Deep brain stimulation: Imaging on a group level

Optimizing stimulation parameters for anterior thalamic nuclei deep brain stimulation in epilepsy: A randomized crossover trial

OBJECTIVE

The effects of brain stimulation for diseases like epilepsy are delayed, making stimulation optimization difficult. The parameters for anterior thalamic nuclei (ANT) deep brain stimulation (DBS) for focal drug-resistant epilepsy management are often restricted to those used in the SANTE landmark trial. There is little evidence regarding effective alternatives, and low-frequency stimulation is typically neglected. We prospectively compare a widely differing stimulation parameter set to typical settings.

METHODS

This randomized, modified crossover, open trial compares the efficacy and safety of an alternative set of parameters using continuous low-frequency stimulation (cLFS) with a longer pulse width (7 Hz, 200 μs, continuous) compared to SANTE's intermittent high-frequency stimulation (iHFS) with a short pulse width (145 Hz, 90 μs, cycling 1 min on/5 min off). After 3 months on a randomly assigned first set, patients are switched to the other settings, unless seizure-free. Patients are re-evaluated after 3 more months, which marks the completion of the trial. After that, they can either remain on the same settings or switch back.

RESULTS

Sixteen patients with a median baseline seizure frequency of 13.8 seizures/month (interquartile range [IQR] = 2.7-22.8) were included in the analysis. At trial completion (median follow-up = 30 weeks, IQR = 26-35), ANT-DBS significantly reduced median seizure frequency (62%, IQR = 18-81, Wilcoxon test statistic [W] = 99, p = .008). Both iHFS (33%, IQR = 0-65, W = 81, p = .02) and cLFS (73%, IQR = 30-79, W = 105, p = .001) significantly reduced median seizure frequency. cLFS showed improved median seizure frequency reduction compared to iHFS (W = 63, p = .03) and was not associated with any moderate or severe adverse effects.

SIGNIFICANCE

Results support cLFS for ANT-DBS as a safe and effective alternative to typical iHFS parameters. Stimulation with widely differing parameter sets may be as effective as or, in some situations, more effective than typical stimulation parameters.

Investigating the neural correlates of subjective sleep changes following subthalamic nucleus deep brain stimulation for Parkinson's disease

INTRODUCTION

Sleep disturbances in Parkinson's disease (PD) are extremely common and significantly impact quality of life. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established therapy for motor symptoms and may also influence sleep outcomes. However, the relationship between stimulation location, structural networks, and sleep improvements remains poorly understood, particularly over longer durations.

METHODS

We conducted a retrospective analysis of 53 PD patients implanted with bilateral STN-DBS. Sleep outcomes were assessed using self-report measures, with subsection scores for nighttime sleep, daytime wakefulness, and total sleep disturbance analysed. Local stimulation effects were modelled using sweet spot analyses, and innervated tracts were examined through discriminative fiber filtering. Associations with motor improvements and demographic factors were analysed.

RESULTS

Significant improvements were reported in both nighttime sleep and daytime wakefulness. Motor symptom improvements were significantly positively associated with cumulative sleep scores but did not fully explain sleep changes. Sweet spot analyses revealed associations between cumulative sleep score improvements and the sensorimotor STN, while fiber filtering implicated brainstem, cerebellar, and cortical motor tracts for daytime and cumulative sleep improvements. These associations remained significant after controlling for motor improvements.

DISCUSSION

Our findings suggest that STN-DBS may modulate sleep via broader structural connections and beyond motor symptom improvements. The lateralised effects and involvement of widespread tracts underscore the complexity of DBS-related sleep modulation. Future studies should incorporate longitudinal designs and objective measures to disentangle motor-independent mechanisms and optimise therapeutic strategies.

Subthalamic nucleus dynamics during executive functioning: Insights from local field potentials in Parkinson's disease

This study explores the involvement of the subthalamic nucleus (STN) in executive functions, particularly cognitive flexibility, in Parkinson's disease (PD) patients. Utilizing a computerized Wisconsin Card Sorting Task (WCST) and local field potential (LFP) recordings from implanted deep brain stimulation (DBS) electrodes, we investigated task-specific neural dynamics. Behavioural results demonstrated increased error rates and prolonged response times in trials requiring set-shifting and rule induction via cross-temporal information integration. Electrophysiological analyses revealed integration-specific LFP modulations, including enhanced theta-band activity linked to conflict monitoring and cognitive control during high-demand trials, and beta-band suppression associated with motor inhibition and task disengagement. These findings underscore the STN's integrative role in non-motor domains, supporting its function in cross-temporal information integration for cognitive control. The results also highlight the utility of the WCST for assessing multiple executive processes and the potential of LFP-based biomarkers to refine DBS programming. Despite the relatively small sample size, this study provides novel insights into the oscillatory dynamics of the STN, emphasizing its broader role in decision-making and executive control. Future research should expand the understanding of the STN's contributions across cognitive domains.

