Deep Brain Stimulation for Treatment-Resistant Psychiatric Illnesses: What Has Gone Wrong and What Should We Do Next?

Utilising activity patterns of a complex biophysical network model to optimise intra-striatal deep brain stimulation

A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin-Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies.

Closed-loop neurostimulation for the treatment of psychiatric disorders

Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.

Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity

Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.

Phenomenological Changes Associated with Deep Brain Stimulation for Obsessive Compulsive Disorder: A Cognitive Appraisal Model of Recovery

The current scientific enquiry of deep brain stimulation (DBS) does not capture the breadth of DBS-induced changes to an individual's life. Considering that DBS is applied in severe and complex cases, it is ethically and clinically necessary to consider the patient perspective and personally relevant outcomes. This lived experience investigation of people with obsessive compulsive disorder (OCD) undergoing DBS aims to provide a comprehensive evaluation of DBS-induced effects associated with OCD psychopathology. Six patients and six carers completed semi-structured open-ended interviews. A blended approach of interpretative phenomenological, inductive, and thematic analysis techniques was employed. Profound psychopathological changes were expressed; individuals felt more alive, had improved cognitive affective control, greater engagement in the world, and were able to manage their OCD. Through suppression of the condition, self-constructs were able to re-emerge and develop. A framework describing the progression of phenomenological changes, and a theoretical model describing changes in the cognitive appraisal of intrusions influencing recovery are proposed. This is the first identified qualitative investigation of DBS-induced changes in psychiatric patients and carers. Findings have implications for patient education and recovery models of OCD, and scientific understanding of DBS effects.

Pros and Cons of Ablation for Functional Neurosurgery in the Neurostimulation Age

Should one recommend stereotactic ablation for Parkinson disease, tremor, dystonia, and obsessive compulsive disorder, in this era of DBS? The answer depends on several variables such as the symptoms to treat, the patient's preferences and expectations, the surgeons' competence and preference, the availability of financial means (by government health care, by private insurance), the geographical issues, and not least the current and dominating fashion at that particular time. Both ablation and stimulation can be either used alone or even combined (provided expertise in both of them) to treat various symptoms of movement and mind disorders.

Patient, Caregiver, and Decliner Perspectives on Whether to Enroll in Adaptive Deep Brain Stimulation Research

This research study provides patient and caregiver perspectives as to whether or not to undergo adaptive deep brain stimulation (aDBS) research. A total of 51 interviews were conducted in a multi-site study including patients undergoing aDBS and their respective caregivers along with persons declining aDBS. Reasons highlighted for undergoing aDBS included hopes for symptom alleviation, declining quality of life, desirability of being in research, and altruism. The primary reasons for not undergoing aDBS issues were practical rather than specific to aDBS technology, although some persons highlighted a desire to not be the first to trial the new technology. These themes are discussed in the context of "push" factors wherein any form of surgical intervention is preferable to none and "pull" factors wherein opportunities to contribute to science combine with hopes and/or expectations for the alleviation of symptoms. We highlight the significance of study design in decision making. aDBS is an innovative technology and not a completely new technology. Many participants expressed value in being part of research as an important consideration. We suggest that there are important implications when comparing patient perspectives vs. theoretical perspectives on the choice for or against aDBS. Additionally, it will be important how we communicate with patients especially in reference to the complexity of study design. Ultimately, this study reveals that there are benefits and potential risks when choosing a research study that involves implantation of a medical device.

