Test-retest reliability of a stimulation-locked evoked response to deep brain stimulation in subcallosal cingulate for treatment resistant depression

Proceedings of the 12th annual deep brain stimulation think tank: cutting edge technology meets novel applications

The Deep Brain Stimulation (DBS) Think Tank XII was held on August 21st to 23rd. This year we showcased groundbreaking advancements in neuromodulation technology, focusing heavily on the novel uses of existing technology as well as next-generation technology. Our keynote speaker shared the vision of using neuro artificial intelligence to predict depression using brain electrophysiology. Innovative applications are currently being explored in stroke, disorders of consciousness, and sleep, while established treatments for movement disorders like Parkinson's disease are being refined with adaptive stimulation. Neuromodulation is solidifying its role in treating psychiatric disorders such as depression and obsessive-compulsive disorder, particularly for patients with treatment-resistant symptoms. We estimate that 300,000 leads have been implanted to date for neurologic and neuropsychiatric indications. Magnetoencephalography has provided insights into the post-DBS physiological changes. The field is also critically examining the ethical implications of implants, considering the long-term impacts on clinicians, patients, and manufacturers.

What can neuroimaging of neuromodulation reveal about the basis of circuit therapies for psychiatry?

Neuromodulation is increasingly becoming a therapeutic option for treatment resistant psychiatric disorders. These non-invasive and invasive therapies are still being refined but are clinically effective and, in some cases, provide sustained symptom reduction. Neuromodulation relies on changing activity within a specific brain region or circuit, but the precise mechanisms of action of these therapies, is unclear. Here we review work in both humans and animals that has provided insight into how therapies such as deep brain and transcranial magnetic stimulation alter neural activity across the brain. We focus on studies that have combined neuromodulation with neuroimaging such as PET and MRI as these measures provide detailed information about the distributed networks that are modulated and thus insight into both the mechanisms of action of neuromodulation but also potentially the basis of psychiatric disorders. Further we highlight work in nonhuman primates that has revealed how neuromodulation changes neural activity at different scales from single neuron activity to functional connectivity, providing key insight into how neuromodulation influences the brain. Ultimately, these studies highlight the value of combining neuromodulation with neuroimaging to reveal the mechanisms through which these treatments influence the brain, knowledge vital for refining targeted neuromodulation therapies for psychiatric disorders.

Nanomedicine in Neuroprotection, Neuroregeneration, and Blood-Brain Barrier Modulation: A Narrative Review

Nanomedicine is a newer, promising approach to promote neuroprotection, neuroregeneration, and modulation of the blood-brain barrier. This review includes the integration of various nanomaterials in neurological disorders. In addition, gelatin-based hydrogels, which have huge potential due to biocompatibility, maintenance of porosity, and enhanced neural process outgrowth, are reviewed. Chemical modification of these hydrogels, especially with guanidine moieties, has shown improved neuron viability and underscores tailored biomaterial design in neural applications. This review further discusses strategies to modulate the blood-brain barrier-a factor critically associated with the effective delivery of drugs to the central nervous system. These advances bring supportive solutions to the solving of neurological conditions and innovative therapies for their treatment. Nanomedicine, as applied to neuroscience, presents a significant leap forward in new therapeutic strategies that might help raise the treatment and management of neurological disorders to much better levels. Our aim was to summarize the current state-of-knowledge in this field.

Densely sampled stimulus-response map of human cortex with single pulse TMS-EEG and its relation to whole brain neuroimaging measures

Large-scale networks underpin brain functions. How such networks respond to focal stimulation can help decipher complex brain processes and optimize brain stimulation treatments. To map such stimulation-response patterns across the brain non-invasively, we recorded concurrent EEG responses from single-pulse transcranial magnetic stimulation (i.e., TMS-EEG) from over 100 cortical regions with two orthogonal coil orientations from one densely-sampled individual. We also acquired Human Connectome Project (HCP)-styled diffusion imaging scans (six), resting-state functional Magnetic Resonance Imaging (fMRI) scans (120 mins), resting-state EEG scans (108 mins), and structural MR scans (T1- and T2-weighted). Using the TMS-EEG data, we applied network science-based community detection to reveal insights about the brain's causal-functional organization from both a stimulation and recording perspective. We also computed structural and functional maps and the electric field of each TMS stimulation condition. Altogether, we hope the release of this densely sampled (n=1) dataset will be a uniquely valuable resource for both basic and clinical neuroscience research.