Evaluation of DBS computational modeling methodologies using in-vivo electrophysiology in Parkinson's disease

Deep brain stimulation (DBS) is an effective therapy for Parkinson's disease (PD) and other neuropsychiatric disorders, but its outcomes vary due to differences in patient selection, electrode placement, and programming. Optimizing DBS parameter settings requires postoperative adjustments through a trial-and-error process, which is complex and time-consuming. As such, researchers have been developing patient-specific computational models to help guide DBS programming. Despite growing interest in image-guided DBS technology, and recent adoption into clinical practice, the direct validation of the prediction accuracy remains limited. The objective of this study was to establish a comparative framework for validating the accuracy of various DBS computational modeling methodologies in predicting the activation of clinically relevant pathways using in vivo measurements from PD patients undergoing subthalamic (STN) DBS surgery. Our prior work assessed the accuracy of driving force (DF) models in native space by predicting activation of the corticospinal/bulbar tract (CSBT) and cortico-subthalamic hyperdirect pathway (HDP) using very short- (<2 ms) and short-latency (2-4 ms) cortical evoked potentials (cEPs). In this study, we extended our previous work by comparing the accuracy of five computational modeling variations for predicting the activation of HDP and CSBT based on three key factors: modeling method (DF vs. Volume of Tissue Activated [VTA]), imaging space (native vs. normative), and anatomical representation (pathway vs. volume). The model performances were quantified using the coefficient of determination (R2) between the cEP amplitudes and percent pathway activation or percent volume (structure) overlap. We compared model accuracy for 11 PD patients. The DF-Native-Pathway model was the most accurate method for quantitatively predicting experimental subcortical pathway activations. Additionally, our analysis showed that using normative brain space, instead of native (i.e., patient-specific) space, significantly diminished the accuracy of model predictions. Although the DF and VTA modeling methods exhibited comparable accuracy for the hyperdirect pathway, they diverged significantly in their predictions for the corticospinal tract. In conclusion, we believe that the choice of methodology should depend on the specific application and the required level of precision in clinical, surgical, or research settings. These findings offer valuable guidance for developing more accurate models, facilitating reliable DBS outcome predictions, and advancing both clinical practice and research.

The Deep Brain Stimulation Response Network in Parkinson's Disease Operates in the High Beta Band

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) improves motor symptoms in patients with Parkinson's disease. Using functional MRI, optimal DBS response networks have been characterized. However, neural activity associated with Parkinsonian symptoms is magnitudes faster than what can be resolved by this method. While both spatial and temporal domains of these networks appear critical, no single study has yet investigated both domains simultaneously. Here, we aim to close this gap using subthalamic local field potentials that were concurrently recorded alongside whole-brain magnetoencephalography in a multi-center cohort of patients that underwent STN-DBS for the treatment of Parkinson's disease (N = 100 hemispheres). In every cortical vertex, cortico-subthalamic coupling was correlated with stimulation outcomes. This network spatially resembled fMRI-based findings (R = 0.40, P = 0.039) and explained significant amounts of variance in clinical outcomes (β std = 0.30, P = 0.002), while theta-alpha and low beta coupling did not show significant associations with DBS response (theta-alpha: β std = -0.02, P = 0.805; low beta: β std = -0.08, P = 0.426). The 'optimal' high beta coupling map was robust when subjected to various cross-validation designs (10-fold cross-validation: R = 0.29, P = 0.009; split-half design: R = 0.31, P = 0.026) and was able to predict outcomes across DBS centers (R = 0.74; P (1) = 8.9e-5). We identified a DBS response network that i) resembles the previously defined MRI network and ii) operates in the high-beta band. Maximal connectivity to this network was associated with optimal DBS outcomes and was able to cross-predict clinical improvements across DBS surgeons and centers.

A technology framework for distributed preoperative planning and medical training in deep brain stimulation

Deep brain stimulation (DBS) is a groundbreaking therapy for movement disorders, necessitating precise planning and extensive training to ensure accurate electrode placement in critical brain regions, such as the thalamic nuclei. This paper introduces an innovative technology framework for DBS to support distributed, real-time preoperative planning and medical training. The system integrates advanced imaging techniques, interactive graphical representation, and real-time data synchronization to assist clinicians in accurately identifying essential anatomical structures and refining pre-surgical plans. At the platform's core are multi-volume rendering, segmentation, and virtual tool modeling algorithms that employ transparency and refinement controls to seamlessly merge and visualize different tissue types in 3D alongside their interactions with surgical tools. This method enhances visual clarity and provides a highly detailed depiction of crucial structures, ensuring the precision required for effective DBS planning. By delivering dynamic, real-time feedback, the framework supports improved decision-making and sets a new standard for collaborative DBS training and procedural preparation. The platform's web-based synchronization architecture enhances collaboration by allowing neurologists and surgeons to simultaneously interact with visualized data from any location. This functionality supports live feedback, promotes collaborative decision-making, and streamlines procedural planning, leading to improved surgical outcomes. Performance evaluations across various hardware configurations and web browsers demonstrate the platform's high rendering speed and low-latency data synchronization, ensuring responsive and reliable interactions essential for clinical use. Its adaptability makes it suitable for medical training, preoperative planning, and intraoperative support, accommodating a wide range of hardware setups and web environments to address the specific demands of DBS-related procedures. This research lays a robust foundation for advancing distributed clinical planning, comprehensive medical education, and improved patient care in neurostimulation therapies.

