A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder.Nat Commun. 2020;11:3364. [PMID: 32620886 DOI: 10.1038/s41467-020-16734-3]

Connectivity-based parcellation of the amygdala and identification of its main white matter connections

The amygdala plays a role in emotion, learning, and memory and has been implicated in behavioral disorders. Better understanding of the amygdala circuitry is crucial to develop new therapies for these disorders. We used data from 200 healthy-subjects from the human connectome project. Using probabilistic tractography, we created population statistical maps of amygdala connectivity to brain regions involved in limbic, associative, memory, and reward circuits. Based on the amygdala connectivity with these regions, we applied k-means clustering to parcellate the amygdala into three clusters. The resultant clusters were averaged across all subjects and the main white-matter pathways of the amygdala from each averaged cluster were generated. Amygdala parcellation into three clusters showed a medial-to-lateral pattern. The medial cluster corresponded with the centromedial and cortical nuclei, the basal cluster with the basal nuclei and the lateral cluster with the lateral nuclei. The connectivity analysis revealed different white-matter pathways consistent with the anatomy of the amygdala circuit. This in vivo connectivity-based parcellation of the amygdala delineates three clusters of the amygdala in a mediolateral pattern based on its connectivity with brain areas involved in cognition, memory, emotion, and reward. The human amygdala circuit presented in this work provides the first step for personalized amygdala circuit mapping for patients with behavioral disorders.

The rostral zona incerta: a subcortical integrative hub and potential DBS target for OCD

BACKGROUND

The zona incerta (ZI) is involved in mediating survival behaviors and is connected to a wide range of cortical and subcortical structures, including key basal ganglia nuclei. Based on these connections and their links to behavioral modulation, we propose that the ZI is a connectional hub for mediating between top-down and bottom-up control and a possible target for deep brain stimulation for obsessive-compulsive disorder.

METHODS

We analyzed the trajectory of cortical fibers to the ZI in nonhuman and human primates based on tracer injections in monkeys and high-resolution diffusion magnetic resonance imaging in humans. The organization of cortical and subcortical connections within the ZI were identified in the nonhuman primate studies.

RESULTS

Monkey anatomical data and human diffusion magnetic resonance imaging data showed a similar trajectory of fibers/streamlines to the ZI. Prefrontal cortex/anterior cingulate cortex terminals all converged within the rostral ZI, with dorsal and lateral areas being most prominent. Motor areas terminated caudally. Dense subcortical reciprocal connections included the thalamus, medial hypothalamus, substantia nigra/ventral tegmental area, reticular formation, and pedunculopontine nucleus and a dense nonreciprocal projection to the lateral habenula. Additional connections included the amygdala, dorsal raphe nucleus, and periaqueductal gray.

CONCLUSIONS

Dense connections with dorsal and lateral prefrontal cortex/anterior cingulate cortex cognitive control areas and the lateral habenula and the substantia nigra/ventral tegmental area, coupled with inputs from the amygdala, hypothalamus, and brainstem, suggest that the rostral ZI is a subcortical hub positioned to modulate between top-down and bottom-up control. A deep brain stimulation electrode placed in the rostral ZI would not only involve connections common to other deep brain stimulation sites but also capture several critically distinctive connections.

Structural and functional correlates of the response to deep brain stimulation at ventral capsule/ventral striatum region for treatment-resistant depression

BACKGROUND

Though deep brain stimulation (DBS) shows increasing potential in treatment-resistant depression (TRD), the underlying neural mechanisms remain unclear. Here, we investigated functional and structural connectivities related to and predictive of clinical effectiveness of DBS at ventral capsule/ventral striatum region for TRD.

METHODS

Stimulation effects of 71 stimulation settings in 10 TRD patients were assessed. The electric fields were estimated and combined with normative functional and structural connectomes to identify connections as well as fibre tracts beneficial for outcome. We calculated stimulation-dependent optimal connectivity and constructed models to predict outcome. Leave-one-out cross-validation was used to validate the prediction value.

RESULTS

Successful prediction of antidepressant effectiveness in out-of-sample patients was achieved by the optimal connectivity profiles constructed with both the functional connectivity (R=0.49 at p<10-4; deviated by 14.4±10.9% from actual, p<0.001) and structural connectivity (R=0.51 at p<10-5; deviated by 15.2±11.5% from actual, p<10-5). Frontothalamic pathways and cortical projections were delineated for optimal clinical outcome. Similarity estimates between optimal connectivity profile from one modality (functional/structural) and individual brain connectivity in the other modality (structural/functional) significantly cross-predicted the outcome of DBS. The optimal structural and functional connectivity mainly converged at the ventral and dorsal lateral prefrontal cortex and orbitofrontal cortex.

CONCLUSIONS

Connectivity profiles and fibre tracts following frontothalamic streamlines appear to predict outcome of DBS for TRD. The findings shed light on the neural pathways in depression and may be used to guide both presurgical planning and postsurgical programming after further validation.

Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease

Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer's Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming.

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.

A population-normalized tractographic fiber atlas of the anterior limb of the internal capsule: relevance to surgical neuromodulation

OBJECTIVE

The anterior limb of the internal capsule (ALIC) is a white matter highway that connects several subcortical structures to the prefrontal cortex. Although surgical interventions in the ALIC have been used to treat a number of psychiatric illnesses, there is significant debate regarding what fibers are targeted for intervention. This debate is partially due to an incomplete understanding of connectivity in the region.

METHODS

To better understand this complex structure, the authors employed a novel tractography-based approach to examine how fibers from the thalamus and subthalamic nucleus (STN) traverse the ALIC. Furthermore, the authors analyzed connections from the medial dorsal nucleus, anterior nucleus, and ventral anterior nucleus of the thalamus.

RESULTS

The results showed that there is an organizational gradient of thalamic fibers medially and STN fibers laterally in the ALIC that fades more anteriorly. These findings, in combination with the known corticotopic organization described by previous studies, allow for a more thorough understanding of the organization of the white matter fibers in the ALIC.

CONCLUSIONS

These results are important for understanding and targeting of neuromodulatory therapies in the ALIC and may help explain why differences in therapeutic effect are observed for different areas of the ALIC.

Developments in the mechanistic understanding and clinical application of deep brain stimulation for Parkinson's disease

INTRODUCTION. Deep brain stimulation (DBS) is a life-changing treatment for patients with Parkinson's disease (PD) and gives the unique opportunity to directly explore how basal ganglia work. Despite the rapid technological innovation of the last years, the untapped potential of DBS is still high.