Deep brain stimulation induces white matter remodeling and functional changes to brain-wide networks

Deep brain stimulation (DBS) is an emerging therapeutic option for treatment resistant neurological and psychiatric disorders, most notably depression. Despite this, little is known about the anatomical and functional mechanisms that underlie this therapy. Here we targeted stimulation to the white matter adjacent to the subcallosal anterior cingulate cortex (SCC-DBS) in macaques, modeling the location in the brain proven effective for depression. We demonstrate that SCC-DBS has a selective effect on white matter macro- and micro-structure in the cingulum bundle distant to where stimulation was delivered. SCC-DBS also decreased functional connectivity between subcallosal and posterior cingulate cortex, two areas linked by the cingulum bundle and implicated in depression. Our data reveal that white matter remodeling as well as functional effects contribute to DBS's therapeutic efficacy.

Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation

Subcallosal cingulate (SCC) deep brain stimulation (DBS) is an emerging therapy for refractory depression. Good clinical outcomes are associated with the activation of white matter adjacent to the SCC. This activation produces a signature cortical evoked potential (EP), but it is unclear which of the many pathways in the vicinity of SCC is responsible for driving this response. Individualized biophysical models were built to achieve selective engagement of two target bundles: either the forceps minor (FM) or cingulum bundle (CB). Unilateral 2 Hz stimulation was performed in seven patients with treatment-resistant depression who responded to SCC DBS, and EPs were recorded using 256-sensor scalp electroencephalography. Two distinct EPs were observed: a 120 ms symmetric response spanning both hemispheres and a 60 ms asymmetrical EP. Activation of FM correlated with the symmetrical EPs, while activation of CB was correlated with the asymmetrical EPs. These results support prior model predictions that these two pathways are predominantly activated by clinical SCC DBS and provide first evidence of a link between cortical EPs and selective fiber bundle activation.

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

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

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.

Whole brain network effects of subcallosal cingulate deep brain stimulation for treatment-resistant depression

Ongoing experimental studies of subcallosal cingulate deep brain stimulation (SCC DBS) for treatment-resistant depression (TRD) show a differential timeline of behavioral effects with rapid changes after initial stimulation, and both early and delayed changes over the course of ongoing chronic stimulation. This study examined the longitudinal resting-state regional cerebral blood flow (rCBF) changes in intrinsic connectivity networks (ICNs) with SCC DBS for TRD over 6 months and repeated the same analysis by glucose metabolite changes in a new cohort. A total of twenty-two patients with TRD, 17 [15 O]-water and 5 [18 F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) patients, received SCC DBS and were followed weekly for 7 months. PET scans were collected at 4-time points: baseline, 1-month after surgery, and 1 and 6 months of chronic stimulation. A linear mixed model was conducted to examine the differential trajectory of rCBF changes over time. Post-hoc tests were also examined to assess postoperative, early, and late ICN changes and response-specific effects. SCC DBS had significant time-specific effects in the salience network (SN) and the default mode network (DMN). The rCBF in SN and DMN was decreased after surgery, but responder and non-responders diverged thereafter, with a net increase in DMN activity in responders with chronic stimulation. Additionally, the rCBF in the DMN uniquely correlated with depression severity. The glucose metabolic changes in a second cohort show the same DMN changes. The trajectory of PET changes with SCC DBS is not linear, consistent with the chronology of therapeutic effects. These data provide novel evidence of both an acute reset and ongoing plastic effects in the DMN that may provide future biomarkers to track clinical improvement with ongoing treatment.

Advances in Deep Brain Stimulation: From Mechanisms to Applications

Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Whole Brain Network effects of subcallosal cingulate deep brain stimulation for treatment-resistant depression

Ongoing experimental studies of subcallosal cingulate deep brain stimulation (SCC DBS) for treatment-resistant depression (TRD) show a differential timeline of behavioral effects with rapid changes after initial stimulation, and both early and delayed changes over the course of ongoing chronic stimulation. This study examined the longitudinal resting-state regional cerebral blood ow (rCBF) changes in intrinsic connectivity networks (ICNs) with SCC DBS for TRD over 6 months and repeated the same analysis by glucose metabolite changes in a new cohort. A total of twenty-two patients with TRD, 17 [15O]-water and 5 [18]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) patients, received SCC DBS and were followed weekly for 7 months. PET scans were collected at 4-time points: baseline, 1-month after surgery, and 1 and 6 months of chronic stimulation. A linear mixed model was conducted to examine the differential trajectory of rCBF changes over time. Post-hoc tests were also examined to assess postoperative, early, and late ICN changes and response-specific effects. SCC DBS had significant time-specific effects in the salience network (SN) and the default mode network (DMN). The rCBF in SN and DMN was decreased after surgery, but responder and non-responders diverged thereafter, with a net increase in DMN activity in responders with chronic stimulation. Additionally, the rCBF in the DMN uniquely correlated with depression severity. The glucose metabolic changes in a second cohort show the same DMN changes. The trajectory of PET changes with SCC DBS is not linear, consistent with the chronology of therapeutic effects. These data provide novel evidence of both an acute reset and ongoing plastic effects in the DMN that may provide future biomarkers to track clinical improvement with ongoing treatment.

Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate

Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features—evoked power and phase clustering—in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50–150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4–7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2–4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology.

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.

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.

Dynamic Oscillations Evoked by Subcallosal Cingulate Deep Brain Stimulation

Deep brain stimulation (DBS) of subcallosal cingulate white matter (SCCwm) alleviates symptoms of depression, but its mechanistic effects on brain dynamics remain unclear. In this study we used novel intracranial recordings (LFP) in n = 6 depressed patients stimulated with DBS around the SCCwm target, observing a novel dynamic oscillation (DOs). We confirm that DOs in the LFP are of neural origin and consistently evoked within certain patients. We then characterize the frequency and dynamics of DOs, observing significant variability in DO behavior across patients. Under the hypothesis that LFP-DOs reflect network engagement, we characterize the white matter tracts associated with LFP-DO observations and report a preliminary observation of DO-like activity measured in a single patient's electroencephalography (dEEG). These results support further study of DOs as an objective signal for mechanistic study and connectomics guided DBS.

High-resolution Virtual Brain Modeling Personalizes Deep Brain Stimulation for Treatment-Resistant Depression: Spatiotemporal Response Characteristics Following Stimulation of Neural Fiber Pathways

Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesized to be an important factor in determining outcomes, however, the resulting individual network effects at the whole-brain scale remain largely unknown. Here we provide a computational framework that can explore each individual's brain response characteristics elicited by selective stimulation of fiber tracts. We use a novel personalized in-silico approach, the Virtual Big Brain, which makes use of high-resolution virtual brain models at a mm-scale and explicitly reconstructs more than 100 000 fiber tracts for each individual. Each fiber tract is active and can be selectively stimulated. Simulation results demonstrate distinct stimulus-induced event-related potentials as a function of stimulation location, parametrized by the contact positions of the electrodes implanted in each patient, even though validation against empirical patient data reveals some limitations (i.e., the need for individual parameter adjustment, and differential accuracy across stimulation locations). This study provides evidence for the capacity of personalized high-resolution virtual brain models to investigate individual network effects in DBS for patients with TRD and opens up novel avenues in the personalized optimization of brain stimulation.

Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation

BACKGROUND

Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated.

OBJECTIVE

Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings.

METHODS

Pathway activations were modeled in eleven patients using the latest advances in connectomic modeling of subthalamic DBS, focusing on the hyperdirect pathway (HDP) and corticospinal/bulbar tract (CSBT) for their relevance in human research studies. Correlations between pathway activations and respective EP amplitudes were quantified.

RESULTS

Good model performance required accurate lead localization and image fusions, as well as appropriate selection of fiber diameter in the biophysical model. While optimal model parameters varied across patients, good performance could be achieved using a global set of parameters that explained 60% and 73% of electrophysiologic activations of CSBT and HDP, respectively. Moreover, restricted models fit to only EP amplitudes of eight standard (monopolar and bipolar) electrode configurations were able to extrapolate variation in EP amplitudes across other directional electrode configurations and stimulation parameters, with no significant reduction in model performance across the cohort.

CONCLUSIONS

Our findings demonstrate that connectomic models of DBS with sufficient anatomical and electrical details can predict recruitment dynamics of white matter. These results will help to define connectomic modeling standards for preoperative surgical targeting and postoperative patient programming applications.

Predicting Response to Brain Stimulation in Depression: a Roadmap for Biomarker Discovery

PURPOSE OF REVIEW

Clinical response to brain stimulation treatments for depression is highly variable. A major challenge for the field is predicting an individual patient's likelihood of response. This review synthesises recent developments in neural predictors of response to targeted brain stimulation in depression. It then proposes a framework to evaluate the clinical potential of putative 'biomarkers'.