A Computational Study on the Activation of Neural Transmission in Deep Brain Stimulation

Deep brain stimulation (DBS) is an established treatment for neurodegenerative movement disorders such as Parkinson's disease that mitigates symptoms by overwriting pathological signals from the central nervous system to the motor system. Nearly all computational models of DBS, directly or indirectly, associate clinical improvements with the extent of fiber activation in the vicinity of the stimulating electrode. However, it is not clear how such activation modulates information transmission. Here, we use the exact cable equation for straight or curved axons and show that DBS segregates the signaling pathways into one of the three communicational modes: complete information blockage, uni-, and bi-directional transmission. Furthermore, all these modes respond to the stimulating pulse in an asynchronous but frequency-locked fashion. Asynchrony depends on the geometry of the axon, its placement and orientation, and the stimulation protocol. At the same time, the electrophysiology of the nerve determines frequency-locking. Such a trimodal response challenges the notion of activation as a binary state and studies that correlate it with the DBS outcome. Importantly, our work suggests that a mechanistic understanding of DBS action relies on distinguishing between these three modes of information transmission.

Bioelectronic Therapeutics: A Revolutionary Medical Practice in Health Care

The emerging field of bioelectronic therapeutics unfolds great opportunities for treating numerous neurological and inflammatory conditions by utilizing the amalgamation of molecular medicine, neuroscience, engineering, and computing. These innovative treatments leverage advanced technology to precisely identify, design, and regulate electrical signaling patterns in the nervous system, addressing multiple diseases. Modifying neural signaling patterns to produce therapeutic effects at a particular organ may blur the lines between conventional medical practices. These modify the neurological behavior using electrical, magnetic, optical, and ultrasonic pulses through closed-loop systems to optimize neural behavior. The Food and Drug Administration (FDA) has approved numerous invasive and noninvasive bioelectronic devices, in the treatment of various neuronal diseases and non-neuronal diseases. Furthermore, the FDA has approved many devices for clinical studies. The field of bioelectronics encounters challenges in integrating with the health care system, including incomplete understanding of human nervous anatomy, neuronal function, membrane potential, and technological limitations. This review aims to explore bioelectronics therapeutics, their role or action in challenges to growth and their solutions, and the prospects of bioelectronic therapeutics.

Subthalamic Nucleus Deep Brain Stimulation in the Beta Frequency Range Boosts Cortical Beta Oscillations and Slows Down Movement

Recordings from Parkinson's disease (PD) patients show strong beta-band oscillations (13-35 Hz), which can be modulated by deep brain stimulation (DBS). While high-frequency DBS (>100 Hz) ameliorates motor symptoms and reduces beta activity in the basal ganglia and motor cortex, the effects of low-frequency DBS (<30 Hz) are less clear. Clarifying these effects is relevant for the debate about the role of beta oscillations in motor slowing, which might be causal or epiphenomenal. Here, we investigated how subthalamic nucleus (STN) beta-band DBS affects cortical beta oscillations and motor performance. We recorded the magnetoencephalogram of 14 PD patients (nine males) with DBS implants while on their usual medication. Following a baseline recording (DBS OFF), we applied bipolar DBS at beta frequencies (10, 16, 20, 26, and 30 Hz) via the left electrode in a cyclic fashion, turning stimulation on (5 s) and off (3 s) repeatedly. Cyclic stimulation was applied at rest and during right-hand finger tapping. In the baseline recording, we observed a negative correlation between the strength of hemispheric beta power lateralization and the tap rate. Importantly, beta-band DBS accentuated the lateralization and reduced the tap rate proportionally. The change in lateralization was specific to the alpha/beta range (8-26 Hz), outlasted stimulation, and did not depend on the stimulation frequency, suggesting a remote-induced response rather than entrainment. Our study demonstrates that cortical beta oscillations can be manipulated by STN beta-band DBS. This manipulation has consequences for motor performance, supporting a causal role of beta oscillations.

Treatment of pediatric drug-resistant generalized epilepsy with responsive neurostimulation of the centromedian nucleus of the thalamus: A case series of seven patients

PURPOSE

Responsive neurostimulation of the centromedian nucleus of the thalamus (CM RNS) is being investigated for treatment of drug-resistant generalized epilepsy with promising results. The aim of this study is to report outcomes of seven patients with pediatric-onset drug-resistant generalized epilepsy, including both genetic generalized epilepsy (GGE) and Lennox-Gastaut syndrome (LGS), who underwent treatment with bilateral CM RNS.