AREAS COVERED. This review summarizes the developments in the mechanistic understanding of DBS and the potential clinical applications of cutting-edge technological advances. Rather than a univocal local mechanism, DBS exerts its therapeutic effects through several multimodal mechanisms and involving both local and network-wide structures, although crucial questions remain unexplained. Nonetheless, new insights in mechanistic understanding of DBS in PD have provided solid bases for advances in preoperative selection phase, prediction of motor and non-motor outcomes, leads placement and postoperative stimulation programming.

EXPERT OPINION. DBS has not only strong evidence of clinical effectiveness in PD treatment, but technological advancements are revamping its role of neuromodulation of brain circuits and key to better understanding PD pathophysiology. In the next few years, the worldwide use of new technologies in clinical practice will provide large data to elucidate their role and to expand their applications for PD patients, providing useful insights to personalize DBS treatment and follow-up.

Clinical recommendations for the care of people with treatment-refractory obsessive-compulsive disorder when undergoing deep brain stimulation

Deep brain stimulation is an emerging therapy for treatment-refractory obsessive-compulsive disorder patients. Yet, accessibility is limited, treatment protocols are heterogeneous and there is no guideline or consensus on the best practices. Here, we combine evidence from scientific investigations, expert opinions and our clinical expertise to propose several clinical recommendations from the pre-operative, surgical and post-operative phases of deep brain stimulation care for treatment-refractory obsessive-compulsive disorder patients. A person-centered and biopsychosocial approach is adopted. Briefly, we discuss clinical characteristics associated with response, the use of improved educational materials, an evaluative consent process, comprehensive programming by an expert clinician, a more global assessment of treatment efficacy, multi-disciplinary adjunct psychotherapy and the importance of peer support programs. Furthermore, where gaps are identified, future research suggestions are made, including connectome surgical targeting, scientific evaluation of hardware models and health economic data. In addition, we encourage collaborative groups of data and knowledge sharing by way of a clinical registry and a peer group of programming clinicians. We aim to commence a discussion on the determinants of deep brain stimulation efficacy for treatment-refractory obsessive-compulsive disorder patients, a rare and severe patient group, and contribute to more standardized and evidence-based practices.

Clinical neuroscience and neurotechnology: An amazing symbiosis

In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.

Efficacy of deep brain stimulation for treatment-resistant obsessive-compulsive disorder: systematic review and meta-analysis

Deep brain stimulation (DBS) is an established and growing intervention for treatment-resistant obsessive-compulsive disorder (TROCD). We assessed current evidence on the efficacy of DBS in alleviating OCD and comorbid depressive symptoms including newly available evidence from recent trials and a deeper risk of bias analysis than previously available. PubMed and EMBASE databases were systematically queried using Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. We included studies reporting primary data on multiple patients who received DBS therapy with outcomes reported through the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Primary effect measures included Y-BOCS mean difference and per cent reduction as well as responder rate (≥35% Y-BOCS reduction) at last follow-up. Secondary effect measures included standardised depression scale reduction. Risk of bias assessments were performed on randomised controlled (RCTs) and non-randomised trials. Thirty-four studies from 2005 to 2021, 9 RCTs (n=97) and 25 non-RCTs (n=255), were included in systematic review and meta-analysis based on available outcome data. A random-effects model indicated a meta-analytical average 14.3 point or 47% reduction (p<0.01) in Y-BOCS scores without significant difference between RCTs and non-RCTs. At last follow-up, 66% of patients were full responders to DBS therapy. Sensitivity analyses indicated a low likelihood of small study effect bias in reported outcomes. Secondary analysis revealed a 1 standardised effect size (Hedges' g) reduction in depressive scale symptoms. Both RCTs and non-RCTs were determined to have a predominantly low risk of bias. A strong evidence base supports DBS for TROCD in relieving both OCD and comorbid depression symptoms in appropriately selected patients.

In vivo probabilistic atlas of white matter tracts of the human subthalamic area combining track density imaging and optimized diffusion tractography

The human subthalamic area is a region of high anatomical complexity, tightly packed with tiny fiber bundles. Some of them, including the pallidothalamic, cerebello-thalamic, and mammillothalamic tracts, are relevant targets in functional neurosurgery for various brain diseases. Diffusion-weighted imaging-based tractography has been suggested as a useful tool to map white matter pathways in the human brain in vivo and non-invasively, though the reconstruction of these specific fiber bundles is challenging due to their small dimensions and complex anatomy. To the best of our knowledge, a population-based, in vivo probabilistic atlas of subthalamic white matter tracts is still missing. In the present work, we devised an optimized tractography protocol for reproducible reconstruction of the tracts of subthalamic area in a large data sample from the Human Connectome Project repository. First, we leveraged the super-resolution properties and high anatomical detail provided by short tracks track-density imaging (stTDI) to identify the white matter bundles of the subthalamic area on a group-level template. Tracts identification on the stTDI template was also aided by visualization of histological sections of human specimens. Then, we employed this anatomical information to drive tractography at the subject-level, optimizing tracking parameters to maximize between-subject and within-subject similarities as well as anatomical accuracy. Finally, we gathered subject level tracts reconstructed with optimized tractography into a large-scale, normative population atlas. We suggest that this atlas could be useful in both clinical anatomy and functional neurosurgery settings, to improve our understanding of the complex morphology of this important brain region.

Repeating patterns: Predictive processing suggests an aesthetic learning role of the basal ganglia in repetitive stereotyped behaviors

Recurrent, unvarying, and seemingly purposeless patterns of action and cognition are part of normal development, but also feature prominently in several neuropsychiatric conditions. Repetitive stereotyped behaviors (RSBs) can be viewed as exaggerated forms of learned habits and frequently correlate with alterations in motor, limbic, and associative basal ganglia circuits. However, it is still unclear how altered basal ganglia feedback signals actually relate to the phenomenological variability of RSBs. Why do behaviorally overlapping phenomena sometimes require different treatment approaches−for example, sensory shielding strategies versus exposure therapy for autism and obsessive-compulsive disorder, respectively? Certain clues may be found in recent models of basal ganglia function that extend well beyond action selection and motivational control, and have implications for sensorimotor integration, prediction, learning under uncertainty, as well as aesthetic learning. In this paper, we systematically compare three exemplary conditions with basal ganglia involvement, obsessive-compulsive disorder, Parkinson’s disease, and autism spectrum conditions, to gain a new understanding of RSBs. We integrate clinical observations and neuroanatomical and neurophysiological alterations with accounts employing the predictive processing framework. Based on this review, we suggest that basal ganglia feedback plays a central role in preconditioning cortical networks to anticipate self-generated, movement-related perception. In this way, basal ganglia feedback appears ideally situated to adjust the salience of sensory signals through precision weighting of (external) new sensory information, relative to the precision of (internal) predictions based on prior generated models. Accordingly, behavioral policies may preferentially rely on new data versus existing knowledge, in a spectrum spanning between novelty and stability. RSBs may then represent compensatory or reactive responses, respectively, at the opposite ends of this spectrum. This view places an important role of aesthetic learning on basal ganglia feedback, may account for observed changes in creativity and aesthetic experience in basal ganglia disorders, is empirically testable, and may inform creative art therapies in conditions characterized by stereotyped behaviors.

Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study

BACKGROUND

Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity.

OBJECTIVE

The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement.

METHODS

We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways.

RESULTS

The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort.

CONCLUSION

Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with DBS.

Deep brain stimulation for extreme behaviors associated with autism spectrum disorder converges on a common pathway: a systematic review and connectomic analysis

OBJECTIVE

Individuals with autism spectrum disorder (ASD) may display extreme behaviors such as self-injury or aggression that often become refractory to psychopharmacology or behavioral intervention. Deep brain stimulation (DBS) is a surgical alternative that modulates brain circuits that have yet to be clearly elucidated. In the current study the authors performed a connectomic analysis to identify brain circuitry engaged by DBS for extreme behaviors associated with ASD.

METHODS

A systematic review was performed to identify prior reports of DBS as a treatment for extreme behaviors in patients with ASD. Individual patients' perioperative imaging was collected from corresponding authors. DBS electrode localization and volume of tissue activated modeling were performed. Volumes of tissue activated were used as seed points in high-resolution normative functional and structural imaging templates. The resulting individual functional and structural connectivity maps were pooled to identify networks and pathways that are commonly engaged by all targets.

RESULTS

Nine patients with ASD who were receiving DBS for symptoms of aggression or self-injurious behavior were identified. All patients had some clinical improvement with DBS. Connectomic analysis of 8 patients (from the systematic review and unpublished clinical data) demonstrated a common anatomical area of shared circuitry within the anterior limb of the internal capsule. Functional analysis of 4 patients identified a common network of distant brain areas including the amygdala, insula, and anterior cingulate engaged by DBS.

CONCLUSIONS

This study presents a comprehensive synopsis of the evidence for DBS in the treatment of extreme behaviors associated with ASD. Using network mapping, the authors identified key circuitry common to DBS targets.

Connectivity in deep brain stimulation for self-injurious behavior: multiple targets for a common network?

Self-injurious behavior (SIB) is associated with diverse psychiatric conditions. Sometimes (e.g., in patients with autism spectrum disorder or acquired brain injuries), SIB is the most dominant symptom, severely restricting the psychosocial functioning and quality of life of the patients and inhibiting appropriate patient care. In severe cases, it can lead to permanent physical injuries or even death. Primary therapy consists of medical treatment and if implementable, behavioral therapy. For patients with severe SIB refractory to conventional therapy, neuromodulation can be considered as a last recourse. In scientific literature, several successful lesioning and deep brain stimulation targets have been described that can indicate a common underlying neuronal pathway. The objectives of this study were to evaluate the short- and long-term clinical outcome of patients with severe, therapy refractory SIB who underwent DBS with diverse underlying psychiatric disorders and to correlate these outcomes with the activated connectivity networks. We retrospectively analyzed 10 patients with SIB who underwent DBS surgery with diverse psychiatric conditions including autism spectrum disorder, organic personality disorder after hypoxic or traumatic brain injury or Tourette syndrome. DBS targets were chosen according to the underlying disorder, patients were either stimulated in the nucleus accumbens, amygdala, posterior hypothalamus, medial thalamus or ventrolateral thalamus. Clinical outcome was measured 6 months after surgery and at long-term follow-up after 10 or more years using the Early Rehabilitation Barthel index (ERBI) and time of restraint. Connectivity patterns were analyzed using normative connectome. Based on previous literature the orbitofrontal cortex, superior frontal gyrus, the anterior cingulate cortex, the amygdala and the hippocampus were chosen as regions of interest. This analysis showed a significant improvement in the functionality of the patients with DBS in the short- and long-term follow-up. Good clinical outcome correlated with higher connectivity to the amygdala and hippocampus. These findings may suggest a common pathway, which can be relevant when planning a surgical procedure in patients with SIB.

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.

Association of clinical outcomes and connectivity in awake versus asleep deep brain stimulation for Parkinson disease

OBJECTIVE

Deep brain stimulation (DBS) for Parkinson disease (PD) is traditionally performed with awake intraoperative testing and/or microelectrode recording. Recently, however, the procedure has been increasingly performed under general anesthesia with image-based verification. The authors sought to compare structural and functional networks engaged by awake and asleep PD-DBS of the subthalamic nucleus (STN) and correlate them with clinical outcomes.

METHODS

Levodopa equivalent daily dose (LEDD), pre- and postoperative motor scores on the Movement Disorders Society-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III), and total electrical energy delivered (TEED) at 6 months were retroactively assessed in patients with PD who received implants of bilateral DBS leads. In subset analysis, implanted electrodes were reconstructed using the Lead-DBS toolbox. Volumes of tissue activated (VTAs) were used as seed points in group volumetric and connectivity analysis.

RESULTS

The clinical courses of 122 patients (52 asleep, 70 awake) were reviewed. Operating room and procedure times were significantly shorter in asleep cases. LEDD reduction, MDS-UPDRS III score improvement, and TEED at the 6-month follow-up did not differ between groups. In subset analysis (n = 40), proximity of active contact, VTA overlap, and desired network fiber counts with motor STN correlated with lower DBS energy requirement and improved motor scores. Discriminative structural fiber tracts involving supplementary motor area, thalamus, and brainstem were associated with optimal clinical improvement. Areas of highest structural and functional connectivity with VTAs did not significantly differ between the two groups.

CONCLUSIONS

Compared to awake STN DBS, asleep procedures can achieve similarly optimal targeting-based on clinical outcomes, electrode placement, and connectivity estimates-in more efficient procedures and shorter operating room times.

