ABSTRACT Background Freezing of gait (FoG) is a debilitating motor feature that affects individuals with Parkinson's disease (PD). The mechanism underlying FoG is not entirely understood, which poses a challenge in finding effective treatment. The goal of this study is to advance the understanding of FoG pathophysiology. This study aims to assess the differences in structural connectivity (SC) and functional connectivity (FC) patterns among PD patients with freezing of gait (FoG+), gait disturbances other than freezing (FoG−), and no gait disturbances (NGD). Methods Diffusion‐weighted MRI (dwMRI) and resting‐state functional MRI (rs‐fMRI) were obtained from 9 FoG+, 13 FoG−, and 10 NGD patients. The FC data was processed by a region of interest (ROI)‐to‐ROI analysis using the default preprocessing pipeline from the MATLAB‐based CONN toolbox. SC analysis was performed via diffusion‐based tractography and subsequent connectome reconstructions in MRtrix3. Results Compared to the FoG− and NGD groups, the FoG+ group showed substantial involvement, in both SC and FC, of the limbic system, putamen, parietal lobes, and cerebellum. Furthermore, our results reveal FC alteration between the cerebellum and the median raphe nuclei, which is part of the pontomedullary reticular formation. Conclusions Our results confirmed previous research regarding the alterations in multiple brain areas in those with FoG, particularly the limbic system, putamen, parietal lobe, and cerebellum. We further establish unique FC between the cerebellum and the median raphe nucleus in those with FoG. This finding highlights the role of the cerebellum in regulating posture, gait, and locomotive signals, potentially through serotonergic projections.

Understanding the mechanical interactions between surgical probes and brain tissue is essential for optimizing procedures such as deep brain stimulation (DBS). In this study, agar gel phantoms were used as brain tissue surrogates for their well-characterized mechanical properties and extensive use in neurosurgical modeling. Systematic experiments were conducted to quantify the insertion and withdrawal forces of DBS probes, and the evolution of probe-induced channels was analyzed using synchronized high-speed imaging and force measurements. Key parameters, such as peak insertion force, were extracted from filtered curves showing the relationship between force and depth as well as force and time. Classical physical models, such as the Hertz and Fung equations, characterized the force response in the linear regime and in regimes with weak nonlinearity, while a hybrid physics-guided residual neural network (PGNN) was applied to capture complex and highly nonlinear interactions. Our results show that the force response exhibited time-dependent behavior: insertion force showed clear velocity dependence, whereas withdrawal force was predominantly described by a velocity-independent friction term over the tested range. Probe speed and gel-recovery dynamics nevertheless influenced channel closure. Channel measurements revealed that the residual channel is consistently smaller than the probe diameter, which can be attributed to the combined effects of elastic recovery, viscous flow, and hydration. Both probe speed and depth were found to significantly influence the dynamics of channel closure. Model fitting demonstrated that classical models can adequately describe the force response in specific regimes, but the hybrid PGNN model improves prediction accuracy for complex mechanical interactions. Overall, this work offers new insights into phase-specific probe-material interaction mechanics in a controlled homogeneous surrogate, and the integrated experimental and modeling framework developed here provides a baseline dataset for future studies of DBS-relevant insertion mechanics and model refinement.

Epilepsy surgery, the treatment of choice for drug-resistant focal epilepsy, is evolving rapidly. This progress is driven by a growing interest in the network theory of epilepsy, advances in data-driven models, and a focus on personalised treatment approaches. As a result, treatment options have expanded to include minimally invasive procedures, neurostimulation devices, and network-based interventions. Predicting surgical outcomes—such as seizure freedom and neuropsychological effects—remains challenging but is improving through advances in computational technology and molecular research, paving the way for more precise surgery. Despite these advancements, disparities in access to treatments persist, particularly in resource-scarce settings, highlighting the need for systemic solutions to improve access. Emerging research into genetic and multi-omic markers might assist in tailoring treatments and improving the prediction of outcomes. Future directions include integrating minimally invasive techniques, refining neuromodulation strategies, and leveraging molecular and computational tools to optimise patient care. Multidisciplinary collaboration will be essential to overcome challenges, reduce disparities, and advance surgical outcomes for patients with drug-resistant epilepsy worldwide.

