Patient-specific connectomic models correlate with, but do not reliably predict, outcomes in deep brain stimulation for obsessive-compulsive disorder

Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation

Deep brain stimulation (DBS), a proven treatment for movement disorders, also holds promise for the treatment of psychiatric and cognitive conditions. However, for DBS to be clinically effective, it may require DBS technology that can alter or trigger stimulation in response to changes in biomarkers sensed from the patient's brain. A growing body of evidence suggests that such adaptive DBS is feasible, it might achieve clinical effects that are not possible with standard continuous DBS and that some of the best biomarkers are signals from the cerebral cortex. Yet capturing those markers requires the placement of cortex-optimized electrodes in addition to standard electrodes for DBS. In this Perspective we argue that the need for cortical biomarkers in adaptive DBS and the unfortunate convergence of regulatory and financial factors underpinning the unavailability of cortical electrodes for chronic uses threatens to slow down or stall research on adaptive DBS and propose public-private partnerships as a potential solution to such a critical technological gap.

Striatal stimulation enhances cognitive control and evidence processing in rodents and humans

Brain disorders, in particular mental disorders, might be effectively treated by direct electrical brain stimulation, but clinical progress requires understanding of therapeutic mechanisms. Animal models have not helped, because there are no direct animal models of mental illness. Here, we propose a potential path past this roadblock, by leveraging a common ingredient of most mental disorders: impaired cognitive control. We previously showed that deep brain stimulation (DBS) improves cognitive control in humans. We now reverse translate that result using a set-shifting task in rats. DBS-like stimulation of the midstriatum improved reaction times without affecting accuracy, mirroring our human findings. Impulsivity, motivation, locomotor, and learning effects were ruled out through companion tasks and model-based analyses. To identify the specific cognitive processes affected, we applied reinforcement learning drift-diffusion modeling. This approach revealed that DBS-like stimulation enhanced evidence accumulation rates and lowered decision thresholds, improving domain-general cognitive control. Reanalysis of prior human data showed that the same mechanism applies in humans. This reverse/forward translational model could have near-term implications for clinical DBS practice and future trial design.

A Reproducible Pipeline for Parcellation of the Anterior Limb of the Internal Capsule

BACKGROUND

The anterior limb of the internal capsule (ALIC) is a white matter structure that connects the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation for obsessive-compulsive disorder. There is strong interest in improving deep brain stimulation targeting by using diffusion tractography to reconstruct and target specific ALIC fiber pathways, but this methodology is susceptible to errors and lacks validation. To address these limitations, we developed a novel diffusion tractography pipeline that generates reliable and biologically validated ALIC white matter reconstructions.

METHODS

Following algorithm development and refinement, we analyzed 43 control participants, each with 2 sets of 3T magnetic resonance imaging data and a subset of 5 control participants with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on PFC regions of interest, and we analyzed the relationships among bundles.

RESULTS

We successfully reproduced the topographies established by previous anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intraparticipant variability than interparticipant variability for both test and retest groups across all but one PFC region. We examined the overlap between fibers from different PFC regions and a response tract for obsessive-compulsive disorder deep brain stimulation, and we reconstructed the PFC hyperdirect pathway using a modified version of our pipeline.

CONCLUSIONS

Our diffusion magnetic resonance imaging algorithm reliably generates biologically validated ALIC white matter reconstructions, thereby allowing for more precise modeling of fibers for neuromodulation therapies.

Applying normative atlases in deep brain stimulation: a comprehensive review

Deep brain stimulation (DBS) has emerged as a crucial therapeutic strategy for various neurological and psychiatric disorders. Precise target localization is essential for optimizing therapeutic outcomes, necessitating advanced neuroimaging techniques. Normative atlases provide standardized references for accurate electrode placement, enhancing treatment customization and efficacy. This comprehensive review explores the application of normative atlases in DBS, emphasizing their role in target identification, patient-specific electrode placement, and predicting stimulation outcomes. Challenges, such as variability across atlases and technical complexities, are addressed alongside future directions and innovations, including advancements in neuroimaging technologies and the integration of machine learning (ML) and artificial intelligence (AI). Normative atlases play a pivotal role in enhancing DBS precision and patient outcomes, promising a future of personalized and effective therapies in neurology and psychiatry.