Brain Connectomics

A central tenet of modern neuroscience is the conceptualization of the brain as a collection of complex networks or circuits with a shift away from traditional "localizationist" theories. Connectomics seeks to unravel these brain networks and their role in the pathophysiology of neurologic diseases. This article discusses the science of connectomics with the examples of its potential role in clinical medicine and neuromodulation in multiple disorders, such as essential tremor, Parkinson's disease, obsessive-compulsive disorder, and epilepsy.

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.

Deep brain stimulation in the bed nucleus of the stria terminalis: A symptom provocation study in patients with obsessive-compulsive disorder

BACKGROUND

Deep brain stimulation (DBS) is an emerging therapy for treatment-resistant obsessive-compulsive disorder (OCD), and several targets for electrode implantation and contact selection have been proposed, including the bed nucleus of the stria terminalis (BST). Selecting the active electrode contacts (patients typically have four to choose from in each hemisphere), and thus the main locus of stimulation, can be a taxing process. Here, we investigated whether contact selection based purely on their neuroanatomical position in the BST is a worthwhile approach. For the first time, we also compared the effects of uni- versus bilateral BST stimulation.

METHODS

Nine OCD patients currently receiving DBS participated in a double-blind, randomized symptom provocation study to compare no versus BST stimulation. Primary outcomes were anxiety and mood ratings in response to disorder-relevant trigger images, as well as ratings of obsessions, compulsions, tendency to avoid and overall wellbeing. Furthermore, we asked whether patients preferred the electrode contacts in the BST over their regular stimulation contacts as a new treatment setting after the end of the task.

RESULTS

We found no statistically significant group differences between the four conditions (no, left, right and bilateral BST stimulation). Exploratory analyses, as well as follow-up data, did indicate that (bilateral) bipolar stimulation in the BST was beneficial for some patients, particularly for those who had achieved unsatisfactory effects through the typical contact selection procedure.

CONCLUSIONS

Despite its limitations, this study suggests that selection of stimulation contacts in the BST is a viable option for DBS in treatment-resistant OCD patients.

Cortical-subcortical structural connections support transcranial magnetic stimulation engagement of the amygdala

The amygdala processes valenced stimuli, influences emotion, and exhibits aberrant activity across anxiety disorders, depression, and PTSD. Interventions modulating amygdala activity hold promise as transdiagnostic psychiatric treatments. In 45 healthy participants, we investigated whether transcranial magnetic stimulation (TMS) elicits indirect changes in amygdala activity when applied to ventrolateral prefrontal cortex (vlPFC), a region important for emotion regulation. Harnessing in-scanner interleaved TMS/functional MRI (fMRI), we reveal that vlPFC neurostimulation evoked acute and focal modulations of amygdala fMRI BOLD signal. Larger TMS-evoked changes in the amygdala were associated with higher fiber density in a vlPFC-amygdala white matter pathway when stimulating vlPFC but not an anatomical control, suggesting this pathway facilitated stimulation-induced communication between cortex and subcortex. This work provides evidence of amygdala engagement by TMS, highlighting stimulation of vlPFC-amygdala circuits as a candidate treatment for transdiagnostic psychopathology. More broadly, it indicates that targeting cortical-subcortical structural connections may enhance the impact of TMS on subcortical neural activity and, by extension, subcortex-subserved behaviors.

Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson's disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson's disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement vigor. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.

Lead-OR: a multimodal platform for deep brain stimulation surgery

Background:

Deep brain stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MERs) or local field potential recordings can be used to extend neuroanatomical information (defined by MRI) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced.

Methods:

Here, we present a tool that integrates resources from stereotactic planning, neuroimaging, MER, and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (N = 52) offline and present single-use cases of the real-time platform.

Results:

We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool.

Conclusions:

This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages.

Funding:

Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luft- und Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), and Foundation for OCD Research (FFOR).

Deep brain stimulation is an established therapy for patients with Parkinson’s disease and an emerging option for other neurological conditions. Electrodes are implanted deep in the brain to stimulate precise brain regions and control abnormal brain activity in those areas. The most common target for Parkinson’s disease, for instance, is a structure called the subthalamic nucleus, which sits at the base of the brain, just above the brain stem.

To ensure electrodes are placed correctly, surgeons use various sources of information to characterize the patient’s brain anatomy and decide on an implant site. These data include brain scans taken before surgery and recordings of brain activity taken during surgery to confirm the intended implant site. Sometimes, the brain activity signals from this last confirmation step may slightly alter surgical plans. It represents one of many challenges for clinical teams: to analyse, assimilate, and communicate data as it is collected during the procedure.

Oxenford et al. developed a software pipeline to aggregate the data surgeons use to implant electrodes. The open-source platform, dubbed Lead-OR, visualises imaging data and brain activity recordings (termed electrophysiology data) in real time. The current set-up integrates with commercial tools and existing software for surgical planning.

Oxenford et al. tested Lead-OR on data gathered retrospectively from 32 patients with Parkinson’s who had electrodes implanted in their subthalamic nucleus. The platform showed good agreement between imaging and electrophysiology data, although there were some unavoidable discrepancies, arising from limitations in the imaging pipeline and from the surgical procedure. Lead-OR was also able to correct for brain shift, which is where the brain moves ever so slightly in the skull.

With further validation, this proof-of-concept software could serve as a useful decision-making tool for surgical teams implanting electrodes for deep brain stimulation. In time, if implemented, its use could improve the accuracy of electrode placement, translating into better surgical outcomes for patients. It also has the potential to integrate forthcoming ultra-high-resolution data from current brain mapping projects, and other commercial surgical planning tools.

Imaging versus electrographic connectivity in human mood-related fronto-temporal networks

BACKGROUND

The efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.

OBJECTIVE

Leverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.

METHODS

Evoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.

RESULTS

Evoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.

CONCLUSION

The two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation.

Deep brain stimulation for treatment-refractory obsessive-compulsive disorder should be an accepted therapy in Australia

Deep brain stimulation has shown promise for the treatment of severe, treatment-refractory obsessive-compulsive disorder. With the recent publication of the first Australian, randomised, sham-controlled trial of deep brain stimulation for obsessive-compulsive disorder, there are now four placebo-controlled trials demonstrating the efficacy of this therapy. Together with recent data identifying a biological substrate of effective stimulation that can predict response and that has been successfully reproduced, studies comparing and finding equivalent efficacy among different targets, as well as recent, large, open trials supporting the long-term effectiveness of deep brain stimulation, we argue that this should now be considered an accepted therapy for a select group of patients in the Australasian setting. We call on the Royal Australian and New Zealand College of Psychiatrists to revise their memorandum describing deep brain stimulation for obsessive-compulsive disorder as an 'experimental' treatment and recognise that it has proven efficacy. We stress that this should remain a therapy offered only to those with high treatment-refractory illnesses and only at specialised centres where there is an experienced multidisciplinary team involved in work-up, implantation and follow-up and also where frameworks are in place to provide careful clinical governance and ensure appropriate fully informed consent.