Anterior temporal lobectomy (ATL) remains the standard surgical treatment for drug-resistant temporal lobe epilepsy, yet 20% to 30% of patients experience persistent seizures and/or unfavorable neuropsychological outcomes. These results highlight that postoperative success is influenced not only by the technical execution of surgery but also by the accuracy with which epileptogenic networks are characterized. As such, we consider ATL failure through 2 broad mechanisms: incomplete treatment of the presumed epileptogenic network and limitations in the initial diagnostic understanding of the epileptogenic network. It is also becoming more evident that seizure outcomes alone do not fully capture surgical success, as cognitive, psychiatric, and functional consequences play a critical role in long-term quality of life. Drawing on contemporary evidence and discussions from the Temporal Lobe Club Special Interest Group at the 2025 American Epilepsy Society Annual Meeting, we present a framework for conceptualizing, reevaluating, and managing patients following ATL failure.

OBJECTIVE:This study was undertaken to evaluate the safety and effectiveness of responsive thalamic stimulation as adjunctive therapy for drug-resistant idiopathic generalized epilepsy (IGE) with generalized tonic-clonic seizures (GTCSs). METHODS:NAUTILUS is a prospective, multicenter, single-blind, randomized sham-controlled pivotal trial. Patients were ≥12 years of age with drug-resistant IGE and ≥2 GTCSs over a 3-month baseline. Bilateral depth leads were targeted to the centromedian thalamus. One month later, patients were randomized to Active (responsive stimulation, n = 44) or Sham (no stimulation, n = 43). The effectiveness evaluation period (EEP) began 3 months postimplant through 1 year. After a second GTCS in the EEP, patients transitioned to open-label active stimulation. The primary safety endpoint was the serious adverse device-related event (SADE) rate at 84 days postimplant. The primary effectiveness endpoint was time-to-second-GTCS during the EEP. Additional endpoints included median percent change in days with any generalized seizure, GTCS frequency, and responder rate (RR). RESULTS:Eighty-seven patients were implanted across 23 US centers. The SADE rate was significantly below the performance goal (6.9%, p < .0001), with no adverse effects on cognition, mood, or sleep. The prespecified primary effectiveness endpoint was not significant. However, a post hoc mixed-effects model considering all EEP days demonstrated greater GTCS reduction in the originally randomized Active group (61%) compared to patients originally randomized to Sham (49%, p = .030). Eighteen-month outcomes included 76.8% median GTCS reduction, 62.5% RR, 40% GTCS-free at that timepoint, and 77.8% median reduction in days with any generalized seizure. More than 90% of patients and 86% of physicians reported improvement on Global Impression of Change scales. SIGNIFICANCE:NAUTILUS is the first randomized controlled neuromodulation trial in IGE. Responsive thalamic stimulation provided a clinically meaningful and durable reduction in seizures with an acceptable safety profile, offering a much-needed option for drug-resistant IGE.