Advances in DTI studies for diagnoses and treatment of obsessive-compulsive disorder

This review summarizes the current state of neuroimaging research on obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI), which allows for the examination of white matter abnormalities in the brain. DTI studies on individuals with obsessive-compulsive disorder (OCD) consistently demonstrate widespread reductions in white matter integrity in various regions of the brain, including the corpus callosum, anterior and posterior cingulate cortex, and prefrontal cortex, which are involved in emotion regulation, decision-making, and cognitive control. However, the reviewed studies often have small sample sizes, and findings vary between studies, highlighting the need for larger and more standardized studies. Furthermore, discerning between causal and consequential effects of OCD on white matter integrity poses a challenge. Addressing this issue may be facilitated through longitudinal studies, including those evaluating the impact of treatment interventions, to enhance the accuracy of DTI data acquisition and processing, thereby improving the validity and comparability of study outcomes. In summary, DTI studies provide valuable insights into the neural circuits and connectivity disruptions in OCD, and future studies may benefit from standardized data analysis and larger sample sizes to determine whether structural abnormalities could be potential biomarkers for early identification and treatment of OCD.

The promise and challenges of transcranial magnetic stimulation and deep brain stimulation as therapeutic options for obsessive-compulsive disorder

INTRODUCTION

Obsessive compulsive disorder (OCD) represents a complex and often difficult to treat disorder. Pharmacological and psychotherapeutic interventions are often associated with sub-optimal outcomes, and 40-60% of patients are resistant to first line therapies and thus left with few treatment options. OCD is underpinned by aberrant neurocircuitry within cortical, striatal, and thalamic brain networks. Considering the neurocircuitry impairments that underlie OCD symptomology, neurostimulation therapies provide an opportunity to modulate psychopathology in a personalized manner. Also, by probing pathological neural networks, enhanced understanding of disease states can be obtained.

AREAS COVERED

This perspective discusses the clinical efficacy of TMS and DBS therapies, treatment access options, and considerations and challenges in managing patients. Recent scientific progress is discussed, with a focus on neurocircuitry and biopsychosocial aspects. Translational recommendations and suggestions for future research are provided.

EXPERT OPINION

There is robust evidence to support TMS and DBS as an efficacious therapy for treatment resistant OCD patients supported by an excellent safety profile and favorable health economic data. Despite a great need for alternative therapies for chronic and severe OCD patients, resistance toward neurostimulation therapies from regulatory bodies and the psychiatric community remains. The authors contend for greater access to TMS and DBS for treatment resistant OCD patients at specialized sites with appropriate clinical resources, particularly considering adjunct and follow-up care. Also, connectome targeting has shown robust predictive ability of symptom improvements and holds potential in advancing personalized neurostimulation therapies.

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.

In silicodevelopment and validation of Bayesian methods for optimizing deep brain stimulation to enhance cognitive control

Objective.deep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement.Approach.we leverage prior results showing that effective VCVS DBS engages cognitive control circuitry and improves performance on the multi-source interference task, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We develop a simulation framework based on those empirical results, then combine this framework with an adaptive optimizer to simulate a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control. We explore multiple optimization options (algorithms, number of inputs, speed of stimulation parameter changes) and compare them on problems of varying difficulty.Main results.we show that an upper confidence bound algorithm outperforms other optimizers, with roughly 80% probability of convergence to a global optimum when used in a majority-vote ensemble.Significance.we show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.

Closed-Loop Deep Brain Stimulation for Psychiatric Disorders

ABSTRACT

Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.

Personalized Definition of Surgical Targets in Major Depression and Obsessive-Compulsive Disorder: A Potential Role for Low-Intensity Focused Ultrasound?

Major Depressive Disorder (MDD) and Obsessive-Compulsive Disorder (OCD) are common and potentially incapacitating conditions. Even when recognized and adequately treated, in over a third of patients with these conditions the response to first-line pharmacological and psychotherapeutic measures is not satisfactory. After more assertive measures including pharmacological augmentation (and in the case of depression, transcranial magnetic stimulation, electroconvulsive therapy, or treatment with ketamine or esketamine), a significant number of individuals remain severely symptomatic. In these persons, different ablation and deep-brain stimulation (DBS) psychosurgical techniques have been employed. However, apart from the cost and potential morbidity associated with surgery, on average only about half of patients show adequate response, which limits the widespread application of these potentially life-saving interventions. Possible reasons are considered for the wide variation in outcomes across different series of patients with MDD or OCD exposed to ablative or DBS psychosurgery, including interindividual anatomical and etiological variability. Low-intensity focused ultrasound (LIFU) is an emerging technique that holds promise in its ability to achieve anatomically circumscribed, noninvasive, and reversible neuromodulation of deep brain structures. A possible role for LIFU in the personalized presurgical definition of neuromodulation targets in the individual patient is discussed, including a proposed roadmap for clinical trials addressed at testing whether this technique can help to improve psychosurgical outcomes.