In situ polymerization of conducting polymers around living neural cells: Cellular effect study

Conducting polymer has been directly polymerized around living neural cells or in the cortex with the aim of creating an intimate contact between implantable electrical devices and electrogenetic cells. The long term cellular effect after conductive polymer coating, a critical issue for practical applications, has not been reported. In this study, poly(3,4-ethylenedioxythiophene) PEDOT was directly polymerized around the living primary neural and PC12 cells under varying current densities, potentials and charge-balanced current pulses. The cell morphology, nuclei evolution, and cell viability post PEDOT polymerization were studied at different time points. The aim of this study was to investigate the immediate and long-term cellular response towards in-situ polymerization of conductive polymers and to provide experimental information on the feasibility of this technique in practical applications.

White Matter Tracts Associated With Deep Brain Stimulation Targets in Major Depressive Disorder: A Systematic Review

Background

Deep brain stimulation (DBS) has been proposed as a last-resort treatment for major depressive disorder (MDD) and has shown potential antidepressant effects in multiple clinical trials. However, the clinical effects of DBS for MDD are inconsistent and suboptimal, with 30-70% responder rates. The currently used DBS targets for MDD are not individualized, which may account for suboptimal effect.

Objective

We aim to review and summarize currently used DBS targets for MDD and relevant diffusion tensor imaging (DTI) studies.

Methods

A literature search of the currently used DBS targets for MDD, including clinical trials, case reports and anatomy, was performed. We also performed a literature search on DTI studies in MDD.

Results

A total of 95 studies are eligible for our review, including 51 DBS studies, and 44 DTI studies. There are 7 brain structures targeted for MDD DBS, and 9 white matter tracts with microstructural abnormalities reported in MDD. These DBS targets modulate different brain regions implicated in distinguished dysfunctional brain circuits, consistent with DTI findings in MDD.

Conclusions

In this review, we propose a taxonomy of DBS targets for MDD. These results imply that clinical characteristics and white matter tracts abnormalities may serve as valuable supplements in future personalized DBS for MDD.

Deep Brain Stimulation of the Nucleus Accumbens in Severe Enduring Anorexia Nervosa: A Pilot Study

Introduction

Anorexia nervosa (AN) is one of the most debilitating psychiatric disorders, becoming severe and enduring in a third of cases; with few effective treatments. Deep brain stimulation is a reversible, adjustable neurosurgical procedure that has been gaining ground in psychiatry as a treatment for depression and obsessive-compulsive disorder, yet few studies have investigated AN. Abnormal eating behavior and the compulsive pursuit of thinness in AN is, in part, a consequence of dysfunction in reward circuitry and the nucleus accumbens (NAcc) is central to reward processing.

Methods

Phase 1 prospective open-label pilot study of seven individuals with severe enduring AN. Electrodes were implanted bilaterally into the NAcc with stimulation at the anterior limb of the internal capsule using rechargeable implantable pulse generators. The protocol of 15 months included 12 months of deep brain stimulation incorporating two consecutive, randomized blind on-off fortnights 9 months after stimulation onset. The primary objectives were to investigate safety and feasibility, together with changes in eating disorder psychopathology.

Results

Feasibility and safety was demonstrated with no serious adverse events due to deep brain stimulation. Three patients responded to treatment [defined as > 35% reduction in Eating Disorders Examination (EDE) score at 12 months] and four patients were non-responders. Responders had a statistically significant mean reduction in EDE scores (50.3% reduction; 95% CI 2.6-98.2%), Clinical Impairment Assessment (45.6% reduction; 95% CI 7.4-83.7%). Responders also had a statistically significant mean reduction in Hamilton Depression Scale, Hamilton Anxiety Scale and Snaith-Hamilton pleasure scale. There were no statistically significant changes in Body Mass Index, Yale-Brown-Cornell Eating Disorder Scale, Yale-Brown Obsessive-Compulsive Scale and World Health Organization Quality of Life Psychological subscale.

Conclusion

This study provides some preliminary indication that deep brain stimulation to the NAcc. Might potentially improve some key features of enduring AN. In this small study, the three responders had comorbid obsessive-compulsive disorder which predated AN diagnosis. Future studies should aim to further elucidate predictors of outcome.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [Project ID 128658].

Causal mapping of human brain function

Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments.

Probing responses to deep brain stimulation with functional magnetic resonance imaging

BACKGROUND

Deep brain stimulation (DBS) is an established treatment for certain movement disorders and has additionally shown promise for various psychiatric, cognitive, and seizure disorders. However, the mechanisms through which stimulation exerts therapeutic effects are incompletely understood. A technique that may help to address this knowledge gap is functional magnetic resonance imaging (fMRI). This is a non-invasive imaging tool which permits the observation of DBS effects in vivo.

OBJECTIVE

The objective of this review was to provide a comprehensive overview of studies in which fMRI during active DBS was performed, including studied disorders, stimulated brain regions, experimental designs, and the insights gleaned from stimulation-evoked fMRI responses.

METHODS

We conducted a systematic review of published human studies in which fMRI was performed during active stimulation in DBS patients. The search was conducted using PubMED and MEDLINE.

RESULTS

The rate of fMRI DBS studies is increasing over time, with 37 studies identified overall. The median number of DBS patients per study was 10 (range = 1-67, interquartile range = 11). Studies examined fMRI responses in various disease cohorts, including Parkinson's disease (24 studies), essential tremor (3 studies), epilepsy (3 studies), obsessive-compulsive disorder (2 studies), pain (2 studies), Tourette syndrome (1 study), major depressive disorder, anorexia, and bipolar disorder (1 study), and dementia with Lewy bodies (1 study). The most commonly stimulated brain region was the subthalamic nucleus (24 studies). Studies showed that DBS modulates large-scale brain networks, and that stimulation-evoked fMRI responses are related to the site of stimulation, stimulation parameters, patient characteristics, and therapeutic outcomes. Finally, a number of studies proposed fMRI-based biomarkers for DBS treatment, highlighting ways in which fMRI could be used to confirm circuit engagement and refine DBS therapy.