Deep brain stimulation for psychiatric disorders: role of imaging in identifying/confirming DBS targets, predicting, and optimizing outcome and unravelling mechanisms of action

Following the established application of deep brain stimulation (DBS) in the treatment of movement disorders, new non-neurological indications have emerged, such as for obsessive-compulsive disorders, major depressive disorder, dementia, Gilles de la Tourette Syndrome, anorexia nervosa, and addictions. As DBS is a network modulation surgical treatment, the development of DBS for both neurological and psychiatric disorders has been partly driven by advances in neuroimaging, which has helped explain the brain networks implicated. Advances in magnetic resonance imaging connectivity and electrophysiology have led to the development of the concept of modulating widely distributed, complex brain networks. Moreover, the increasing number of targets for treating psychiatric disorders have indicated that there may be a convergence of the effect of stimulating different targets for the same disorder, and the effect of stimulating the same target for different disorders. The aim of this paper is to review the imaging studies of DBS for psychiatric disorders. Imaging, and particularly connectivity analysis, offers exceptional opportunities to better understand and even predict the clinical outcomes of DBS, especially where there is a lack of objective biomarkers that are essential to properly guide DBS pre- and post-operatively. In future, imaging might also prove useful to individualize DBS treatment. Finally, one of the most important aspects of imaging in DBS is that it allows us to better understand the brain through observing the changes of the functional connectome under neuromodulation, which may in turn help explain the mechanisms of action of DBS that remain elusive.

Ethical examination of deep brain stimulation's 'last resort' status

Deep brain stimulation (DBS) interventions are novel devices being investigated for the management of severe treatment-resistant psychiatric illnesses. These interventions require the invasive implantation of high-frequency neurostimulatory probes intracranially aiming to provide symptom relief in treatment-resistant disorders including obsessive-compulsive disorder and anorexia nervosa. In the scientific literature, these neurostimulatory interventions are commonly described as reversible and to be used as a last resort option for psychiatric patients. However, the 'last resort' status of these interventions is rarely expanded upon. Contrastingly, usages of DBS devices for neurological symptoms (eg, Parkinson's disease, epilepsy or dystonia) have paved the way for established safety and efficacy standards when used earlier in a disease's timeline. As DBS treatments for these neurological diseases progress to have earlier indications, there is a parallel ethical concern that early implementation may one day become prescribed for psychiatric illnesses. The purpose of this article is to build off contemporary understandings of reversible neurostimulatory interventions to examine and provide clarifications on the 'last resort' status of DBS to better address its ethically charged use in psychiatric neurosurgery. To do this, evaluative differences between DBS treatments will be discussed to demonstrate how patient autonomy would be a paramount guiding principle when one day implementing these devices at various points along a psychiatric disease's timeline. In presenting the clarification of 'last resort' status, the ethical tensions of early DBS interventions will be better understood to assist in providing psychiatric patients with more quality of life years in line with their values.

Neuromodulation for major depressive disorder: innovative measures to capture efficacy and outcomes

Major depressive disorder is a common and debilitating disorder. Although most patients with this disorder benefit from established treatments, a subset of patients have symptoms that remain treatment resistant. Novel treatment approaches, such as deep brain stimulation, are urgently needed for patients with treatment-resistant major depressive disorder. These novel treatments are currently being tested in clinical trials in which success hinges on how accurately and comprehensively the primary outcome measure captures the treatment effect. In this Personal View, we argue that current measures used to assess outcomes in neurosurgical trials of major depressive disorder might be missing clinically important treatment effects. A crucial problem of continuing to use suboptimal outcome measures is that true signals of efficacy might be missed, thereby disqualifying potentially effective treatments. We argue that a re-evaluation of how outcomes are measured in these trials is much overdue and describe several novel approaches that attempt to better capture meaningful change.

The Use of Tractography-Based Targeting in Deep Brain Stimulation for Psychiatric Indications

Deep Brain Stimulation (DBS) has been investigated as a treatment option for patients with refractory psychiatric illness. Over the past two decades, neuroimaging developments have helped to advance the field, particularly the use of diffusion tensor imaging (DTI) and tractographic reconstruction of white-matter pathways. In this article, we review translational considerations and how DTI and tractography have been used to improve targeting during DBS surgery for depression, obsessive compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).