RECENT FINDINGS

Largely, developments in identifying putative predictors emerge from two approaches: data-driven, including machine learning algorithms applied to resting state or structural neuroimaging data, and theory-driven, including task-based neuroimaging. Theory-driven approaches can also yield mechanistic insight into the cognitive processes altered by the intervention.

SUMMARY

A pragmatic framework for discovery and testing of biomarkers of brain stimulation response in depression is proposed, involving (1) identification of a cognitive-neural phenotype; (2) confirming its validity as putative biomarker, including out-of-sample replicability and within-subject reliability; (3) establishing the association between this phenotype and treatment response and/or its modifiability with particular brain stimulation interventions via an early-phase randomised controlled trial RCT; and (4) multi-site RCTs of one or more treatment types measuring the generalisability of the biomarker and confirming the superiority of biomarker-selected patients over randomly allocated groups.

Deep Brain Stimulation Initiative: Toward Innovative Technology, New Disease Indications, and Approaches to Current and Future Clinical Challenges in Neuromodulation Therapy

Deep brain stimulation (DBS) is one of the most important clinical therapies for neurological disorders. DBS also has great potential to become a great tool for clinical neuroscience research. Recently, the National Engineering Laboratory for Neuromodulation at Tsinghua University held an international Deep Brain Stimulation Initiative workshop to discuss the cutting-edge technological achievements and clinical applications of DBS. We specifically addressed new clinical approaches and challenges in DBS for movement disorders (Parkinson's disease and dystonia), clinical application toward neurorehabilitation for stroke, and the progress and challenges toward DBS for neuropsychiatric disorders. This review highlighted key developments in (1) neuroimaging, with advancements in 3-Tesla magnetic resonance imaging DBS compatibility for exploration of brain network mechanisms; (2) novel DBS recording capabilities for uncovering disease pathophysiology; and (3) overcoming global healthcare burdens with online-based DBS programming technology for connecting patient communities. The successful event marks a milestone for global collaborative opportunities in clinical development of neuromodulation to treat major neurological disorders.

Deep brain stimulation for psychiatric disorders: From focal brain targets to cognitive networks

Deep brain stimulation (DBS) is a promising intervention for treatment-resistant psychiatric disorders, particularly major depressive disorder (MDD) and obsessive-compulsive disorder (OCD). Up to 90% of patients who have not recovered with therapy or medication have reported benefit from DBS in open-label studies. Response rates in randomized controlled trials (RCTs), however, have been much lower. This has been argued to arise from surgical variability between sites, and recent psychiatric DBS research has focused on refining targeting through personalized imaging. Much less attention has been given to the fact that psychiatric disorders arise from dysfunction in distributed brain networks, and that DBS likely acts by altering communication within those networks. This is in part because psychiatric DBS research relies on subjective rating scales that make it difficult to identify network biomarkers. Here, we overview recent DBS RCT results in OCD and MDD, as well as the follow-on imaging studies. We present evidence for a new approach to studying DBS' mechanisms of action, focused on measuring objective cognitive/emotional deficits that underpin these and many other mental disorders. Further, we suggest that a focus on cognition could lead to reliable network biomarkers at an electrophysiologic level, especially those related to inter-regional synchrony of the local field potential (LFP). Developing the network neuroscience of DBS has the potential to finally unlock the potential of this highly specific therapy.

A Decade of Progress in Deep Brain Stimulation of the Subcallosal Cingulate for the Treatment of Depression

Major depression contributes significantly to the global disability burden. Since the first clinical study of deep brain stimulation (DBS), over 446 patients with depression have now undergone this neuromodulation therapy, and 29 animal studies have investigated the efficacy of subgenual cingulate DBS for depression. In this review, we aim to provide a comprehensive overview of the progress of DBS of the subcallosal cingulate in humans and the medial prefrontal cortex, its rodent homolog. For preclinical animal studies, we discuss the various antidepressant-like behaviors induced by medial prefrontal cortex DBS and examine the possible mechanisms including neuroplasticity-dependent/independent cellular and molecular changes. Interestingly, the response rate of subcallosal cingulate Deep brain stimulation marks a milestone in the treatment of depression. DBS achieved response and remission rates of 64–76% and 37–63%, respectively, from clinical studies monitoring patients from 6–24 months. Although some studies showed its stimulation efficacy was limited, it still holds great promise as a therapy for patients with treatment-resistant depression. Overall, further research is still needed, including more credible clinical research, preclinical mechanistic studies, precise selection of patients, and customized electrical stimulation paradigms.