CONCLUSION

A review of the literature reflects an exciting and expanding field, showing that the combination of DBS and fMRI represents a uniquely powerful tool for simultaneously manipulating and observing neural circuitry. Future work should focus on relatively understudied disease cohorts and stimulated regions, while focusing on the prospective validation of putative fMRI-based biomarkers.

Role of deep brain stimulation in management of psychiatric disorders

Nowadays, most of patients affected by psychiatric disorders are successfully treated with conservative therapies. Still, a variable percentage of them demonstrate resistance to conventional treatments, and alternative methods can then be considered. During the last 20 years, there is a progressive interest in use of deep brain stimulation (DBS) in mental illnesses. It has become clear nowadays, that this modality may be effectively applied under specific indications in some patients with major depressive disorder, obsessive-compulsive disorder, anorexia nervosa and other eating disorders, Tourette syndrome, schizophrenia, substance use disorder, and even pathologically aggressive behavior. Despite the fact that the efficacy of neuromodulation with DBS, as well as of various lesional interventions, in cases of mental illnesses is still not fully established, there are several premises for wider applications of such "unclassical" psychiatric treatments in the future. Novel technologies of DBS, developments in non-invasive lesioning using stereotactic radiosurgery and transcranial magnetic resonance-guided focused ultrasound, and advances of neurophysiological and neuroimaging modalities may bolster further clinical applications of psychiatric neurosurgery, improve its results, and allow for individually selected treatment strategies tailored to specific needs of the patient.

Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia

We studied deep brain stimulation effects in two types of dystonia and conclude that different specific connections between the pallidum and thalamus are responsible for optimal treatment effects. Since alternative treatment options for dystonia beyond deep brain stimulation are scarce, our results will be crucial to maximize treatment outcome in this population of patients.

Dystonia is a debilitating disease with few treatment options. One effective option is deep brain stimulation (DBS) to the internal pallidum. While cervical and generalized forms of isolated dystonia have been targeted with a common approach to the posterior third of the nucleus, large-scale investigations regarding optimal stimulation sites and potential network effects have not been carried out. Here, we retrospectively studied clinical results following DBS for cervical and generalized dystonia in a multicenter cohort of 80 patients. We model DBS electrode placement based on pre- and postoperative imaging and introduce an approach to map optimal stimulation sites to anatomical space. Second, we investigate which tracts account for optimal clinical improvements, when modulated. Third, we investigate distributed stimulation effects on a whole-brain functional connectome level. Our results show marked differences of optimal stimulation sites that map to the somatotopic structure of the internal pallidum. While modulation of the striatopallidofugal axis of the basal ganglia accounted for optimal treatment of cervical dystonia, modulation of pallidothalamic bundles did so in generalized dystonia. Finally, we show a common multisynaptic network substrate for both phenotypes in the form of connectivity to the cerebellum and somatomotor cortex. Our results suggest a brief divergence of optimal stimulation networks for cervical vs. generalized dystonia within the pallidothalamic loop that merge again on a thalamo-cortical level and share a common whole-brain network.

Past, Present, and Future of Deep Brain Stimulation: Hardware, Software, Imaging, Physiology and Novel Approaches

Deep brain stimulation (DBS) has advanced treatment options for a variety of neurologic and neuropsychiatric conditions. As the technology for DBS continues to progress, treatment efficacy will continue to improve and disease indications will expand. Hardware advances such as longer-lasting batteries will reduce the frequency of battery replacement and segmented leads will facilitate improvements in the effectiveness of stimulation and have the potential to minimize stimulation side effects. Targeting advances such as specialized imaging sequences and “connectomics” will facilitate improved accuracy for lead positioning and trajectory planning. Software advances such as closed-loop stimulation and remote programming will enable DBS to be a more personalized and accessible technology. The future of DBS continues to be promising and holds the potential to further improve quality of life. In this review we will address the past, present and future of DBS.

Toward personalized medicine in connectomic deep brain stimulation

At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.

Seed-Based Connectivity Prediction of Initial Outcome of Subthalamic Nuclei Deep Brain Stimulation

Subthalamic nuclei deep brain stimulation (STN-DBS) is a well-established treatment for Parkinson's disease (PD). Some studies have confirmed the long-term efficacy is associated with brain connectivity; however, whether the initial outcome is associated with brain connectivity and efficacy of prediction based on these factors has not been well investigated. In the present study, a total of 98 patients were divided into a training set (n = 78) and a test set (n = 20). The stimulation and medication responses were calculated based on the motor performance. The functional and structural connectomes were established based on a public database and used to measure the association between stimulation response and brain connectivity. The prediction of initial outcome was achieved via a machine learning algorithm-support vector machine based on the model established with the training set. It was found that the initial outcome of STN-DBS was associated with functional/structural connectivities between the volume of tissue activated and multiple brain regions, including the supplementary motor area, precentral and frontal areas, cingulum, temporal cortex, and striatum. These factors could be used to predict the initial outcome, with an r value of 0.4978 (P = 0.0255). Our study demonstrates a correlation between a specific connectivity pattern and initial outcome of STN-DBS, which could be used to predict the initial outcome of DBS.

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

Deep brain stimulation (DBS) of the ventral internal capsule/ventral striatum (VCVS) is an emerging treatment for obsessive-compulsive disorder (OCD). Recently, multiple studies using normative connectomes have correlated DBS outcomes to stimulation of specific white matter tracts. Those studies did not test whether these correlations are clinically predictive, and did not apply cross-validation approaches that are necessary for biomarker development. Further, they did not account for the possibility of systematic differences between DBS patients and the non-diagnosed controls used in normative connectomes. To address these gaps, we performed patient-specific diffusion imaging in 8 patients who underwent VCVS DBS for OCD. We delineated tracts connecting thalamus and subthalamic nucleus (STN) to prefrontal cortex via VCVS. We then calculated which tracts were likely activated by individual patients' DBS settings. We fit multiple statistical models to predict both OCD and depression outcomes from tract activation. We further attempted to predict hypomania, a VCVS DBS complication. We assessed all models' performance on held-out test sets. With this best-practices approach, no model predicted OCD response, depression response, or hypomania above chance. Coefficient inspection partly supported prior reports, in that capture of tracts projecting to cingulate cortex was associated with both YBOCS and MADRS response. In contrast to prior reports, however, tracts connected to STN were not reliably correlated with response. Thus, patient-specific imaging and a guideline-adherent analysis were unable to identify a tractographic target with sufficient effect size to drive clinical decision-making or predict individual outcomes. These findings suggest caution in interpreting the results of normative connectome studies.