Improving long term patient outcomes from deep brain stimulation for treatment-refractory obsessive-compulsive disorder

Introduction: Deep brain stimulation (DBS) has emerged as an effective treatment for patients with severe treatment-refractory obsessive-compulsive disorder (OCD). Over the past two decades, several clinical trials with multiple years of follow-up have shown that DBS offers long-term symptom relief for individuals with severe OCD, though a portion of patients do not achieve an adequate response.Areas covered: This review sought to summarize the literature on the efficacy and long-term effectiveness of DBS for OCD, and to identify strategies that have the potential to improve treatment outcomes.Expert opinion: Although this literature is just emerging, a small number of DBS enhancement strategies have shown promising initial results. More posterior targets along the striatal axis and at the bed nucleus of the stria terminalis appear to offer greater symptom relief than more anterior targets. Research is also beginning to demonstrate the feasibility of maximizing treatment outcomes with target selection based on neural activation patterns during symptom provocation and clinical presentation. Finally, integrating DBS with post-surgery exposure and response prevention therapy appears to be another promising approach. Definitive conclusions about these strategies are limited by a low number of studies with small sample sizes that will require multi-site replication.

Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead

There is growing interest in non-invasive brain stimulation (NIBS) as a novel treatment option for substance-use disorders (SUDs). Recent momentum stems from a foundation of preclinical neuroscience demonstrating links between neural circuits and drug consuming behavior, as well as recent FDA-approval of NIBS treatments for mental health disorders that share overlapping pathology with SUDs. As with any emerging field, enthusiasm must be tempered by reason; lessons learned from the past should be prudently applied to future therapies. Here, an international ensemble of experts provides an overview of the state of transcranial-electrical (tES) and transcranial-magnetic (TMS) stimulation applied in SUDs. This consensus paper provides a systematic literature review on published data - emphasizing the heterogeneity of methods and outcome measures while suggesting strategies to help bridge knowledge gaps. The goal of this effort is to provide the community with guidelines for best practices in tES/TMS SUD research. We hope this will accelerate the speed at which the community translates basic neuroscience into advanced neuromodulation tools for clinical practice in addiction medicine.

Animal Models and Animal Experimentation in the Development of Deep Brain Stimulation: From a Specific Controversy to a Multidimensional Debate

In this article, we explore a specific controversy about animal experimentation and animal models in the recent history of deep brain stimulation (DBS), and we question its ramifications. DBS development intertwines clinical practice with fundamental research and stands at the crossroads of multiple legacies. We take up the various issues and controversies embedded in this rarely addressed dispute, from a standpoint that combines socio-anthropological and legal aspects. Our starting point is a debate on the role of animal experimentation in the development of DBS between Jarrod Bailey, a researcher promoting the abolition of animal experimentation, and Alim Louis Benabid, Marwan Hariz, and Mahlon DeLong, three key figures in the area of DBS and neuroscience. By clarifying the positions of the different protagonists and retracing the issues raised in these discussions, our objective is to show how this specific debate has extended from its initial space and how it provides an object of study with heuristic scope. We first present this partially polemic discussion about the history of DBS, and its link with a more general debate on the validity and use of animal models and the need for animal experiments. Then, we raise the issue of the relations and interactions between experiments on animals and on humans in the logics of biomedical innovation. The third step is to situate the discussion within the wider framework of opposition towards animal experimentation and the promotion of animal' rights. Finally, combining these interweaved issues, possible implications emerge regarding the future of DBS. We show that behind these several controversies lie the question of translational research and the model of medicine upheld by DBS. We describe how the technology contributes to blurring the lines between research (fundamental, preclinical and clinical research) and care, as well as between humans and animals as substrates and objects of knowledge. The dynamics of DBS future development might then become a point of convergence for neuroscientists and animal rights defenders' interests.

