this read-out of symptom state. The described procedures include how to obtain neural recordings concurrent with patient symptom reports, how to use these data in a state-space model approach to differentiate low- and high-symptom states and corresponding neural features, and how to subsequently program and tune the device to deliver closed-loop stimulation therapy.

Intracranial electrical stimulation of corticolimbic sites modulates arousal in humans.

BACKGROUND: Humans routinely shift their sleepiness and wakefulness levels in response to emotional factors. The diversity of emotional factors that modulates sleep-wake levels suggests that the ascending arousal network may be intimately linked with networks that mediate mood. Indeed, while animal studies have identified select limbic structures that play a role in sleep-wake regulation, the breadth of corticolimbic structures that directly modulates arousal in humans remains unknown. OBJECTIVE: We investigated whether select regional activation of the corticolimbic network through direct electrical stimulation can modulate sleep-wake levels in humans, as measured by subjective experience and behavior. METHODS: We performed intensive inpatient stimulation mapping in two human participants with treatment resistant depression, who underwent intracranial implantation with multi-site, bilateral depth electrodes. Stimulation responses of sleep-wake levels were measured by subjective surveys (i.e. Stanford Sleepiness Scale and visual-analog scale of energy) and a behavioral arousal score. Biomarker analyses of sleep-wake levels were performed by assessing spectral power features of resting-state electrophysiology. RESULTS: Our findings demonstrated three regions whereby direct stimulation modulated arousal, including the orbitofrontal cortex (OFC), subgenual cingulate (SGC), and, most robustly, ventral capsule (VC). Modulation of sleep-wake levels was frequency-specific: 100Hz OFC, SGC, and VC stimulation promoted wakefulness, whereas 1Hz OFC stimulation increased sleepiness. Sleep-wake levels were correlated with gamma activity across broad brain regions. CONCLUSIONS: Our findings provide evidence for the overlapping circuitry between arousal and mood regulation in humans. Furthermore, our findings open the door to new treatment targets and the consideration of therapeutic neurostimulation for sleep-wake disorders.

New and emerging approaches to treat psychiatric disorders.

Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact the lives of millions of people worldwide. Although their etiological and diagnostic heterogeneity has long challenged drug discovery, an emerging circuit-based understanding of psychiatric illness is offering an important alternative to the current reliance on trial and error, both in the development and in the clinical application of treatments. Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.

Corrigendum: Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies.

[This corrects the article DOI: 10.3389/fnhum.2021.644593.].

Closed-loop neuromodulation in an individual with treatment-resistant depression.

Deep brain stimulation is a promising treatment for neuropsychiatric conditions such as major depression. It could be optimized by identifying neural biomarkers that trigger therapy selectively when symptom severity is elevated. We developed an approach that first used multi-day intracranial electrophysiology and focal electrical stimulation to identify a personalized symptom-specific biomarker and a treatment location where stimulation improved symptoms. We then implanted a chronic deep brain sensing and stimulation device and implemented a biomarker-driven closed-loop therapy in an individual with depression. Closed-loop therapy resulted in a rapid and sustained improvement in depression. Future work is required to determine if the results and approach of this n-of-1 study generalize to a broader population.

Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies.

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer's disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.

State-dependent responses to intracranial brain stimulation in a patient with depression.

Deep brain stimulation is a promising treatment for severe depression, but lack of efficacy in randomized trials raises questions regarding anatomical targeting. We implanted multi-site intracranial electrodes in a severely depressed patient and systematically assessed the acute response to focal electrical neuromodulation. We found an elaborate repertoire of distinctive emotional responses that were rapid in onset, reproducible, and context and state dependent. Results provide proof of concept for personalized, circuit-specific medicine in psychiatry.

A Gaussian Process Model of Human Electrocorticographic Data.

We present a model-based method for inferring full-brain neural activity at millimeter-scale spatial resolutions and millisecond-scale temporal resolutions using standard human intracranial recordings. Our approach makes the simplifying assumptions that different people's brains exhibit similar correlational structure, and that activity and correlation patterns vary smoothly over space. One can then ask, for an arbitrary individual's brain: given recordings from a limited set of locations in that individual's brain, along with the observed spatial correlations learned from other people's recordings, how much can be inferred about ongoing activity at other locations throughout that individual's brain? We show that our approach generalizes across people and tasks, thereby providing a person- and task-general means of inferring high spatiotemporal resolution full-brain neural dynamics from standard low-density intracranial recordings.

Pilot Study of An Intracranial Electroencephalography Biomarker of Depressive Symptoms in Epilepsy.