Longitudinal thalamic white and grey matter changes associated with visual hallucinations in Parkinson's disease

OBJECTIVE

Visual hallucinations are common in Parkinson's disease (PD) and associated with worse outcomes. Large-scale network imbalance is seen in PD-associated hallucinations, but mechanisms remain unclear. As the thalamus is critical in controlling cortical networks, structural thalamic changes could underlie network dysfunction in PD hallucinations.

METHODS

We used whole-brain fixel-based analysis and cortical thickness measures to examine longitudinal white and grey matter changes in 76 patients with PD (15 hallucinators, 61 non-hallucinators) and 26 controls at baseline, and after 18 months. We compared white matter and cortical thickness, adjusting for age, gender, time-between-scans and intracranial volume. To assess thalamic changes, we extracted volumes for 50 thalamic subnuclei (25 each hemisphere) and mean fibre cross-section (FC) for white matter tracts originating in each subnucleus and examined longitudinal change in PD-hallucinators versus non-hallucinators.

RESULTS

PD hallucinators showed white matter changes within the corpus callosum at baseline and extensive posterior tract involvement over time. Less extensive cortical thickness changes were only seen after follow-up. White matter connections from the right medial mediodorsal magnocellular thalamic nucleus showed reduced FC in PD hallucinators at baseline followed by volume reductions longitudinally. After follow-up, almost all thalamic subnuclei showed tract losses in PD hallucinators compared with non-hallucinators.

INTERPRETATION

PD hallucinators show white matter loss particularly in posterior connections and in thalamic nuclei, over time with relatively preserved cortical thickness. The right medial mediodorsal thalamic nucleus shows both connectivity and volume loss in PD hallucinations. Our findings provide mechanistic insights into the drivers of network imbalance in PD hallucinations and potential therapeutic targets.

Common and differential connectivity profiles of deep brain stimulation and capsulotomy in refractory obsessive-compulsive disorder

Neurosurgical interventions including deep brain stimulation (DBS) and capsulotomy have been demonstrated effective for refractory obsessive-compulsive disorder (OCD), although treatment-shared/-specific network mechanisms remain largely unclear. We retrospectively analyzed resting-state fMRI data from three cohorts: a cross-sectional dataset of 186 subjects (104 OCD and 82 healthy controls), and two longitudinal datasets of refractory patients receiving ventral capsule/ventral striatum DBS (14 OCD) and anterior capsulotomy (27 OCD). We developed a machine learning model predictive of OCD symptoms (indexed by the Yale-Brown Obsessive Compulsive Scale, Y-BOCS) based on functional connectivity profiles and used graphic measures of network communication to characterize treatment-induced profile changes. We applied a linear model on 2 levels treatments (DBS or capsulotomy) and outcome to identify whether pre-surgical network communication was associated with differential treatment outcomes. We identified 54 functional connectivities within fronto-subcortical networks significantly predictive of Y-BOCS score in patients across 3 independent cohorts, and observed a coexisting pattern of downregulated cortico-subcortical and upregulated cortico-cortical network communication commonly shared by DBS and capsulotomy. Furthermore, increased cortico-cortical communication at ventrolateral and centrolateral prefrontal cortices induced by DBS and capsulotomy contributed to improvement of mood and anxiety symptoms, respectively (p < 0.05). Importantly, pretreatment communication of ventrolateral and centrolateral prefrontal cortices were differentially predictive of mood and anxiety improvements by DBS and capsulotomy (effect sizes = 0.45 and 0.41, respectively). These findings unravel treatment-shared and treatment-specific network characteristics induced by DBS and capsulotomy, which may facilitate the search of potential evidence-based markers for optimally selecting among treatment options for a patient.

Deep brain stimulation electrode modeling in rats

Deep Brain Stimulation (DBS) is an efficacious treatment option for an increasing range of brain disorders. To enhance our knowledge about the mechanisms of action of DBS and to probe novel targets, basic research in animal models with DBS is an essential research base. Beyond nonhuman primate, pig, and mouse models, the rat is a widely used animal model for probing DBS effects in basic research. Reconstructing DBS electrode placement after surgery is crucial to associate observed effects with modulating a specific target structure. Post-mortem histology is a commonly used method for reconstructing the electrode location. In humans, however, neuroimaging-based electrode localizations have become established. For this reason, we adapt the open-source software pipeline Lead-DBS for DBS electrode localizations from humans to the rat model. We validate our localization results by inter-rater concordance and a comparison with the conventional histological method. Finally, using the open-source software pipeline OSS-DBS, we demonstrate the subject-specific simulation of the VTA and the activation of axon models aligned to pathways representing neuronal fibers, also known as the pathway activation model. Both activation models yield a characterization of the impact of DBS on the target area. Our results suggest that the proposed neuroimaging-based method can precisely localize DBS electrode placements that are essentially rater-independent and yield results comparable to the histological gold standard. The advantages of neuroimaging-based electrode localizations are the possibility of acquiring them in vivo and combining electrode reconstructions with advanced imaging metrics, such as those obtained from diffusion or functional magnetic resonance imaging (MRI). This paper introduces a freely available open-source pipeline for DBS electrode reconstructions in rats. The presented initial validation results are promising.

Functional Approaches to the Surgery of Brain Gliomas

In the surgery of gliomas, recent years have witnessed unprecedented theoretical and technical development, which extensively increased indication to surgery. On one hand, it has been solidly demonstrated the impact of gross total resection on life expectancy. On the other hand, the paradigm shift from classical cortical localization of brain function towards connectomics caused by the resurgence of awake surgery and the advent of tractography has permitted safer surgeries focused on subcortical white matter tracts preservation and allowed for surgical resections within regions, such as Broca's area or the primary motor cortex, which were previously deemed inoperable. Furthermore, new asleep electrophysiological techniques have been developed whenever awake surgery is not an option, such as operating in situations of poor compliance (including paediatric patients) or pre-existing neurological deficits. One such strategy is the use of intraoperative neurophysiological monitoring (IONM), enabling the identification and preservation of functionally defined, but anatomically ambiguous, cortico-subcortical structures through mapping and monitoring techniques. These advances tie in with novel challenges, specifically risk prediction and the impact of neuroplasticity, the indication for tumour resection beyond visible borders, or supratotal resection, and most of all, a reappraisal of the importance of the right hemisphere from early psychosurgery to mapping and preservation of social behaviour, executive control, and decision making.Here we review current advances and future perspectives in a functional approach to glioma surgery.