Deep brain stimulation of the internal capsule enhances human cognitive control and prefrontal cortex function

Deep brain stimulation (DBS) is a circuit-oriented treatment for mental disorders. Unfortunately, even well-conducted psychiatric DBS clinical trials have yielded inconsistent symptom relief, in part because DBS’ mechanism(s) of action are unclear. One clue to those mechanisms may lie in the efficacy of ventral internal capsule/ventral striatum (VCVS) DBS in both major depression (MDD) and obsessive-compulsive disorder (OCD). MDD and OCD both involve deficits in cognitive control. Cognitive control depends on prefrontal cortex (PFC) regions that project into the VCVS. Here, we show that VCVS DBS’ effect is explained in part by enhancement of PFC-driven cognitive control. DBS improves human subjects’ performance on a cognitive control task and increases theta (5–8Hz) oscillations in both medial and lateral PFC. The theta increase predicts subjects’ clinical outcomes. Our results suggest a possible mechanistic approach to DBS therapy, based on tuning stimulation to optimize these neurophysiologic phenomena.

Deep brain stimulation (DBS) is a promising treatment for psychiatric disorders, but its mechanism in relieving symptoms is unclear. Here, the authors show that DBS of ventral internal capsule/ventral striatum (VCVS) may act by enhancing prefrontal cortex oscillations that in turn enhance cognitive control.

Comparative effectiveness of neuroablation and deep brain stimulation for treatment-resistant obsessive-compulsive disorder: a meta-analytic study

BACKGROUND

The safety and efficacy of neuroablation (ABL) and deep brain stimulation (DBS) for treatment refractory obsessive-compulsive disorder (OCD) has not been examined. This study sought to generate a definitive comparative effectiveness model of these therapies.

METHODS

A EMBASE/PubMed search of English-language, peer-reviewed articles reporting ABL and DBS for OCD was performed in January 2018. Change in quality of life (QOL) was quantified based on the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) and the impact of complications on QOL was assessed. Mean response of Y-BOCS was determined using random-effects, inverse-variance weighted meta-analysis of observational data.

FINDINGS

Across 56 studies, totalling 681 cases (367 ABL; 314 DBS), ABL exhibited greater overall utility than DBS. Pooled ability to reduce Y-BOCS scores was 50.4% (±22.7%) for ABL and was 40.9% (±13.7%) for DBS. Meta-regression revealed no significant change in per cent improvement in Y-BOCS scores over the length of follow-up for either ABL or DBS. Adverse events occurred in 43.6% (±4.2%) of ABL cases and 64.6% (±4.1%) of DBS cases (p<0.001). Complications reduced ABL utility by 72.6% (±4.0%) and DBS utility by 71.7% (±4.3%). ABL utility (0.189±0.03) was superior to DBS (0.167±0.04) (p<0.001).

INTERPRETATION

Overall, ABL utility was greater than DBS, with ABL showing a greater per cent improvement in Y-BOCS than DBS. These findings help guide success thresholds in future clinical trials for treatment refractory OCD.

COMPASS: An Open-Source, General-Purpose Software Toolkit for Computational Psychiatry

Mathematical modeling of behavior during a psychophysical task, referred to as "computational psychiatry," could greatly improve our understanding of mental disorders. One barrier to the broader adoption of computational methods, is that they often require advanced statistical modeling and mathematical skills. Biological and behavioral signals often show skewed or non-Gaussian distributions, and very few toolboxes and analytical platforms are capable of processing such signal categories. We developed the Computational Psychiatry Adaptive State-Space (COMPASS) toolbox, an open-source MATLAB-based software package. This toolbox is easy to use and capable of integrating signals with a variety of distributions. COMPASS has the tools to process signals with continuous-valued and binary measurements, or signals with incomplete-missing or censored-measurements, which makes it well-suited for processing those signals captured during a psychophysical task. After specifying a few parameters in a small set of user-friendly functions, COMPASS allows users to efficiently apply a wide range of computational behavioral models. The model output can be analyzed as an experimental outcome or used as a regressor for neural data and can also be tested using the goodness-of-fit measurement. Here, we demonstrate that COMPASS can replicate two computational behavioral analyses from different groups. COMPASS replicates and can slightly improve on the original modeling results. We also demonstrate the use of COMPASS application in a censored-data problem and compare its performance result with naïve estimation methods. This flexible, general-purpose toolkit should accelerate the use of computational modeling in psychiatric neuroscience.