OBJECTIVE:Deep brain stimulation (DBS) is an established surgical therapy for movement disorders, epilepsy, and psychiatric conditions, yet remains underutilized due to perceived risks. We therefore endeavored to compare the safety of DBS to other common elective procedures to provide context for its relative risk. METHODS:This retrospective cohort study utilized the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database, encompassing diverse referral and community hospitals across the United States from 2015 to 2021. Patients with DBS were compared with those receiving one of the 16 most common elective procedures. The primary outcome of interest was the weighted odds of any postoperative complication at 30 days. Secondary outcomes included risk of readmission, reoperation, and discharge disposition. Logistic regression with inverse probability of treatment weighting (IPTW) based on propensity scores adjusted for baseline group heterogeneity. RESULTS:We identified 2,853,662 patients for analysis, including 4,749 DBS procedures. After IPTW adjustment, patients with DBS experienced lower 30-day complication rates compared with other procedures (1.3% vs 4.1%, OR = 0.32, 95% confidence interval [CI] = 0.25-0.41, p < 0.0001). Readmission rates did not differ significantly (2.2% vs 2.6%, OR = 0.84, 95% CI = 0.69-1.02, p = 0.08). DBS cases had higher odds of discharge home (98.7% vs 96.3%, OR = 2.94, 95% CI = 2.27-3.82, p < 0.0001) and lower reoperation rates (0.7% vs 1.3%, OR = 0.50, 95% CI = 0.35-0.72, p = 0.0002). INTERPRETATION:DBS demonstrates a favorable safety profile with substantially lower complication rates compared with the most widely performed elective surgeries. These findings support broader consideration of surgical referral for appropriate DBS candidates. ANN NEUROL 2026;99:1239-1250.

BACKGROUND:Deep-brain stimulation (DBS) systems are implanted for movement disorders, epilepsy, and psychiatric conditions. Neurologic surgery remains the only discipline credentialed to implant DBS devices, although significant practice variation exists, partly due to heterogeneous training. The North American Neuromodulation Society (NANS) education committee offers a granular recommendation for the progression of an early learner through the practitioner level. It is contextualized within the six-core competency rubric for the surgical implantation of DBS devices. MATERIALS AND METHODS:Guided by the Accreditation Council for Graduate Medical Education (ACGME) core competencies, a subcommittee of the NANS education committee met virtually and in-person over two years to develop a curriculum. The subcommittee used a consensus approach and an evidence-based development strategy; once completed, the NANS board approved the DBS curriculum. RESULTS:The DBS curriculum was developed for implanting surgeons and neurosurgical trainees. The table was vertically oriented into the six ACGME educational core competencies. A horizontal progression across 57 competencies defines expected skills for early learners, advanced learners, and independent practitioners. CONCLUSIONS:DBS devices are implanted by neurologic surgeons; education variability in acquired surgical skills and judgment may influence practice variation. This DBS curriculum presents consensus recommendations for competency progression within the six core competencies of the ACGME.

Intracranial electroencephalographic (iEEG) connectivity analysis is a promising method to localize epileptic networks and guide surgical planning in focal drug-resistant epilepsy. Despite numerous studies exploring its utility, the added value of iEEG connectivity over standard clinical presurgical evaluation remains unclear. We assess the current evidence on the efficacy of iEEG connectivity analyses to improve seizure outcomes following epilepsy surgery through a systematic review and meta-analysis. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines, we searched PubMed and Embase for studies (2006-2024) of adult focal drug-resistant epilepsy patients who underwent surgical resection or ablation, reported outcomes at least 1 year postsurgery, and used iEEG connectivity analysis to localize networks. Reviews, nonhuman studies, and studies lacking iEEG connectivity analysis or network localization were excluded. We derived classification metrics (true/false positives/negatives) based on concordance between iEEG findings, clinical localization, and outcome. Subgroup meta-analyses and meta-regressions determined differences by seizure type, lesion status, and analysis approach. Of 2881 studies screened, 25 met criteria (n = 909). The pooled odds ratio comparing seizure outcome prediction using iEEG connectivity versus standard clinical evaluation was 1.36 (95% confidence interval = 1.10-1.69, p = .004), indicating a significant overall benefit. Subgroup analyses found no significant differences by directionality, modeling method (linear/nonlinear), or iEEG epoch (interictal/peri-ictal). Meta-regression revealed greater added value of iEEG connectivity in studies with higher proportions of non-seizure-free patients following surgery for temporal lobe or lesional epilepsy. However, no individual study achieved statistical significance on its own, reflecting limited power and lack of individual patient-level data. Power analysis confirmed that detecting a clinically meaningful effect requires substantially larger, potentially multicenter datasets. iEEG connectivity analysis offers modest but consistent increased value over standard clinical methods to predict seizure freedom in adult patients with focal drug-resistant epilepsy. For clinical translation, we propose recommendations for future studies to address sample size limitations, standardize reporting, and prioritize individual patient-level data sharing.

