Research on the neural basis of major depressive disorder suggests that it is fundamentally a disease of cortical disinhibition, where breakdowns of inhibitory neuronal systems lead to diminished emotion regulation and intrusive rumination. Subregions of the prefrontal cortex are thought to be sources of this disinhibition. However, due to limited opportunities for intracranial recordings from humans with major depression, this hypothesis has not been directly tested. Here, we use intracranial recordings from the dorsolateral prefrontal, orbitofrontal, and anterior cingulate cortices from patients with major depression to measure daily fluctuations in self-reported depression symptom severity. Results indicate that directed connectivity within the delta frequency band, which has been linked to cortical inhibition, transiently increases intensity during negative mood. Symptom severity also shifts as connectivity patterns within the left and right prefrontal cortices become imbalanced. Our findings support the overarching hypothesis that depression worsens with prefrontal disinhibition and functional imbalance between hemispheres.

OBJECTIVE Deep brain stimulation (DBS) is an effective neurosurgical option for patients with treatment-resistant obsessive-compulsive disorder (OCD). Despite being more costly than neuroablative procedures of comparable efficacy, DBS has gained popularity over the years for its reversibility and adjustability. Although the cost-effectiveness of DBS has been investigated extensively in movement disorders, few economic analyses of DBS for psychiatric disorders exist. In this study, the authors present the first cost-effectiveness analysis of DBS for treatment-resistant OCD in the United States. METHODS The authors developed four decision analytical models to compare the cost-effectiveness of DBS with treatment as usual (TAU) for OCD, varying either the device type (i.e., nonrechargeable or rechargeable) or the time horizon (i.e., 3 or 5 years) in each model. Treatment response and complication rates were based on a literature review. Published algorithms were used to convert Yale-Brown Obsessive Compulsive Scale scores into utility scores reflecting improvements in quality of life. Costs were approached from the healthcare sector perspective and were drawn primarily from Medicare facility and physician reimbursement rates. For each model, a Monte Carlo simulation (n = 100,000) and probabilistic sensitivity analysis were performed to estimate the incremental cost-effectiveness ratio (ICER) in US dollars per quality-adjusted life year (QALY). RESULTS Data from 249 and 265 treatment-resistant OCD patients from the published literature who received DBS and had sufficient follow-up in 3- and 5-year models, respectively, were included. When conventional US willingness-to-pay (WTP) thresholds were used, nonrechargeable DBS models were less cost-effective (3-year ICER: $108,431/QALY; 5-year ICER: $203,202/QALY) and rechargeable DBS models were more cost-effective (3-year ICER: $49,363/QALY; 5-year ICER: $41,495/QALY) than TAU. At a WTP threshold of $100,000/QALY, rechargeable DBS devices were moderately more cost-effective than TAU at 3 and 5 years in 100% of iterations. At a WTP threshold of $50,000/QALY, rechargeable DBS devices were definitively more cost-effective than TAU at 3 and 5 years in 54% and 89% of iterations, respectively. When using WHO WTP conventions, 3- and 5-year nonrechargeable models were cost-effective in 100% and 84% of iterations, and 3- and 5-year rechargeable models were highly cost-effective in 99% and 100% of iterations, respectively. CONCLUSIONS Rechargeable DBS models were cost-effective for treatment-resistant OCD compared with TAU. Nonrechargeable DBS models may be cost-effective, especially with improvement in battery longevity and changes in accepted WTP thresholds.

Recent advances in surgical neuromodulation have enabled chronic and continuous intracranial monitoring during everyday life. We used this opportunity to identify neural predictors of clinical state in 12 individuals with treatment-resistant obsessive-compulsive disorder (OCD) receiving deep brain stimulation (DBS) therapy (NCT05915741). We developed our neurobehavioral models based on continuous neural recordings in the region of the ventral striatum in an initial cohort of five patients and tested and validated them in a held-out cohort of seven additional patients. Before DBS activation, in the most symptomatic state, theta/alpha (9 Hz) power evidenced a prominent circadian pattern and a high degree of predictability. In patients with persistent symptoms (non-responders), predictability of the neural data remained consistently high. On the other hand, in patients who improved symptomatically (responders), predictability of the neural data was significantly diminished. This neural feature accurately classified clinical status even in patients with limited duration recordings, indicating generalizability that could facilitate therapeutic decision-making. Machine learning classifiers generated using chronic neural measurements in individuals with obsessive-compulsive disorder accurately predicted clinical status and deep brain stimulation response.