OBJECTIVES: Adult patients with epilepsy have an increased prevalence of major depressive disorder (MDD). Intracranial EEG (iEEG) captured during extended inpatient monitoring of patients with treatment-resistant epilepsy offers a particularly promising method to study MDD networks in epilepsy. METHODS: The authors used 24 hours of resting-state iEEG to examine the neural activity patterns within corticolimbic structures that reflected the presence of depressive symptoms in 13 adults with medication-refractory epilepsy. Principal component analysis was performed on the z-scored mean relative power in five standard frequency bands averaged across electrodes within a region. RESULTS: Principal component 3 was a statistically significant predictor of the presence of depressive symptoms (R2=0.35, p=0.014). A balanced logistic classifier model using principal component 3 alone correctly classified 78% of patients as belonging to the group with a high burden of depressive symptoms or a control group with minimal depressive symptoms (sensitivity, 75%; specificity, 80%; area under the curve=0.8, leave-one-out cross validation). Classification was dependent on beta power throughout the corticolimbic network and low-frequency cingulate power. CONCLUSIONS: These finding suggest, for the first time, that neural features across circuits involved in epilepsy may distinguish patients who have depressive symptoms from those who do not. Larger studies are required to validate these findings and to assess their diagnostic utility in MDD.

An Electrophysiological Biomarker That May Predict Treatment Response to ECT.

OBJECTIVE: Electroconvulsive therapy (ECT) is the most effective treatment for major depression but also carries risk of cognitive side effects. The ability to predict whether treatment will be effective before initiation of treatment could significantly improve quality of care, reduce suffering, and diminish costs. We sought to carry out a comprehensive and definitive study of the relationship between the background electroencephalography (EEG) and therapeutic response to ECT. METHODS: Twenty-one channel resting EEG was collected pre-ECT and 2 to 3 days after ECT course from 2 separate data sets, one to develop an EEG model of therapeutic response (n = 30) and a second to test this model (n = 40). A 3-way principal components analysis was applied and coherence and spectral amplitude across 6 frequency bands were examined. The primary outcome measure was the Montgomery-Asberg Rating Scale (MADRS). RESULTS: Four patterns of amplitude and coherence along with baseline MADRS score accounted for 85% of the variance in posttreatment course MADRS score in study 1 (R = 0.85, F = 11.7, P < 0.0002) and 53% of the variance in MADRS score in study 2 (R = 0.53, F = 5.5, P < 0.003). Greater pre-ECT course anterior delta coherence accounted for the majority of variance in therapeutic response (study 1: R = 0.44, P = 0.01; study 2: R = 0.16, P = 0.008). CONCLUSIONS: These results suggest a putative electrophysiological biomarker that can predict therapeutic response before a course of ECT. Greater baseline anterior delta coherence is significantly associated with a better subsequent therapeutic response and could be indicative of intact circuitry allowing for improved seizure propagation.

Performance monitoring by presupplementary and supplementary motor area during an arm movement countermanding task.

A key component of executive control and decision making is the ability to use the consequences of chosen actions to update and inform the process of future action selection. Evaluative signals, which monitor the outcomes of actions, are critical for this ability. Signals related to the evaluation of actions have been identified in eye movement-related areas of the medial frontal cortex. Here we examined whether such evaluative signals are also present in areas of the medial frontal cortex related to arm movements. To answer this question, we recorded from cells in the supplementary motor area (SMA) and pre-SMA, while monkeys performed an arm movement version of the countermanding paradigm. SMA and pre-SMA have been implicated in the higher-order control of movement selection and execution, although their precise role within the skeletomotor control circuit is unclear. We found evaluative signals that encode information about the expected outcome of the reward, the actual outcome, and the mismatch between actual and intended outcome. These findings suggest that signals that monitor and evaluate movement outcomes are represented throughout the medial frontal cortex, playing a general role across effector systems. These evaluation signals supervise the relationship between intentional motor behavior and reward expectation and could be used to adaptively shape future goal-directed behavior.

Notch signaling is antagonized by SAO-1, a novel GYF-domain protein that interacts with the E3 ubiquitin ligase SEL-10 in Caenorhabditis elegans.

Notch signaling pathways can be regulated through a variety of cellular mechanisms, and genetically compromised systems provide useful platforms from which to search for the responsible modulators. The Caenorhabditis elegans gene aph-1 encodes a component of γ-secretase, which is essential for Notch signaling events throughout development. By looking for suppressors of the incompletely penetrant aph-1(zu147) mutation, we identify a new gene, sao-1 (suppressor of aph-one), that negatively regulates aph-1(zu147) activity in the early embryo. The sao-1 gene encodes a novel protein that contains a GYF protein-protein interaction domain and interacts specifically with SEL-10, an Fbw7 component of SCF E3 ubiquitin ligases. We demonstrate that the embryonic lethality of aph-1(zu147) mutants can be suppressed by removing sao-1 activity or by mutations that disrupt the SAO-1-SEL-10 protein interaction. Decreased sao-1 activity also influences Notch signaling events when they are compromised at different molecular steps of the pathway, such as at the level of the Notch receptor GLP-1 or the downstream transcription factor LAG-1. Combined analysis of the SAO-1-SEL-10 protein interaction and comparisons of sao-1 and sel-10 genetic interactions suggest a possible role for SAO-1 as an accessory protein that participates with SEL-10 in downregulation of Notch signaling. This work provides the first mutant analysis of a GYF-domain protein in either C. elegans or Drosophila and introduces a new type of Fbw7-interacting protein that acts in a subset of Fbw7 functions.