Stereoelectroencephalography in epilepsy, cognitive neurophysiology, and psychiatric disease: safety, efficacy, and place in therapy

For patients with drug-resistant epilepsy, surgical intervention may be an effective treatment option if the epileptogenic zone (EZ) can be well localized. Subdural strip and grid electrode (SDE) implantations have long been used as the mainstay of intracranial seizure localization in the United States. Stereoelectroencephalography (SEEG) is an alternative approach in which depth electrodes are placed through percutaneous drill holes to stereotactically defined coordinates in the brain. Long used in certain centers in Europe, SEEG is gaining wider popularity in North America, bolstered by the advent of stereotactic robotic assistance and mounting evidence of safety, without the need for catheter-based angiography. Rates of clinically significant hemorrhage, infection, and other complications appear lower with SEEG than with SDE implants. SEEG also avoids unnecessary craniotomies when seizures are localized to unresectable eloquent cortex, found to be multifocal or nonfocal, or ultimately treated with stereotactic procedures such as laser interstitial thermal therapy (LITT), radiofrequency thermocoagulation (RF-TC), responsive neurostimulation (RNS), or deep brain stimulation (DBS). While SDE allows for excellent localization and functional mapping on the cortical surface, SEEG offers a less invasive option for sampling disparate brain areas, bilateral investigations, and deep or medial targets. SEEG has shown efficacy for seizure localization in the temporal lobe, the insula, lesional and nonlesional extra-temporal epilepsy, hypothalamic hamartomas, periventricular nodular heterotopias, and patients who have had prior craniotomies for resections or grids. SEEG offers a valuable opportunity for cognitive neurophysiology research and may have an important role in the study of dysfunctional networks in psychiatric disease and understanding the effects of neuromodulation.

Tuning Neuromodulation Effects by Orientation Selective Deep Brain Stimulation in the Rat Medial Frontal Cortex

Previous studies that focused on treating major depressive disorder with conventional deep brain stimulation (DBS) paradigms produced inconsistent results. In this proof-of-concept preclinical study in rats (n = 8), we used novel paradigms of orientation selective DBS for stimulating the complex circuitry crossing the infralimbic cortex, an area considered analogous to human subgenual cingulate cortex. Using functional MRI at 9.4 T, we monitored whole brain responses to varying the electrical field orientation of DBS within the infralimbic cortex. Substantial alterations of functional MRI responses in the amygdala, a major node connected to the infralimbic cortex implicated in the pathophysiology of depression, were observed. As expected, the activation cluster near the electrode was insensitive to the changes of the stimulation orientation. Hence, our findings substantiate the ability of orientation selective stimulation (OSS) to recruit neuronal pathways of distinct orientations relative to the position of the electrode, even in complex circuits such as those involved in major depressive disorder. We conclude that OSS is a promising approach for stimulating brain areas that inherently require individualisation of the treatment approach.

Altering alpha-frequency brain oscillations with rapid analog feedback-driven neurostimulation

Oscillations of the brain's local field potential (LFP) may coordinate neural ensembles and brain networks. It has been difficult to causally test this model or to translate its implications into treatments, because there are few reliable ways to alter LFP oscillations. We developed a closed-loop analog circuit to enhance brain oscillations by feeding them back into cortex through phase-locked transcranial electrical stimulation. We tested the system in a rhesus macaque with chronically implanted electrode arrays, targeting 8-15 Hz (alpha) oscillations. Ten seconds of stimulation increased alpha oscillatory power for up to 1 second after stimulation offset. In contrast, open-loop stimulation decreased alpha power. There was no effect in the neighboring 15-30 Hz (beta) LFP rhythm or on a neighboring array that did not participate in closed-loop feedback. Analog closed-loop neurostimulation might thus be a useful strategy for altering brain oscillations, both for basic research and the treatment of neuro-psychiatric disease.