METHODS

A retrospective chart review was performed for patients with drug-resistant generalized epilepsy who underwent treatment with bilateral CM RNS at Children's Hospital of Pittsburgh from 2020 to 2022. Improvement in seizure frequency was obtained through patient and/or caregiver reports on standardized patient questionnaires. The primary outcome measure was percent improvement in seizure frequency at time of last follow-up appointment compared to baseline seizure frequency.

RESULTS

Five of the seven patients (71 %) had an average 50 % or greater improvement in seizure frequency among seizure types including four of the five patients (80 %) with GGE and one of the two patients (50 %) with LGS. There were no serious adverse events including post-operative infection, stroke, or device malfunction/migration.

CONCLUSION

This data, along with other recent studies, suggests that CM RNS can improve seizure frequency in pediatric-onset drug-resistant generalized epilepsy, but larger systematic studies with longer follow-up times and standardized outcome measures are needed to determine long-term effectiveness and optimal patient selection for thalamic RNS.

Deep Brain Stimulation Lead Functional Repositioning After Spontaneous Pneumocephalus Resorption: A Clinical Case Presentation and Systematic Review

Deep brain stimulation (DBS) has become a critical intervention for managing advanced Parkinson's disease (PD), particularly for patients whose symptoms are no longer controlled by medication. This report details the case of a 61-year-old male with PD who experienced electrode displacement due to pneumocephalus following DBS surgery targeting the subthalamic nucleus (STN). Initial imaging revealed a significant subdural air volume causing electrode displacement. However, one month later, spontaneous pneumocephalus resorption led to the functional repositioning of the electrodes, restoring proper function and negating the need for reoperation. The accompanying systematic review analyzed 24 studies, involving 1,439 patients across 12 countries, to assess the occurrence and management in this specific scenario. Findings showed electrode displacement occurred in 75% of cases, but spontaneous repositioning happened only in 12.5%, typically with air volumes below 10 cm³. Larger volumes often required surgical intervention, though definitive thresholds for action remain unclear. The review highlights inconsistencies in managing this complication, emphasizing the need for clearer protocols to improve outcomes. This work underscores the rarity of spontaneous electrode realignment and the importance of careful evaluation of pneumocephalus volume and patient symptoms. It advocates for evidence-based management strategies to balance clinical intervention with the potential for natural resolution, aiming to enhance DBS efficacy and patient quality of life. Further research is necessary to establish standardized guidelines for addressing this complication.

Statistical Multiscore Functional Atlas Creation for Image-Guided Deep Brain Stimulation

Deep brain stimulation is increasingly performed for patients who suffer from drug-resistant movement disorders. It still remains challenging to determine the optimal electrode contact location to obtain the optimal surgical outcome and simultaneously minimize adverse effects. This paper proposes to construct a new statistical functional atlas to guide electrode contact targeting during deep brain stimulation. The construction of the atlas consists of four main steps: 1) multimodal image segmentation and registration, 2) activation volume modeling, 3) computing and combining multiple functional scores, and 4) generation of multiscore functional atlas. Based on these steps, the statistical functional atlas is created by integrating anatomical information analysis with multiple clinical scores that postoperatively characterize stimulation efficacy (e.g., motor symptom) and adverse effect. We evaluated the created atlas on 40 subthalamic nucleus stimulated parkinsonian patient datasets. The experimental results show that the reproducibility of the created statistical functional atlas was more than 75% in the cross validation. In addition, the motor, neuropsychological, and health scores can be reproduced up to 77%, 82%, and 78%. Compared to the actually implanted electrode position, the atlas predicted and the manually planned electrode position errors were 2.89 mm and 2.38 mm, respectively. The constructed multiscore atlas provides an automatic and accurate electrode targeting strategy that potentially outperforms manually planned approaches.

Deep brain stimulation of the motor thalamus relieves experimentally induced air hunger

RESEARCH QUESTION

We previously reported that deep brain stimulation (DBS) of the motor thalamus, in a patient with post-stroke tremor, relieved breathlessness associated with COPD. This raised the question of whether motor thalamus DBS mitigates the ascending dyspnoea signal. We therefore sought to conduct a fully powered cohort study of experimentally induced air hunger, an uncomfortable urge to breathe in patients with motor thalamus DBS "ON" and "OFF".

METHODS

16 patients (three females) with DBS of the ventral intermediate nucleus (VIM) as treatment for tremor underwent hypercapnic air hunger tests, with DBS ON and OFF. Patients rated air hunger on a visual analogue scale (VAS) every 15 s. Hypercapnia and ventilation were matched for ON and OFF states (end-tidal carbon dioxide tension mean±sd 43±4 and 43±4 mmHg, respectively; ventilation 13.7 and 13.4 L·min-1, respectively). Participants' ventilation was constrained to baseline levels by breathing from a 3-L inspiratory reservoir with fixed flow of fresh gas while targeting their resting breathing frequency to a metronome.