Prefrontal connectomics: from anatomy to human imaging

The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic "hard wiring" first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas.

Circuit-Targeted Neuromodulation for Anhedonia

Despite the prevalence of anhedonia across multiple psychiatric disorders, its relevance to treatment selection and prognostication can be unclear (Davey et al., Psychol Med 42(10):2071-81, 2012). Given the challenges in pharmacological and psychosocial treatment, there has been increasing attention devoted to neuroanatomically-targeted treatments. This chapter will present a brief introduction to circuit-targeted therapeutics in psychiatry (Sect. 1), an overview of brain mapping as it relates to anhedonia (Sect. 2), a review of existing studies on brain stimulation for anhedonia (Sect. 3), and a description of emerging approaches to circuit-based neuromodulation for anhedonia (Sect. 4).

The prefrontal cortex and neurosurgical treatment for intractable OCD

Over the past two decades, circuit-based neurosurgical procedures have gained increasing acceptance as a safe and efficacious approach to the treatment of the intractable obsessive-compulsive disorder (OCD). Lesions and deep brain stimulation (DBS) of the longitudinal corticofugal white matter tracts connecting the prefrontal cortex with the striatum, thalamus, subthalamic nucleus (STN), and brainstem implicate orbitofrontal, medial prefrontal, frontopolar, and ventrolateral cortical networks in the symptoms underlying OCD. The highly parallel distributed nature of these networks may explain the relative lack of adverse effects observed following surgery. Additional pre-post studies of cognitive tasks in more surgical patients are needed to confirm the role of these networks in OCD and to define therapeutic responses to surgical intervention.

3 T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation

Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS), a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While SCC-DBS drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 Tesla functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of twelve patients with fully implanted SCC-DBS devices. Four additional SCC-DBS patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n=78 acquisitions overall) during i) inactive DBS; ii) clinically optimal active DBS; iii) suboptimal active DBS. All scans were acquired within a single MRI session, each separated by a 5-minute washout period. Analysis of the amplitude of low frequency fluctuations (ALFF) in each sequence indicated that clinically optimal SCC-DBS reduced spontaneous brain activity in several areas, including bilateral dorsal anterior cingulate cortex (dACC), posterior cingulate cortex (PCC), precuneus, and left inferior parietal lobule (pBonferroni<0.0001). Stimulation-induced dACC signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings, and related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dACC, PCC, and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated ALFF changes in these three areas (along with pre-operative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally all three brain areas exhibited significant changes in functional connectivity between active and inactive DBS states (pBonferroni<0.01). These results provide insight into the network-level mechanisms of SCC-DBS and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.

A Network-Based Approach to Glioma Surgery: Insights from Functional Neurosurgery

Simple Summary

This manuscript details the literature and discussion around revolutionizing the neurosurgeon’s approach to surgery for brain tumors by conceptualizing these tumors as entities within functional networks. We hope that the work detailed herein will aid in establishing neurosurgical paradigms to optimize planning for brain tumor surgery to improve functional outcomes for all patients.

Abstract

The evaluation and manipulation of structural and functional networks, which has been integral to advancing functional neurosurgery, is beginning to transcend classical subspecialty boundaries. Notably, its application in neuro-oncologic surgery has stimulated an exciting paradigm shift from the traditional localizationist approach, which is lacking in nuance and optimization. This manuscript reviews the existing literature and explores how structural and functional connectivity analyses have been leveraged to revolutionize and individualize pre-operative tumor evaluation and surgical planning. We describe how this novel approach may improve cognitive and neurologic preservation after surgery and attenuate tumor spread. Furthermore, we demonstrate how connectivity analysis combined with neuromodulation techniques can be employed to induce post-operative neuroplasticity and personalize neurorehabilitation. While the landscape of functional neuro-oncology is still evolving and requires further study to encourage more widespread adoption, this functional approach can transform the practice of neuro-oncologic surgery and improve the care and outcomes of patients with intra-axial tumors.

Long-term ecological assessment of intracranial electrophysiology synchronized to behavioral markers in obsessive-compulsive disorder

Detection of neural signatures related to pathological behavioral states could enable adaptive deep brain stimulation (DBS), a potential strategy for improving efficacy of DBS for neurological and psychiatric disorders. This approach requires identifying neural biomarkers of relevant behavioral states, a task best performed in ecologically valid environments. Here, in human participants with obsessive-compulsive disorder (OCD) implanted with recording-capable DBS devices, we synchronized chronic ventral striatum local field potentials with relevant, disease-specific behaviors. We captured over 1,000 h of local field potentials in the clinic and at home during unstructured activity, as well as during DBS and exposure therapy. The wide range of symptom severity over which the data were captured allowed us to identify candidate neural biomarkers of OCD symptom intensity. This work demonstrates the feasibility and utility of capturing chronic intracranial electrophysiology during daily symptom fluctuations to enable neural biomarker identification, a prerequisite for future development of adaptive DBS for OCD and other psychiatric disorders.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Obsessive-Compulsive Disorders

PURPOSE OF REVIEW

This article describes the phenomenology and clinical presentation of obsessive-compulsive disorder (OCD), a common but underdiagnosed psychiatric disorder. Guidance for effectively identifying obsessive-compulsive symptoms is provided, and treatment options, including psychotherapy, pharmacologic management, and neuromodulation approaches for treatment-resistant OCD, are discussed.

RECENT FINDINGS

OCD affects 2% to 3% of adults worldwide and is associated with substantial individual disability and societal costs. Lack of recognition of common OCD symptom types, in addition to shame and fear of stigma on the part of patients, has created an average delay in diagnosis by almost 10 years and a delay in effective treatment (ie, a treatment gap) of nearly 2 years. Cognitive-behavioral therapy (CBT), specifically a form of CBT that includes a type of behavioral intervention called exposure and response prevention, remains the most effective form of treatment for OCD. If CBT is not effective or not available, pharmacologic treatment with selective serotonin reuptake inhibitors (SSRIs) or clomipramine, a nonselective serotonin reuptake inhibitor, can also be of benefit. Neuromodulation approaches such as deep brain stimulation and transcranial magnetic stimulation are rapidly emerging as effective treatments for OCD, particularly for patients who have not experienced an adequate response to psychotherapy or pharmacologic management.

SUMMARY

OCD affects more than one in every 50 adults in the United States but is recognized and adequately treated in fewer than half of those affected. Early intervention and appropriate treatment can substantially reduce OCD symptom severity, improve quality of life, and minimize the functional disability associated with this chronic and often debilitating illness.