A neural mass model to predict electrical stimulation evoked responses in human and non-human primate brain

OBJECTIVE

Deep brain stimulation (DBS) is a valuable tool for ameliorating drug resistant pathologies such as movement disorders and epilepsy. DBS is also being considered for complex neuro-psychiatric disorders, which are characterized by high variability in symptoms and slow responses that hinder DBS setting optimization. The objective of this work was to develop an in silico platform to examine the effects of electrical stimulation in regions neighboring a stimulated brain region.

APPROACH

We used the Jansen-Rit neural mass model of single and coupled nodes to simulate the response to a train of electrical current pulses at different frequencies (10-160 Hz) of the local field potential recorded in the amygdala and cortical structures in human subjects and a non-human primate.

RESULTS

We found that using a single node model, the evoked responses could be accurately modeled following a narrow range of stimulation frequencies. Including a second coupled node increased the range of stimulation frequencies whose evoked responses could be efficiently modeled. Furthermore, in a chronic recording from a non-human primate, features of the in vivo evoked response remained consistent for several weeks, suggesting that model re-parameterization for chronic stimulation protocols would be infrequent.

SIGNIFICANCE

Using a model of neural population activity, we reproduced the evoked response to cortical and subcortical stimulation in human and non-human primate. This modeling framework provides an environment to explore, safely and rapidly, a wide range of stimulation settings not possible in human brain stimulation studies. The model can be trained on a limited dataset of stimulation responses to develop an optimal stimulation strategy for an individual patient.

Totally Implantable Bidirectional Neural Prostheses: A Flexible Platform for Innovation in Neuromodulation

Implantable neural prostheses are in widespread use for treating a variety of brain disorders. Until recently, most implantable brain devices have been unidirectional, either delivering neurostimulation without brain sensing, or sensing brain activity to drive external effectors without a stimulation component. Further, many neural interfaces that incorporate a sensing function have relied on hardwired connections, such that subjects are tethered to external computers and cannot move freely. A new generation of neural prostheses has become available, that are both bidirectional (stimulate as well as record brain activity) and totally implantable (no externalized connections). These devices provide an opportunity for discovering the circuit basis for neuropsychiatric disorders, and to prototype personalized neuromodulation therapies that selectively interrupt neural activity underlying specific signs and symptoms.

Deep Brain Stimulation in Psychiatry: Mechanisms, Models, and Next-Generation Therapies

Deep brain stimulation has preliminary evidence of clinical efficacy, but has been difficult to develop into a robust therapy, in part because its mechanisms are incompletely understood. We review evidence from movement and psychiatric disorder studies, with an emphasis on how deep brain stimulation changes brain networks. From this, we argue for a network-oriented approach to future deep brain stimulation studies. That network approach requires methods for identifying patients with specific circuit/network deficits. We describe how dimensional approaches to diagnoses may aid that identification. We discuss the use of network/circuit biomarkers to develop self-adjusting "closed loop" systems.

Deep Brain Stimulation: Clinical Applications

Deep brain stimulation has been used for decades in neurology to treat movement disorders. More recent work has focused on developing applications for deep brain stimulation in psychiatric illness. Initial studies have demonstrated positive results for treatment-refractory obsessive-compulsive disorder. Initial open-label studies of deep brain stimulation at targets for treatment-resistant depression have been encouraging. However, the only 2 published controlled trials that were conducted for potential FDA approval for treatment-resistant depression were both negative. Future directions include potential use of alternate clinical trial designs, using tractography for more refined deep brain stimulation electrode targeting, and closed-loop deep brain stimulation approaches.