Causally mapping human threat extinction relevant circuits with depolarizing brain stimulation methods

Laboratory threat extinction paradigms and exposure-based therapy both involve repeated, safe confrontation with stimuli previously experienced as threatening. This fundamental procedural overlap supports laboratory threat extinction as a compelling analogue of exposure-based therapy. Threat extinction impairments have been detected in clinical anxiety and may contribute to exposure-based therapy non-response and relapse. However, efforts to improve exposure outcomes using techniques that boost extinction - primarily rodent extinction - have largely failed to date, potentially due to fundamental differences between rodent and human neurobiology. In this review, we articulate a comprehensive pre-clinical human research agenda designed to overcome these failures. We describe how connectivity guided depolarizing brain stimulation methods (i.e., TMS and DBS) can be applied concurrently with threat extinction and dual threat reconsolidation-extinction paradigms to causally map human extinction relevant circuits and inform the optimal integration of these methods with exposure-based therapy. We highlight candidate targets including the amygdala, hippocampus, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, and mesolimbic structures, and propose hypotheses about how stimulation delivered at specific learning phases could strengthen threat extinction.

Tractography-based versus anatomical landmark-based targeting in vALIC deep brain stimulation for refractory obsessive-compulsive disorder

Deep brain stimulation (DBS) of the ventral anterior limb of the internal capsule (vALIC) is effective for refractory obsessive-compulsive disorder (OCD). Retrospective evaluation showed that stimulation closer to the supero-lateral branch of the medial forebrain bundle (slMFB), within the vALIC, was associated with better response to DBS. The present study is the first to compare outcomes of DBS targeted at the vALIC using anatomical landmarks and DBS with connectomic tractography-based targeting of the slMFB. We included 20 OCD-patients with anatomical landmark-based DBS of the vALIC that were propensity score matched to 20 patients with tractography-based targeting of electrodes in the slMFB. After one year, we compared severity of OCD, anxiety and depression symptoms, response rates, time to response, number of parameter adjustments, average current, medication usage and stimulation-related adverse effects. There was no difference in Y-BOCS decrease between patients with anatomical landmark-based and tractography-based DBS. Nine (45%) patients with anatomical landmark-based DBS and 13 (65%) patients with tractography-based DBS were responders (BF₁₀ = 1.24). The course of depression and anxiety symptoms, time to response, number of stimulation adjustments or medication usage did not differ between groups. Patients with tractography-based DBS experienced fewer stimulation-related adverse effects than patients with anatomical landmark-based DBS (38 vs 58 transient and 1 vs. 17 lasting adverse effects; BF₁₀ = 14.968). OCD symptoms in patients with anatomical landmark-based DBS of the vALIC and tractography-based DBS of the slMFB decrease equally, but patients with tractography-based DBS experience less adverse effects.

Neuromodulation of OCD: A review of invasive and non-invasive methods

Early research into neural correlates of obsessive compulsive disorder (OCD) has focused on individual components, several network-based models have emerged from more recent data on dysfunction within brain networks, including the the lateral orbitofrontal cortex (lOFC)-ventromedial caudate, limbic, salience, and default mode networks. Moreover, the interplay between multiple brain networks has been increasingly recognized. As the understanding of the neural circuitry underlying the pathophysiology of OCD continues to evolve, so will too our ability to specifically target these networks using invasive and noninvasive methods. This review discusses the rationale for and theory behind neuromodulation in the treatment of OCD.

A Systematic Review of Treatment Outcome Predictors in Deep Brain Stimulation for Refractory Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is a chronic and debilitating mental disorder. Deep brain stimulation (DBS) is a promising approach for refractory OCD patients. Research aiming at treatment outcome prediction is vital to provide optimized treatments for different patients. The primary purpose of this systematic review was to collect and synthesize studies on outcome prediction of OCD patients with DBS implantations in recent years. This systematic review (PROSPERO registration number: CRD42022335585) followed the PRISMA (Preferred Reporting Items for Systematic Review and Meta-analysis) guidelines. The search was conducted using three different databases with the following search terms related to OCD and DBS. We identified a total of 3814 articles, and 17 studies were included in our review. A specific tract confirmed by magnetic resonance imaging (MRI) was predictable for DBS outcome regardless of implant targets, but inconsistencies still exist. Current studies showed various ways of successful treatment prediction. However, considering the heterogeneous results, we hope that future studies will use larger cohorts and more precise approaches for predictors and establish more personalized ways of DBS surgeries.