From bed to bench side: Reverse translation to optimize neuromodulation for mood disorders

The advent of neuroimaging has provided foundational insights into the neural basis of psychiatric conditions, such as major depression. Across countless studies, dysfunction has been localized to distinct parts of the limbic system. Specific knowledge about affected locations has led to the development of circuit modulation therapies to correct dysfunction, notably deep brain stimulation (DBS). This and other emerging neuromodulation approaches have shown great promise, but their refinement has been slow and fundamental questions about their mechanisms of action remain. Here, we argue that their continued development requires reverse translation to animal models with close homology to humans, namely, nonhuman primates. With a particular focus on DBS approaches for depression, we highlight the parts of the brain that have been targeted by neuromodulation in humans, their efficacy, and why nonhuman primates are the most suitable model in which to conduct their refinement. We finish by highlighting key gaps in our knowledge that need to be filled to allow more rapid progress toward effective therapies in patients for whom all other treatment attempts have failed.

Proceedings of the Sixth Deep Brain Stimulation Think Tank Modulation of Brain Networks and Application of Advanced Neuroimaging, Neurophysiology, and Optogenetics

The annual deep brain stimulation (DBS) Think Tank aims to create an opportunity for a multidisciplinary discussion in the field of neuromodulation to examine developments, opportunities and challenges in the field. The proceedings of the Sixth Annual Think Tank recapitulate progress in applications of neurotechnology, neurophysiology, and emerging techniques for the treatment of a range of psychiatric and neurological conditions including Parkinson’s disease, essential tremor, Tourette syndrome, epilepsy, cognitive disorders, and addiction. Each section of this overview provides insight about the understanding of neuromodulation for specific disease and discusses current challenges and future directions. This year’s report addresses key issues in implementing advanced neurophysiological techniques, evolving use of novel modulation techniques to deliver DBS, ans improved neuroimaging techniques. The proceedings also offer insights into the new era of brain network neuromodulation and connectomic DBS to define and target dysfunctional brain networks. The proceedings also focused on innovations in applications and understanding of adaptive DBS (closed-loop systems), the use and applications of optogenetics in the field of neurostimulation and the need to develop databases for DBS indications. Finally, updates on neuroethical, legal, social, and policy issues relevant to DBS research are discussed.

Field potential 1/f activity in the subcallosal cingulate region as a candidate signal for monitoring deep brain stimulation for treatment-resistant depression

Subcallosal cingulate cortex deep brain stimulation (SCC-DBS) is an experimental therapy for treatment-resistant depression (TRD). Refinement and optimization of SCC-DBS will benefit from increased study of SCC electrophysiology in context of ongoing high-frequency SCC-DBS therapy. The study objective was a 7-mo observation of frequency-domain 1/f slope in off-stimulation local field potentials (SCC-LFPs) alongside standardized measurements of depression severity in 4 patients undergoing SCC-DBS. SCC was implanted bilaterally with a combined neurostimulation-LFP recording system. Following a 1-mo off-stimulation postoperative phase with multiple daily recordings, patients received bilateral SCC-DBS therapy (130 Hz, 90 μs) and weekly resting-state SCC-LFP recordings over a 6-mo treatment phase. 1/f slopes for each time point were estimated via linear regression of log-transformed Welch periodograms. General linear mixed-effects models were constructed to estimate pretreatment sources of 1/f slope variance, and 95% bootstrap confidence intervals were constructed to estimate treatment phase 1/f slope association with treatment response (50% decrease in preimplantation symptom severity). Results show the time of recording was a prominent source of pretreatment 1/f slope variance bilaterally, with increased 1/f slope magnitude observed during night hours (2300-0659). Increase in right 1/f slope was observed in the setting of treatment response, with bootstrap analysis supporting this observation in 3 of 4 subjects. We conclude that 1/f slope can be measured longitudinally in a combined SCC-DBS/LFP recording system and likely conforms to known 1/f circadian variability. The preliminary evidence of 1/f slope increase during treatment response suggests a potential utility as a candidate biomarker for ongoing development of adaptive TRD-neuromodulation strategies.NEW & NOTEWORTHY In four patients with treatment-resistant depression undergoing therapeutic deep brain stimulation (DBS), we present the first longitudinal observations of local field potentials (LFP) from the subcallosal cingulate region outside the postoperative period. Specifically, our results demonstrate that frequency-domain 1/f activity is measurable in a combined DBS-LFP recording system and that right hemisphere recordings appear sensitive to mood state, thus suggesting a potential readout suitable for consideration in ongoing efforts to develop adaptive DBS delivery systems.