Closed Loop Deep Brain Stimulation for PTSD, Addiction, and Disorders of Affective Facial Interpretation: Review and Discussion of Potential Biomarkers and Stimulation Paradigms

The treatment of psychiatric diseases with Deep Brain Stimulation (DBS) is becoming more of a reality as studies proliferate the indications and targets for therapies. Opinions on the initial failures of DBS trials for some psychiatric diseases point to a certain lack of finesse in using an Open Loop DBS (OLDBS) system in these dynamic, cyclical pathologies. OLDBS delivers monomorphic input into dysfunctional brain circuits with modulation of that input via human interface at discrete time points with no interim modulation or adaptation to the changing circuit dynamics. Closed Loop DBS (CLDBS) promises dynamic, intrinsic circuit modulation based on individual physiologic biomarkers of dysfunction. Discussed here are several psychiatric diseases which may be amenable to CLDBS paradigms as the neurophysiologic dysfunction is stochastic and not static. Post-Traumatic Stress Disorder (PTSD) has several peripheral and central physiologic and neurologic changes preceding stereotyped hyper-activation behavioral responses. Biomarkers for CLDBS potentially include skin conductance changes indicating changes in the sympathetic nervous system, changes in serum and central neurotransmitter concentrations, and limbic circuit activation. Chemical dependency and addiction have been demonstrated to be improved with both ablation and DBS of the Nucleus Accumbens and as a serendipitous side effect of movement disorder treatment. Potential peripheral biomarkers are similar to those proposed for PTSD with possible use of environmental and geolocation based cues, peripheral signs of physiologic arousal, and individual changes in central circuit patterns. Non-substance addiction disorders have also been serendipitously treated in patients with OLDBS for movement disorders. As more is learned about these behavioral addictions, DBS targets and effectors will be identified. Finally, discussed is the use of facial recognition software to modulate activation of inappropriate responses for psychiatric diseases in which misinterpretation of social cues feature prominently. These include Autism Spectrum Disorder, PTSD, and Schizophrenia-all of which have a common feature of dysfunctional interpretation of facial affective clues. Technological advances and improvements in circuit-based, individual-specific, real-time adaptable modulation, forecast functional neurosurgery treatments for heretofore treatment-resistant behavioral diseases.

Targeted neural network interventions for auditory hallucinations: Can TMS inform DBS?

The debilitating and refractory nature of auditory hallucinations (AH) in schizophrenia and other psychiatric disorders has stimulated investigations into neuromodulatory interventions that target the aberrant neural networks associated with them. Internal or invasive forms of brain stimulation such as deep brain stimulation (DBS) are currently being explored for treatment-refractory schizophrenia. The process of developing and implementing DBS is limited by symptom clustering within psychiatric constructs as well as a scarcity of causal tools with which to predict response, refine targeting or guide clinical decisions. Transcranial magnetic stimulation (TMS), an external or non-invasive form of brain stimulation, has shown some promise as a therapeutic intervention for AH but remains relatively underutilized as an investigational probe of clinically relevant neural networks. In this editorial, we propose that TMS has the potential to inform DBS by adding individualized causal evidence to an evaluation processes otherwise devoid of it in patients. Although there are significant limitations and safety concerns regarding DBS, the combination of TMS with computational modeling of neuroimaging and neurophysiological data could provide critical insights into more robust and adaptable network modulation.

Lateral habenula perturbation reduces default-mode network connectivity in a rat model of depression

Hyperconnectivity of the default-mode network (DMN) is one of the most widely replicated neuroimaging findings in major depressive disorder (MDD). Further, there is growing evidence for a central role of the lateral habenula (LHb) in the pathophysiology of MDD. There is preliminary neuroimaging evidence linking LHb and the DMN, but no causal relationship has been shown to date. We combined optogenetics and functional magnetic resonance imaging (fMRI), to establish a causal relationship, using an animal model of treatment-resistant depression, namely Negative Cognitive State rats. First, an inhibitory light-sensitive ion channel was introduced into the LHb by viral transduction. Subsequently, laser stimulation was performed during fMRI acquisition on a 9.4 Tesla animal scanner. Neural activity and connectivity were assessed, before, during and after laser stimulation. We observed a connectivity decrease in the DMN following laser-induced LHb perturbation. Our data indicate a causal link between LHb downregulation and reduction in DMN connectivity. These findings may advance our mechanistic understanding of LHb inhibition, which had previously been identified as a promising therapeutic principle, especially for treatment-resistant depression.