INTRODUCTION: Deep brain stimulation (DBS) of the ventral capsule/ventral striatum (VC/VS) improves symptoms in ∼66% of patients with treatment-resistant obsessive-compulsive disorder (OCD). However, a common adverse effect of VC/VS DBS is hypomania, marked by decreased need for sleep and increased risk-taking behaviors. Modern DBS devices have enabled 24-hour collection of neural data, allowing for tracking of circadian rhythms reflected by VC/VS local field potentials (LFPs). METHODS: We implanted six patients with treatment-resistant OCD with a DBS device configured for constant VC/VS stimulation and recording. Spectral power in the 9 ± 2.5 Hz band was estimated onboard the device every 10 minutes for a median of 249 days (range 77-608). We assessed the rhythmicity of power in this spectral band by fitting 7-day retrospective rolling windows of per-day normalized LFP power to cosine functions using least-squared regression. Output metrics included acrophase (time of peak activity), amplitude, and fit significance. We quantified trends in acrophase over time using Pearson correlation. RESULTS: All six patients demonstrated consistent 24-hour cyclic LFP activity bilaterally. Two of the six had diurnal peaks which shifted significantly earlier across the study period. The remaining four patients had nocturnal peaks, all shifting significantly later over time. Notably, a patient in the latter group experienced three days of hypomania after DBS initiation associated with circadian disruptions even after clinical symptom resolution. Only after clinical DBS adjustment 2 weeks later did circadian rhythm rapidly return to pre-hypomanic levels. CONCLUSIONS: Study patients demonstrated evolving circadian VC/VS LFP activity across the course of DBS therapy, usually independent of cyclic whole-brain activity (i.e. sleep). Conversely, disruptions to these circadian patterns, as observed here during hypomania, may serve as biomarkers of region-specific stimulation side effects.

The rewards that we get from our choices and actions can have a major influence on our future behavior. Understanding how reward biasing of behavior is implemented in the brain is important for many reasons, including the fact that diminution in reward biasing is a hallmark of clinical depression. We hypothesized that reward biasing is mediated by the anterior cingulate cortex (ACC), a cortical hub region associated with the integration of reward and executive control and with the etiology of depression. To test this hypothesis, we recorded neural activity during a biased judgment task in patients undergoing intracranial monitoring for either epilepsy or major depressive disorder. We found that beta (12-30 Hz) oscillations in the ACC predicted both associated reward and the size of the choice bias, and also tracked reward receipt, thereby predicting bias on future trials. We found reduced magnitude of bias in depressed patients, in whom the beta-specific effects were correspondingly reduced. Our findings suggest that ACC beta oscillations may orchestrate the learning of reward information to guide adaptive choice, and, more broadly, suggest a potential biomarker for anhedonia and point to future development of interventions to enhance reward impact for therapeutic benefit.

Deep brain stimulation (DBS) for obsessive-compulsive disorder (OCD) achieves clinical benefit in 66% of treatment-resistant patients. However, there is still a lack of a fundamental understanding of the neurophysiological basis of the relationship between OCD behavior and neural activity. Recent advances in surgical neuromodulation have enabled continuous monitoring of neural activity during everyday activities. Here, our goal was to use these passive, continuous recordings to better understand the neurophysiological basis of clinical response after DBS for OCD.

Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130–160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.

Deep brain stimulation (DBS) has been used effectively for both treatment-resistant obsessive-compulsive disorder (OCD) and Tourette syndrome (TS) (1,2). While DBS of the anterior limb of the internal capsule is Food and Drug Administration approved for use in OCD under a Humanitarian Device Exemption, DBS for TS is still considered investigational (3,4). Several DBS targets for TS have been studied, most prominently the globus pallidus internus (GPi) and centromedian/parafascicular thalamus, though no single best target has emerged (2,5).