RESULTS

Overall steady-state air hunger was 52±28%VAS for ON and 67±20%VAS for OFF (p=0.002; two-tailed paired t-test). The mean reduction in air hunger during VIM DBS was -14.4%VAS. DBS of the motor thalamus relieved air hunger in 13 patients, heightened air hunger in two and caused no change in one.

CONCLUSION

DBS of the motor thalamus for tremor relief also mitigates the air hunger component of dyspnoea. We posit that DBS of the motor thalamus heightens the gating control of the thalamus modulating the ascending air hunger signal. Extent of relief suggests that thalamic DBS may prove to be a viable therapy for intractable dyspnoea.

Hypothalamic deep brain stimulation augments walking after spinal cord injury

A spinal cord injury (SCI) disrupts the neuronal projections from the brain to the region of the spinal cord that produces walking, leading to various degrees of paralysis. Here, we aimed to identify brain regions that steer the recovery of walking after incomplete SCI and that could be targeted to augment this recovery. To uncover these regions, we constructed a space-time brain-wide atlas of transcriptionally active and spinal cord-projecting neurons underlying the recovery of walking after incomplete SCI. Unexpectedly, interrogation of this atlas nominated the lateral hypothalamus (LH). We demonstrate that glutamatergic neurons located in the LH (LHVglut2) contribute to the recovery of walking after incomplete SCI and that augmenting their activity improves walking. We translated this discovery into a deep brain stimulation therapy of the LH (DBSLH) that immediately augmented walking in mice and rats with SCI and durably increased recovery through the reorganization of residual lumbar-terminating projections from brainstem neurons. A pilot clinical study showed that DBSLH immediately improved walking in two participants with incomplete SCI and, in conjunction with rehabilitation, mediated functional recovery that persisted when DBSLH was turned off. There were no serious adverse events related to DBSLH. These results highlight the potential of targeting specific brain regions to maximize the engagement of spinal cord-projecting neurons in the recovery of neurological functions after SCI. Further trials must establish the safety and efficacy profile of DBSLH, including potential changes in body weight, psychological status, hormonal profiles and autonomic functions.

Evaluating a motor progression connectivity model across Parkinson's disease stages

BACKGROUND

Stimulation of a specific site in the dorsolateral subthalamic nucleus (STN) was recently associated with slower motor progression in Parkinson's Disease (PD), based on the deep brain stimulation (DBS) in early-stage PD pilot clinical trial. Here, subject-level visualizations are presented of this early-stage PD dataset to further describe the relationship between active contacts and motor progression. This study also evaluates whether stimulation of the sweet spot and connectivity model associated with slower motor progression is also associated with improvements in long-term motor outcomes in patients with advanced-stage PD.

METHODS

Active contacts of the early-stage PD cohort (N = 14) were analyzed alongside the degree of two-year motor progression. Sweet spot and connectivity models derived from the early-stage PD cohort were then used to determine how well they can estimate the variance in long-term motor outcomes in an independent STN-DBS cohort of advanced-stage PD patients (N = 29).

RESULTS

In early-stage PD, proximity of stimulation to the dorsolateral STN was associated with slower motor progression. In advanced-stage PD, stimulation proximity to the early PD connectivity model and sweet spot were associated with better long-term motor outcomes (R = 0.60, P < 0.001; R = 0.37, P = 0.046, respectively).

CONCLUSIONS

Results suggest stimulation of a specific site in the dorsolateral STN is associated with both slower motor progression and long-term motor improvements in PD.

Randomized crossover trial on motor and non-motor outcome of directional deep brain stimulation in Parkinson's disease

Deep brain stimulation (DBS) with electric field steering may avoid areas responsible for side effects. This prospective randomized cross-over trial compared omnidirectional (OS) and directional (DS) subthalamic DBS in 19 patients. Electromyographically measured rigidity was the primary outcome. Motor and non-motor scores were secondary outcomes. There were no significant differences between OS and DS. In the acute setting, both conditions improved motor scores compared to no stimulation. Motor symptoms improved after 3 weeks of OS relative to acute measurements, whereas they worsened under DS. The more ventral the active contact, and the less the motor improvement sweet spot was stimulated, the greater the benefit of DS over OS for executive function. Accurate OS of the dorsal subthalamic nucleus ensures motor and non-motor improvements. While DS can mitigate executive decline stemming from off-target stimulation, it may lead to worse motor outcomes. Larger, long-term studies are needed to confirm these findings. (Registration: subthalamic steering for therapy optimization in Parkinson's Disease ClinicalTrials.gov: NCT03548506, 2018-06-06).

Predictive modeling of sensory responses in deep brain stimulation

Introduction

Although stimulation-induced sensations are typically considered undesirable side effects in clinical DBS therapy, there are emerging scenarios, such as computer-brain interface applications, where these sensations may be intentionally created. The selection of stimulation parameters, whether to avoid or induce sensations, is a challenging task due to the vast parameter space involved. This study aims to streamline DBS parameter selection by employing a machine learning model to predict the occurrence and somatic location of paresthesias in response to thalamic DBS.