Remote, internet-based deep brain stimulation programming for Parkinson’s disease accelerates clinical benefits postoperatively by improving access to therapy adjustments compared to in-clinic optimization. After completion of the initial digital programming phase, we show that clinical outcomes, quality of life, and safety remain sustained over at least twelve months under routine care conditions. Embedding a randomized trial within a larger cohort study enables long-term, real-world evaluation, offering a scalable and pragmatic model for assessing complex digital interventions in routine clinical care. (NCT05269862 registered on 2022-03-08 and NCT04071847 registered on 2019-08-28).

ABSTRACT Introduction The ventral intermediate nucleus (VIM) is a key target for deep brain stimulation (DBS) in treating essential tremor (ET). However, conventional indirect targeting often overlooks individual anatomic variability. Diffusion tractography (DT) offers a patient‐specific approach, but its effectiveness depends on the chosen method. Objective To compare the performance of nine DT methods for presurgical targeting of the VIM and Ventralis Caudalis (VC) in the thalamus. Methods We applied five probabilistic and four deterministic tractography methods to pre‐operative diffusion images from 15 ET patients. The dentato‐rubro‐thalamic (DRT) and spinothalamic (ST) tracts were reconstructed to localize the VIM and VC. Patient‐specific targets were defined as the centers‐of‐gravity (CoG) of thalamic tract‐density indices. Accuracy was evaluated by comparing CoGs with post‐implantation electrode locations, given the lack of direct anatomical validation. Additional metrics included the lateral distance from the third ventricle and the VIM–VC distance. Statistical analysis used Kruskal–Wallis and Dunn's tests. Results Tractography methods showed substantial inter‐ and intra‐method variability. Probabilistic approaches specifically constrained spherical deconvolution (CSD)‐based tractography exhibited lower variability and closer correspondence to planned and implanted lead locations. CSD‐based tractography also demonstrated greater anatomical separation between the VIM from the VC compared with several deterministic approaches. Conclusions Probabilistic methods, especially CSD‐based approaches, showed promising accuracy and reliability, results should be interpreted with caution given the retrospective design and indirect accuracy estimates. These findings highlight the need for prospective studies with anatomical validation but also suggest how optimized tractography methods may help refine targeting strategies.

OBJECTIVE:The objective was to evaluate the stability of stimulation current delivered by deep brain stimulation (DBS) systems during MRI scanning and to assess whether configuration-dependent variability in induced current may undermine the interpretability of functional MRI (fMRI) acquired during active stimulation. METHODS:The authors measured the electrical output of 2 current-controlled DBS systems in a standardized phantom during 3-T MRI acquisition. Stimulation was delivered in both monopolar and bipolar configurations, with the DBS systems on and off. Induced current was recorded using a custom MRI-conditional setup, and peak amplitudes were quantified across multiple sequences, including gradient-intensive fMRI protocols. All data were normalized to baseline output and analyzed using Cohen's d to assess the magnitude of MRI-induced current deviation. RESULTS:Monopolar stimulation during MRI exhibited significant current fluctuations, with induced amplitudes ranging from -3.2 to +3.9 mA and frequent polarity inversion. These distortions were sequence dependent and most pronounced during fMRI acquisition. In contrast, bipolar stimulation demonstrated stable output with minimal deviation from programmed parameters. The variability observed in monopolar output was not attributable to impedance shifts and was consistent across both DBS systems tested. CONCLUSIONS:MRI-induced current substantially alters the effective output of monopolar DBS, introducing uncertainty into any concurrent fMRI acquisition. Although functional imaging was not directly performed in human subjects, these findings imply that the observed blood oxygen level-dependent (BOLD) response during monopolar stimulation likely reflects the distorted, not programmed, stimulation. Bipolar configurations avoid this confounder and should be preferred when interpreting fMRI data acquired during DBS.