BACKGROUND:Deep brain stimulation (DBS) and other neuromodulatory techniques are being increasingly utilized to treat refractory neurologic and psychiatric disorders. OBJECTIVE:/Hypothesis: To better understand the circuit-level pathophysiology of treatment-resistant depression (TRD) and treat the network-level dysfunction inherent to this challenging disorder, we adopted an approach of inpatient intracranial monitoring borrowed from the epilepsy surgery field. METHODS:We implanted 3 patients with 4 DBS leads (bilateral pair in both the ventral capsule/ventral striatum and subcallosal cingulate) and 10 stereo-electroencephalography (sEEG) electrodes targeting depression-relevant network regions. For surgical planning, we used an interactive, holographic visualization platform to appreciate the 3D anatomy and connectivity. In the initial surgery, we placed the DBS leads and sEEG electrodes using robotic stereotaxy. Subjects were then admitted to an inpatient monitoring unit for depression-specific neurophysiological assessments. Following these investigations, subjects returned to the OR to remove the sEEG electrodes and internalize the DBS leads to implanted pulse generators. RESULTS:Intraoperative testing revealed positive valence responses in all 3 subjects that helped verify targeting. Given the importance of the network-based hypotheses we were testing, we required accurate adherence to the surgical plan (to engage DBS and sEEG targets) and stability of DBS lead rotational position (to ensure that stimulation field estimates of the directional leads used during inpatient monitoring were relevant chronically), both of which we confirmed (mean radial error 1.2±0.9 mm; mean rotation 3.6±2.6°). CONCLUSION:This novel hybrid sEEG-DBS approach allows detailed study of the neurophysiological substrates of complex neuropsychiatric disorders.

Several studies have demonstrated the substantial benefit of deep brain stimulation (DBS) in treatment-refractory obsessive-compulsive disorder (OCD). Despite this evidence base, the procedure remains underutilized due to barriers in access for patients1,2. One significant barrier is that the expertise in programming these devices is limited to a few experienced centers. This limitation creates challenges for patient access and places a high burden on these few sites. Our objective in this study was to describe our DBS programming strategy for patients with treatment-refractory OCD in relation to their clinical outcome scores over time.

INTRODUCTION: Major depression is associated with widespread dysfunction throughout the limbic system and neocortical regions such as the orbitofrontal cortex (OFC) and the dorsolateral prefrontal cortex (dlPFC) (4–7). The brain regions comprising the limbic system, including the amygdala, ventral striatum, and anterior cingulate cortex (ACC), show altered connectivity in MDD patients (5, 7). As part of an ongoing NIH-funded trial of DBS for depression, we implanted 3 patients with both DBS leads and stereo-EEG (sEEG) electrodes to measure neural oscillations in the dlPFC, OFC, and ACC. METHODS: Three depression patients were implanted with sEEG electrodes in areas including OFC, dlPFC, and ACC. We frequently measured depression severity throughout a 9-day inpatient monitoring period using a validated adaptive severity scale (8). We measured directed connectivity using multivariate vector autoregressive models that measure information flow between the right dlPFC, OFC, and ACC during resting state). Then we examined the relationship between depression severity and GC within the delta band (1-3 Hz). RESULTS: Information flow within the delta band was positively correlated with depression severity in each patient. Each showed distinct patterns of pathophysiological connectivity. Across all patients, directed connectivity from the OFC to the ACC predicted depression severity (p < 0.05). CONCLUSIONS: Information flow within the prefrontal cortex correlates closely with depression severity. Increased OFC -> ACC connectivity may relate to increased self-appraisals of mood and diminished control of emotional state during depressive episodes.

OBJECTIVE:Stereotactic radiosurgical capsulotomy (SRS-C) is an effective neurosurgical option for patients with treatment-resistant obsessive-compulsive disorder (TROCD). Unlike other procedures such as deep brain stimulation and radiofrequency ablation, the cost-effectiveness of SRS-C for TROCD has not been investigated. The authors herein report the first cost-effectiveness analysis of SRS-C for TROCD.METHODS:Using a decision analytic model, the authors compared the cost-effectiveness of SRS-C to treatment as usual (TAU) for TROCD. Treatment response and complication rates were derived from a review of relevant clinical trials. Published algorithms were used to convert Yale-Brown Obsessive Compulsive Scale scores into utility scores reflecting improvements in quality of life. Costs were approached from the healthcare sector perspective and were drawn from Medicare reimbursement rates and available healthcare economics data. A Monte Carlo simulation and probabilistic sensitivity analysis were performed to estimate the incremental cost-effectiveness ratio.RESULTS:One hundred fifty-eight TROCD patients across 9 studies who had undergone SRS-C and had at least 36 months of follow-up were included in the model. Compared to TAU, SRS-C was more cost-effective, with an estimated incremental cost-effectiveness ratio of $28,960 per quality-adjusted life year (QALY) gained. Within the 3-year time horizon, net QALYs gained were greater in the SRS-C group than the TAU group by 0.27 (95% CI 0.2698-0.2702, p < 0.0001). At willingness-to-pay thresholds of $50,000 and $100,000 per QALY, the Monte Carlo simulation revealed that SRS-C was more cost-effective than TAU in 83% and 100% of iterations, respectively.CONCLUSIONS:Compared to TAU, SRS-C for TROCD is more cost-effective under a range of possible cost and effectiveness values.