Methods

We used a dataset comprising 3,359 paresthetic sensations collected from 18 thalamic DBS leads from 10 individuals in two clinical centers. For each stimulation, we modeled the Volume of Tissue Activation (VTA). We then used the stimulation parameters and the VTA information to train a machine learning model to predict the occurrence of sensations and their corresponding somatic areas.

Results

Our results show fair to substantial agreement with ground truth in predicting the presence and somatic location of DBS-evoked paresthesias, with Kappa values ranging from 0.31 to 0.72. We observed comparable performance in predicting the presence of paresthesias for both seen and unseen cases (Kappa 0.72 vs. 0.60). However, Kappa agreement for predicting specific somatic locations was significantly lower for unseen cases (0.53 vs. 0.31).

Conclusion

The results suggest that machine learning can potentially be used to optimize DBS parameter selection, leading to faster and more efficient postoperative management. Outcome predictions may be used to guide clinical DBS programming or tuning of DBS based computer-brain interfaces.

Disruption of neural periodicity predicts clinical response after deep brain stimulation for obsessive-compulsive disorder

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.

Centromedian region thalamic responsive neurostimulation mitigates idiopathic generalized and multifocal epilepsy with focal to bilateral tonic-clonic seizures

OBJECTIVE

Although >30% of epilepsy patients have drug-resistant epilepsy (DRE), typically those with generalized or multifocal disease have not traditionally been considered surgical candidates. Responsive neurostimulation (RNS) of the centromedian (CM) region of the thalamus now appears to be a promising therapeutic option for this patient population. We present outcomes following CM RNS for 13 patients with idiopathic generalized epilepsy (IGE) and eight with multifocal onsets that rapidly generalize to bilateral tonic-clonic (focal to bilateral tonic-clonic [FBTC]) seizures.

METHODS

A retrospective review of all patients undergoing bilateral CM RNS by the senior author through July 2022 were reviewed. Electrodes were localized and volumes of tissue activation were modeled in Lead-DBS. Changes in patient seizure frequency were extracted from electronic medical records.

RESULTS

Twenty-one patients with DRE underwent bilateral CM RNS implantation. For 17 patients with at least 1 year of postimplantation follow-up, average seizure reduction from preoperative baseline was 82.6% (SD = 19.0%, median = 91.7%), with 18% of patients Engel class 1, 29% Engel class 2, 53% Engel class 3, and 0% Engel class 4. There was a trend for average seizure reduction to be greater for patients with nonlesional FBTC seizures than for other patients. For patients achieving at least Engel class 3 outcome, median time to worthwhile seizure reduction was 203.5 days (interquartile range = 110.5-343.75 days). Patients with IGE with myoclonic seizures had a significantly shorter time to worthwhile seizure reduction than other patients. The surgical targeting strategy evolved after the first four subjects to achieve greater anatomic accuracy.

SIGNIFICANCE

Patients with both primary and rapidly generalized epilepsy who underwent CM RNS experienced substantial seizure relief. Subsets of these patient populations may particularly benefit from CM RNS. The refinement of lead targeting, tuning of RNS system parameters, and patient selection are ongoing areas of investigation.

Pallidal multifractal complexity is a new potential physiomarker of dystonia

OBJECTIVE

Low-frequency 4-12 Hz pallidal oscillations are being considered as potential physiomarkers for dystonia. We suggest investigating the multifractal properties of pallidal activity as an additional marker.

METHODS

We employed local field potentials (LFP) recordings from 23 patients with dystonia who were undergoing deep brain stimulation (DBS) surgery to explore the connection between disease severity and the multifractal characteristics of pallidal activity. Furthermore, we performed an analysis of LFP recordings from four patients, following the externalization of DBS lead electrodes, to investigate the impact of DBS and neck muscle vibration on multifractal parameters.

RESULTS

Greater dystonia severity exhibited a correlation with a narrower multifractal spectrum width but higher multifractal spectral asymmetry. Both GPi DBS and muscle vibration in dystonia patients expanded the multifractal spectrum width while restoring multifractal spectral symmetry. Notably, the threshold peak intensities for an increase in multifractal spectrum width substantially overlapped with the optimal volume of tissue activated. A broader multifractal spectrum during DBS corresponded to more favorable clinical outcomes.

CONCLUSIONS

Multifractal properties of pallidal neuronal activity serve as indicators of neural dysfunction in dystonia.

SIGNIFICANCE

These findings suggest the potential of utilizing multifractal characteristics as predictive factors for the DBS outcome in dystonia.

Deep brain stimulation of symptom-specific networks in Parkinson's disease

Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.

Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor

Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.