OBJECTIVES:Pivotal trials have established the effectiveness of the Responsive Neurostimulation System (RNS® System) in treating focal epilepsy. In clinical trials, depth leads were primarily used to treat mesial temporal seizure onsets while cortical strip leads were used to treat neocortical seizure onsets. Here, we systematically analyze the safety and efficacy of stereoelectroencephalography (sEEG)-guided depth leads to provide responsive stimulation to neocortical gray matter. METHODS:Patients were stratified as strong responders (>median cohort seizure reduction %), weak responders (>0% and ≤median cohort seizure reduction %), and anti-responders (≤0%) based on percent seizure reduction at 1 year post-implant (1-Y). Pre-operative T1-weighted magnetic resonance imaging and post-operative computed tomography images were merged, and the Euclidean distance between the sEEG epileptic focus (sEEG-EF) and the nearest RNS System depth lead contacts was calculated. RESULTS:A total of 87 depth leads were implanted in 55 patients across neocortical brain regions. The median reduction in clinical seizures improved from 66.7% at 1-Y to 77.5% at long-term follow-up (LTFU: 2.35 ± 0.95 years), with 10 patients (18.2%) achieving complete seizure freedom. Seven patients (12.7%) experienced six serious adverse events. At 1-Y, shorter Euclidean distance between the sEEG-EF and RNS System depth leads predicted improved seizure outcome in strong responders (β = -0.84, p = 0.008) but not in weak responders (β = 0.21, p = 0.9) or anti-responders (β = -20.34, p = 0.11). At LTFU, there was no significant relationship between Euclidean distance and seizure reduction in strong responders (β = 0.77, p = 0.18), weak responders (β = 2.05, p = 0.54), or anti-responders (β = 0.24, p = 0.99). Exploratory analyses at 1-Y showed nominal associations between older age (ρ = 0.32), longer epilepsy duration (ρ = 0.27), and non-mesial temporal sEEG-EFs and greater seizure reduction; however, none survived Bonferroni correction (adjusted α = 0.0027; all post-correction p > 0.0027), and no associations were observed at LTFU. SIGNIFICANCE:In this series, neocortical depth leads for RNS therapy had favorable safety and efficacy and proximity to the sEEG-EF drove initial outcomes for strong responders to RNS therapy. PLAIN LANGUAGE SUMMARY:In this multi-center study, patients with difficult-to-treat seizures received brain-responsive stimulation using a device called responsive neurostimulation (RNS), which delivers small electrical pulses to reduce seizures. We focused on patients treated with electrodes placed in the brain's outer regions (the neocortex) and guided by a mapping procedure called sEEG. On average, patients had their seizures cut by two-thirds after one year and by more than three-quarters with longer follow-up, with about one in five becoming seizure-free. The treatment was safe, and closer electrode placement to the seizure source helped explain early-but not long-term-improvements.

BACKGROUND AND OBJECTIVES:The efficacy of deep brain stimulation (DBS) relies on accurate electrode placement. Unfortunately, electrode deviation poses a persistent problem, with most electrodes demonstrating some degree of bending. Although such bending does not always result in target deviation, an estimated 3% to 8% of patients still require revision surgery to address suboptimal electrode placement. DBS electrode deviation may occur at mechanical tissue interfaces, with denser internal capsule (IC) fibers being the most likely factor. Based on basic principles of physics, we hypothesized that the angle of a planned trajectory relative to tissue interfaces created by the IC induces deviation. METHODS:Ten patients with Parkinson disease scheduled for DBS surgery underwent preoperative 3T magnetic resonance elastography (MRE) using synchronized external vibrations to measure brain tissue stiffness. The IC stiffness interface (ICSI) was defined as the transition between the corona radiata and IC on MRE. The rate of transition was calculated as the change in stiffness across the ICSI. Postoperative computed tomography was used to measure target deviation . The angle of approach was calculated as the angle between the planned trajectory and the normal vector to the ICSI. Pearson correlations and t -tests were performed to evaluate associations between the angle of approach and target deviation. RESULTS:Twenty-one electrode trajectories were analyzed. The mean electrode deviation was 1.27 ± 0.63 mm. A significant correlation (r = 0.57, 95% CI [0.18, 0.80], P = .007) was found between angle of approach and target deviation, with larger angles associated with greater deviations. The rate of transition did not correlate with deviation ( P = .874). CONCLUSION:MRE effectively quantifies in vivo brain tissue stiffness in Parkinson disease. The angle between the planned trajectory and the ICSI correlates with target deviation, supporting the hypothesis that tissue mechanics influence electrode bending. MRE has potential to quantify the likelihood of DBS electrode deviation, which could reduce revision surgeries and enhance clinical outcomes.