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.

Background:Anxiety is a common symptom of mental health disorders. Surgical treatment of anxiety-related disorders is limited by our understanding of the neural circuitry responsible for emotional regulation. Limbic regions communicate with other cortical and subcortical regions to generate emotional responses and behaviors toward anxiogenic stimuli. Epilepsy involving corticolimbic regions may disrupt normal neural circuitry and present with mood disorders. Anxiety presenting in patients with mesial temporal lobe epilepsy is common; however, anxiety in patients with cingulate epilepsy is not well described. Neurosurgical cases with rare clinical presentations may provide insight into the basic functionality of the human mind and ultimately lead to improvements in surgical treatments.Case Description:We present the case of a 24-year-old male with a 20-year history of nonlesional and cingulate epilepsy with an aura of anxiety and baseline anxiety. Noninvasive work-up was discordant. Intracranial evaluation using stereoelectroencephalography established the epileptogenic zone in the left anterior and mid-cingulate gyrus. Stimulation of the cingulate reproduced a sense of anxiety typical of the habitual auras. We performed laser interstitial thermal therapy of the left anterior and mid-cingulate gyrus. At 8 months following ablation, the patient reported a substantial reduction in seizure frequency and complete elimination of his baseline anxiety and anxious auras.Conclusion:This case highlights the role of the cingulate cortex (CC) in regulating anxiety. Ablation of the epileptic focus resolved both epilepsy-related anxiety and baseline features.a Future studies assessing the role of the CC in anxiety disorders may enable improvements in surgical treatments for anxiety disorders.

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.

OBJECTIVE Magnetoencephalography (MEG) is a useful component of the presurgical evaluation of patients with epilepsy. Due to its high spatiotemporal resolution, MEG often provides additional information to the clinician when forming hypotheses about the epileptogenic zone (EZ). Because of the increasing utilization of stereo-electroencephalography (sEEG), MEG clusters are used to guide sEEG electrode targeting with increasing frequency. However, there are no predefined features of an MEG cluster that predict ictal activity. This study aims to determine which MEG cluster characteristics are predictive of the EZ. METHODS The authors retrospectively analyzed all patients who had an MEG study (2017???2021) and underwent subsequent sEEG evaluation. MEG dipoles and sEEG electrodes were reconstructed in the same coordinate space to calculate overlap among individual contacts on electrodes and MEG clusters. MEG cluster features???including number of dipoles, proximity, angle, density, magnitude, confidence parameters, and brain region???were used to predict ictal activity in sEEG. Logistic regression was used to identify important cluster features and to train a binary classifier to predict ictal activity. RESULTS Across 40 included patients, 196 electrodes (42.2%) sampled MEG clusters. Electrodes that sampled MEG clusters had higher rates of ictal and interictal activity than those that did not sample MEG clusters (ictal 68.4% vs 39.8%, p < 0.001; interictal 71.9% vs 44.6%, p < 0.001). Logistic regression revealed that the number of dipoles (odds ratio [OR] 1.09, 95% confidence interval [CI] 1.04???1.14, t = 3.43) and confidence volume (OR 0.02, 95% CI 0.00???0.86, t = ???2.032) were predictive of ictal activity. This model was predictive of ictal activity with 77.3% accuracy (sensitivity = 80%, specificity = 74%, C-statistic = 0.81). Using only the number of dipoles had a predictive accuracy of 75%, whereas a threshold between 14 and 17 dipoles in a cluster detected ictal activity with 75.9%???85.2% sensitivity. CONCLUSIONS MEG clusters with approximately 14 or more dipoles are strong predictors of ictal activity and may be useful in the preoperative planning of sEEG implantation.