Closing the Loop on Deep Brain Stimulation for Treatment-Resistant Depression

Major depressive episodes are the largest cause of psychiatric disability, and can often resist treatment with medication and psychotherapy. Advances in the understanding of the neural circuit basis of depression, combined with the success of deep brain stimulation (DBS) in movement disorders, spurred several groups to test DBS for treatment-resistant depression. Multiple brain sites have now been stimulated in open-label and blinded studies. Initial open-label results were dramatic, but follow-on controlled/blinded clinical trials produced inconsistent results, with both successes and failures to meet endpoints. Data from follow-on studies suggest that this is because DBS in these trials was not targeted to achieve physiologic responses. We review these results within a technology-lifecycle framework, in which these early trial “failures” are a natural consequence of over-enthusiasm for an immature technology. That framework predicts that from this “valley of disillusionment,” DBS may be nearing a “slope of enlightenment.” Specifically, by combining recent mechanistic insights and the maturing technology of brain-computer interfaces (BCI), the next generation of trials will be better able to target pathophysiology. Key to that will be the development of closed-loop systems that semi-autonomously alter stimulation strategies based on a patient's individual phenotype. Such next-generation DBS approaches hold great promise for improving psychiatric care.

Neuromodulation interventions for addictive disorders: challenges, promise, and roadmap for future research

Addictive disorders are a major public health concern, associated with high relapse rates, significant disability and substantial mortality. Unfortunately, current interventions are only modestly effective. Preclinical studies as well as human neuroimaging studies have provided strong evidence that the observable behaviours that characterize the addiction phenotype, such as compulsive drug consumption, impaired self-control, and behavioural inflexibility, reflect underlying dysregulation and malfunction in specific neural circuits. These developments have been accompanied by advances in neuromodulation interventions, both invasive as deep brain stimulation, and non-invasive such as repetitive transcranial magnetic stimulation and transcranial direct current stimulation. These interventions appear particularly promising as they may not only allow us to probe affected brain circuits in addictive disorders, but also seem to have unique therapeutic applications to directly target and remodel impaired circuits. However, the available literature is still relatively small and sparse, and the long-term safety and efficacy of these interventions need to be confirmed. Here we review the literature on the use of neuromodulation in addictive disorders to highlight progress limitations with the aim to suggest future directions for this field.

Closed-loop neuromodulation systems: next-generation treatments for psychiatric illness

Despite deep brain stimulation's positive early results in psychiatric disorders, well-designed clinical trials have yielded inconsistent clinical outcomes. One path to more reliable benefit is closed-loop therapy: stimulation that is automatically adjusted by a device or algorithm in response to changes in the patient's electrical brain activity. These interventions may provide more precise and patient-specific treatments. This article first introduces the available closed-loop neuromodulation platforms, which have shown clinical efficacy in epilepsy and strong early results in movement disorders. It discusses the strengths and limitations of these devices in the context of psychiatric illness. It then describes emerging technologies to address these limitations, including pre-clinical developments such as wireless deep neurostimulation and genetically targeted neuromodulation. Finally, ongoing challenges and limitations for closed-loop psychiatric brain stimulation development, most notably the difficulty of identifying meaningful biomarkers for titration, are discussed. This is considered in the recently-released Research Domain Criteria (RDoC) framework, and how neuromodulation and RDoC are jointly very well suited to address the problem of treatment-resistant illness is described.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson’s disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.