Pathological high-frequency oscillations (HFOs 80-600 Hz) in intracranial EEG distinguish epileptogenic cortex. However, it is uncertain whether utilizing HFO measures for surgical planning improve epilepsy surgery seizure outcomes and minimize morbidity. The clinical gold standard for planning an epilepsy surgery involves consensus between epileptologists, radiologists, and neurosurgeons based on multimodality findings, and particularly the location of the seizure onset zone. We asked whether seizure freedom following epilepsy surgery could be accurately predicted using machine learning that uses measures of HFO features relative to the boundaries of a surgical resection or laser ablation. We detected and quantified HFOs from depth EEG contacts during 30-200 minutes of non-rapid eye movement sleep from 78 pre-surgical patients from three institutions. We trained a three-branch convolutional neural network (CNN) using 3 neuroanatomic features and 37 HFO derived features. The first and second CNN branches computed within and between patient differences, respectively, and the third branch contains the resected contacts that also influenced branches 1 and 2. We found that this HFO CNN labeled the seizure free patients with 92% accuracy using 5-fold cross-validation. These results suggest that a resection planned with the clinical gold standard can be prospectively evaluated by a HFO CNN approach to test whether the resection boundaries will achieve a seizure free outcome. Future work will explore utilizing the HFO CNN approach for counterfactual virtual resections constrained by a utility function to minimize morbidity. ### Competing Interest Statement M.R.S. has received compensation for speaking at continuing medical education (CME) programmes from Medscape, Projects for Knowledge, International Medical Press and Eisai. He has consulted for Medtronic, Neurelis and Johnson & Johnson. He has received research support from Eisai, Medtronic, Neurelis, SK Life Science, Takeda, Xenon, Cerevel, UCB Pharma, Janssen and Engage Pharmaceuticals. He has received royalties from Oxford University Press and Cambridge University Press. The remainder of the authors declare no competing interests. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB of Jefferson University gave ethical approval for this work IRB of University of California Los Angeles gave ethical approval for this work IRB of Zhejiang University gave ethical approval for this work IRB of Stony Brook University deemed this work IRB exempt I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Resective surgery for drug-resistant temporal lobe epilepsy remains underutilized in the United States. While anteromesial temporal lobectomy consistently achieves the highest rates of long-term seizure freedom, it comes with greater risks for memory and language decline. Magnetic resonance imaging-guided laser interstitial thermal therapy and neuromodulation have gained popularity due to perceived lower surgical risk and faster recovery, although they yield lower rates of sustained seizure freedom. Neuromodulation with vagus nerve, deep brain, or responsive neurostimulation provides an option for patients ineligible for resection or ablation, but overall seizure outcomes remain modest. Balancing improved seizure control with open resection against the potential cognitive advantages of less invasive treatments is complex, requiring careful patient selection. Future research must refine these approaches to optimize results. Thoughtful, individualized decision-making, guided by each patient's clinical scenario and goals, is paramount for achieving the best balance between seizure freedom, cognitive preservation, and overall patient outcome.