A large normative connectome for exploring the tractographic correlates of focal brain interventions

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics - the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts - have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

Chronic Pallidal Local Field Potentials Are Associated With Dystonic Symptoms in Children

BACKGROUND

Novel deep brain stimulation devices can record local field potentials (LFPs), which represent the synchronous synaptic activity of neuronal populations. The clinical relevance of LFPs in patients with dystonia remains unclear.

OBJECTIVES

We sought to determine whether chronic LFPs recorded from the globus pallidus internus (GPi) were associated with symptoms of dystonia in children.

MATERIALS AND METHODS

Ten patients with heterogeneous forms of dystonia (genetic and acquired) were implanted with neurostimulators that recorded LFP spectral snapshots. Spectra were compared across parent-reported asymptomatic and symptomatic periods, with daily narrowband data superimposed in 24 one-hour bins.

RESULTS

Spectral power increased during periods of registered dystonic symptoms: mean increase = 102%, CI: (76.7, 132). Circadian rhythms within the LFP narrowband time series correlated with dystonic symptoms: for delta/theta-waves, correlation = 0.33, CI: (0.18, 0.47) and for alpha waves, correlation = 0.27, CI: (0.14, 0.40).

CONCLUSIONS

LFP spectra recorded in the GPi indicate a circadian pattern and are associated with the manifestation of dystonic symptoms.

Structural connectivity of low-frequency subthalamic stimulation for improving stride length in Parkinson's disease

BACKGROUND

A reduction in stride length is considered a key characteristic of gait kinematics in Parkinson's disease (PD) and has been identified as a predictor of falls. Although low-frequency stimulation (LFS) has been suggested as a method to improve gait characteristics, the underlying structural network is not well understood.

OBJECTIVE

This study aims to investigate the structural correlates of changes in stride length during LFS (85 Hz).

METHODS

Objective gait performance was retrospectively evaluated in 19 PD patients who underwent deep brain stimulation (DBS) at 85 Hz and 130 Hz. Individual DBS contacts and volumes of activated tissue (VAT) were computed using preoperative magnetic resonance imaging (MRI) and postoperative computed tomography (CT) scans. Structural connectivity profiles to predetermined cortical and mesencephalic areas were estimated using a normative connectome.

RESULTS

LFS led to a significant improvement in stride length compared to 130 Hz stimulation. The intersection between VAT and the associative subregion of the subthalamic nucleus (STN) was associated with an improvement in stride length and had structural connections to the supplementary motor area, prefrontal cortex, and pedunculopontine nucleus. Conversely, we found that a lack of improvement was linked to stimulation volumes connected to cortico-diencephalic fibers bypassing the STN dorsolaterally. The robustness of the connectivity model was verified through leave-one-patient-out, 5-, and 10-fold cross cross-validation paradigms.

CONCLUSION

These findings offer new insights into the structural connectivity that underlies gait changes following LFS. Targeting the non-motor subregion of the STN with LFS on an individual level may present a potential therapeutic approach for PD patients with gait disorders.

Modeling brain network flexibility in networks of coupled oscillators: a feasibility study

Modeling the functionality of the human brain is a major goal in neuroscience for which many powerful methodologies have been developed over the last decade. The impact of working memory and the associated brain regions on the brain dynamics is of particular interest due to their connection with many functions and malfunctions in the brain. In this context, the concept of brain flexibility has been developed for the characterization of brain functionality. We discuss emergence of brain flexibility that is commonly measured by the identification of changes in the cluster structure of co-active brain regions. We provide evidence that brain flexibility can be modeled by a system of coupled FitzHugh-Nagumo oscillators where the network structure is obtained from human brain Diffusion Tensor Imaging (DTI). Additionally, we propose a straightforward and computationally efficient alternative macroscopic measure, which is derived from the Pearson distance of functional brain matrices. This metric exhibits similarities to the established patterns of brain template flexibility that have been observed in prior investigations. Furthermore, we explore the significance of the brain's network structure and the strength of connections between network nodes or brain regions associated with working memory in the observation of patterns in networks flexibility. This work enriches our understanding of the interplay between the structure and function of dynamic brain networks and proposes a modeling strategy to study brain flexibility.

Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation

Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.

Motivational and cognitive predictors of apathy after subthalamic nucleus stimulation in Parkinson's disease