INTRODUCTION: Magnetoencephalography (MEG) is a useful component of a pre-surgical evaluation. Due to its high spatiotemporal resolution, MEG often provides nonredundant information to the clinician when forming hypotheses about the epileptogenic zone (EZ). With the increasing utilization of stereo-EEG (sEEG), MEG clusters are more commonly used as an sEEG electrode target. However, there are no pre-defined features of an MEG cluster that predict whether it is representative of intracranial EEG interictal or ictal activity, which limits optimal utilization of MEG in surgical planning. METHODS: We retrospectively analyzed patients who had an MEG study since it became available at our center (2017-2021). Patients were included if they had a positive MEG prior to an sEEG evaluation. MEG dipoles and sEEG electrodes were reconstructed in the same coordinate space to calculate overlap between electrodes and MEG clusters, and to quantify MEG cluster characteristics. MEG cluster features including brain region, stability (degree to which dipoles are parallel), tightness (density of dipole distribution), and number of dipoles were included in a binary classifier to predict ictal and interictal activity. RESULTS: Across 39 included patients, 13% of sEEG electrodes sampled MEG clusters. In these contacts, there were higher rates of ictal (43.22% vs 17.36%, p < 0.001) and interictal activity (39.63% vs 18.93%, p < 0.001) compared to electrodes not sampling MEG clusters. For contacts sampling the MEG cluster, binary classification predicted ictal activity with 76.7% accuracy compared to 54.4% in shuffled data (c-statistic = 0.816) , while interictal activity was predicted accurately at 68.2% compared to 57.8% in shuffled data (c-statistic = 0.672) . Further analysis of individual characteristics showed that cluster stability contributed most to the model’s accuracy (c-statistic = 0.773), whereas tightness (c-statistic = 0.701) and number of spikes (c-statistic = 0.692) contributed to a lesser extent. Brain region (c-statistic = 0.553) was not predictive of ictal activity. CONCLUSION: MEG cluster stability, tightness, and number of dipoles can be used to predict ictal activity. Quantitative analysis of these features may be useful for prospective planning of intracranial diagnostic implants.

BACKGROUND: A number of stereotactic platforms are available for performing deep brain stimulation (DBS) lead implantation. Robot-assisted stereotaxy has emerged more recently demonstrating comparable accuracy and shorter operating room times compared with conventional frame-based systems. OBJECTIVE: To compare the accuracy of our streamlined robotic DBS workflow with data in the literature from frame-based and frameless systems. METHODS: We retrospectively reviewed 126 consecutive DBS lead placement procedures using a robotic stereotactic platform. Indications included Parkinson disease (n = 94), essential tremor (n = 21), obsessive compulsive disorder (n = 7), and dystonia (n = 4). Procedures were performed using a stereotactic frame for fixation and the frame pins as skull fiducials for robot registration. We used intraoperative fluoroscopic computed tomography for registration and postplacement verification. RESULTS: The mean radial error for the target point was 1.06 mm (SD: 0.55 mm, range 0.04-2.80 mm) on intraoperative fluoroscopic computed tomography. The mean operative time for an asleep, bilateral implant without implantable pulse generator placement was 238 minutes (SD: 52 minutes), and skin-to-skin procedure time was 116 minutes (SD: 42 minutes). CONCLUSION: We describe a streamlined workflow for DBS lead placement using robot-assisted stereotaxy with a comparable accuracy profile. Obviating the need for checking and switching coordinates, as is standard for frame-based DBS, also reduces the chance for human error and facilitates training.

Introduction: Movement disorders can be common, persistent, and debilitating sequelae of severe traumatic brain injury. Post-traumatic movement disorders are usually complex in nature, involving multiple phenomenological manifestations, and can be difficult to control with medical management alone. Deep brain stimulation (DBS) has been used to treat these challenging cases, but distorted brain anatomy secondary to trauma can complicate effective targeting. In such cases, use of diffusion tractography imaging and inpatient testing with externalized DBS leads can be beneficial in optimizing outcomes. Case Description: We present the case of a 42-year-old man with severe, disabling post-traumatic tremor who underwent bilateral, dual target DBS to the globus pallidus internus (GPi) and a combined ventral intermediate nucleus of the thalamus (Vim)/dentato-rubro-thalamic tracts (DRTT) target. DRTT fiber tracts were reconstructed preoperatively to assist in surgical targeting given the patient's distorted anatomy. Externalization and survey of the four leads extra-operatively with inpatient testing allowed for internalization of the leads that demonstrated benefit. Six months after surgery, the patient's tremor and dystonic burden had decreased by 67% in the performance sub-score of The Essential Tremor Rating Scale (TETRAS). Conclusion: A patient-tailored approach including target selection guided by individualized anatomy and tractography as well as extra-operative externalized lead interrogation was shown to be effective in optimizing clinical outcome in a patient with refractory post-traumatic tremor.