Consistent linear and non-linear responses to invasive electrical brain stimulation across individuals and primate species with implanted electrodes

BACKGROUND

Electrical neuromodulation via implanted electrodes is used in treating numerous neurological disorders, yet our knowledge of how different brain regions respond to varying stimulation parameters is sparse.

OBJECTIVE/HYPOTHESIS

We hypothesized that the neural response to electrical stimulation is both region-specific and non-linearly related to amplitude and frequency.

METHODS

We examined evoked neural responses following 400 ms trains of 10-400 Hz electrical stimulation ranging from 0.1 to 10 mA. We stimulated electrodes implanted in cingulate cortex (dorsal anterior cingulate and rostral anterior cingulate) and subcortical regions (nucleus accumbens, amygdala) of non-human primates (NHP, N = 4) and patients with intractable epilepsy (N = 15) being monitored via intracranial electrodes. Recordings were performed in prefrontal, subcortical, and temporal lobe locations.

RESULTS

In subcortical regions as well as dorsal and rostral anterior cingulate cortex, response waveforms depended non-linearly on frequency (Pearson's linear correlation r < 0.39), but linearly on current (r > 0.58). These relationships between location, and input-output characteristics were similar in homologous brain regions with average Pearson's linear correlation values r > 0.75 between species and linear correlation values between participants r > 0.75 across frequency and current values per brain region. Evoked waveforms could be described by three main principal components (PCs) which allowed us to successfully predict response waveforms across individuals and across frequencies using PC strengths as functions of current and frequency using brain region specific regression models.

CONCLUSIONS

These results provide a framework for creation of an atlas of input-output relationships which could be used in the principled selection of stimulation parameters per brain region.

Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is an emerging experimental therapy for treatment-resistant depression. New developments in SCC DBS surgical targeting are focused on identifying specific axonal pathways for stimulation that are estimated from patient-specific computational models. This connectomic-based biophysical modeling strategy has proven successful in improving the clinical response to SCC DBS therapy, but the DBS models used to date have been relatively simplistic, limiting the precision of the pathway activation estimates. Therefore, we used the most detailed patient-specific foundation for DBS modeling currently available (i.e., field-cable modeling) to evaluate SCC DBS in our most recent cohort of six subjects, all of which were responders to the therapy. We quantified activation of four major pathways in the SCC region: forceps minor (FM), cingulum bundle (CB), uncinate fasciculus (UF), and subcortical connections between the frontal pole and the thalamus or ventral striatum (FP). We then used the percentage of activated axons in each pathway as regressors in a linear model to predict the time it took patients to reach a stable response, or TSR. Our analysis suggests that stimulation of the left and right CBs, as well as FM are the most likely therapeutic targets for SCC DBS. In addition, the right CB alone predicted 84% of the variation in the TSR, and the correlation was positive, suggesting that activation of the right CB beyond a critical percentage may actually protract the recovery process.

Test-retest reliability of a stimulation-locked evoked response to deep brain stimulation in subcallosal cingulate for treatment resistant depression

Deep brain stimulation (DBS) to the subcallosal cingulate cortex (SCC) is an emerging therapy for treatment resistant depression. Precision targeting of specific white matter fibers is now central to the model of SCC DBS treatment efficacy. A method to confirm SCC DBS target engagement is needed to reduce procedural variance across treatment providers and to optimize DBS parameters for individual patients. We examined the reliability of a novel cortical evoked response that is time-locked to a 2 Hz DBS pulse and shows the propagation of signal from the DBS target. The evoked response was detected in four individuals as a stereotyped series of components within 150 ms of a 6 V DBS pulse, each showing coherent topography on the head surface. Test-retest reliability across four repeated measures over 14 months met or exceeded standards for valid test construction in three of four patients. Several observations in this pilot sample demonstrate the prospective utility of this method to confirm surgical target engagement and instruct parameter selection. The topography of an orbital frontal component on the head surface showed specificity for patterns of forceps minor activation, which may provide a means to confirm DBS location with respect to key white matter structures. A divergent cortical response to unilateral stimulation of left (vs. right) hemisphere underscores the need for feedback acuity on the level of a single electrode, despite bilateral presentation of therapeutic stimulation. Results demonstrate viability of this method to explore patient-specific cortical responsivity to DBS for brain-circuit pathologies.