Postoperative apathy is a frequent symptom in Parkinson's disease patients who have undergone bilateral deep brain stimulation of the subthalamic nucleus. Two main hypotheses for postoperative apathy have been suggested: (i) dopaminergic withdrawal syndrome relative to postoperative dopaminergic drug tapering; and (ii) direct effect of chronic stimulation of the subthalamic nucleus. The primary objective of our study was to describe preoperative and 1-year postoperative apathy in Parkinson's disease patients who underwent chronic bilateral deep brain stimulation of the subthalamic nucleus. We also aimed to identify factors associated with 1-year postoperative apathy considering: (i) preoperative clinical phenotype; (ii) dopaminergic drug management; and (iii) volume of tissue activated within the subthalamic nucleus and the surrounding structures. We investigated a prospective clinical cohort of 367 patients before and 1 year after chronic bilateral deep brain stimulation of the subthalamic nucleus. We assessed apathy using the Lille Apathy Rating Scale and carried out a systematic evaluation of motor, cognitive and behavioural signs. We modelled the volume of tissue activated in 161 patients using the Lead-DBS toolbox and analysed overlaps within motor, cognitive and limbic parts of the subthalamic nucleus. Of the 367 patients, 94 (25.6%) exhibited 1-year postoperative apathy: 67 (18.2%) with 'de novo apathy' and 27 (7.4%) with 'sustained apathy'. We observed disappearance of preoperative apathy in 22 (6.0%) patients, who were classified as having 'reversed apathy'. Lastly, 251 (68.4%) patients had neither preoperative nor postoperative apathy and were classified as having 'no apathy'. We identified preoperative apathy score [odds ratio (OR) 1.16; 95% confidence interval (CI) 1.10, 1.22; P < 0.001], preoperative episodic memory free recall score (OR 0.93; 95% CI 0.88, 0.97; P = 0.003) and 1-year postoperative motor responsiveness (OR 0.98; 95% CI 0.96, 0.99; P = 0.009) as the main factors associated with postoperative apathy. We showed that neither dopaminergic dose reduction nor subthalamic stimulation were associated with postoperative apathy. Patients with 'sustained apathy' had poorer preoperative fronto-striatal cognitive status and a higher preoperative action initiation apathy subscore. In these patients, apathy score and cognitive status worsened postoperatively despite significantly lower reduction in dopamine agonists (P = 0.023), suggesting cognitive dopa-resistant apathy. Patients with 'reversed apathy' benefited from the psychostimulant effect of chronic stimulation of the limbic part of the left subthalamic nucleus (P = 0.043), suggesting motivational apathy. Our results highlight the need for careful preoperative assessment of motivational and cognitive components of apathy as well as executive functions in order to better prevent or manage postoperative apathy.

Image-guided programming deep brain stimulation improves clinical outcomes in patients with Parkinson's disease

Deep brain stimulation (DBS) is an effective treatment for patients with Parkinson's disease (PD). However, some patients may not respond optimally to clinical programming adjustments. Advances in DBS technology have led to more complex and time-consuming programming. Image-guided programming (IGP) could optimize and improve programming leading to better clinical outcomes in patients for whom DBS programming is not ideal due to sub-optimal response. We conducted a prospective single-center study including 31 PD patients with subthalamic nucleus (STN) DBS and suboptimal responses refractory to clinical programming. Programming settings were adjusted according to the volumetric reconstruction of the stimulation field using commercial postoperative imaging software. Clinical outcomes were assessed at baseline and at 3-month follow-up after IGP, using motor and quality of life (QoL) scales. Additionally, between these two assessment points, follow-up visits for fine-tuning amplitude intensity and medication were conducted at weeks 2, 4, 6, and 9. After IGP, twenty-six patients (83.9%) experienced motor and QoL improvements, with 25.8% feeling much better and 38.7% feeling moderately better according to the patient global impression scale. Five patients (16.1%) had no clinical or QoL changes after IGP. The MDS-UPDRS III motor scale showed a 21.9% improvement and the DBS-IS global score improved by 41.5%. IGP optimizes STN-DBS therapy for PD patients who are experiencing suboptimal clinical outcomes. These findings support using IGP as a standard tool in clinical practice, which could save programming time and improve patients' QoL.

WarpDrive: Improving spatial normalization using manual refinements

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

One-pass deep brain stimulation of subthalamic nucleus and ventral intermediate nucleus for levodopa-resistant tremor-dominant Parkinson's disease

Objective

Tremor-dominant Parkinson's disease (TD-PD) can be further separated into levodopa-responsive and levodopa-resistant types, the latter being considered to have a different pathogenesis. Previous studies indicated that deep brain stimulation (DBS) of the subthalamic nucleus (STN) or the globus pallidus internus (GPi) individually was not sufficient for tremor control, especially for the levodopa-resistant TD-PD (LRTD-PD). The thalamic ventral intermediate nucleus (VIM) has been regarded as a potent DBS target for different kinds of tremors. Therefore, we focused on the LRTD-PD subgroup and performed one-pass combined DBSs of STN and VIM to treat refractory tremors, aiming to investigate the safety and effectiveness of this one-trajectory dual-target DBS scheme.

Methods

We retrospectively collected five LRTD-PD patients who underwent a one-pass combined DBS of STN and VIM via a trans-frontal approach. The targeting of VIM was achieved by probabilistic tractography. Changes in severity of symptoms (measured by the Unified Parkinson Disease Rating Scale part III, UPDRS-III), levodopa equivalent daily doses (LEDD), and disease-specific quality of life (measured by the 39-item Parkinson's Disease Questionnaire, PDQ-39) were evaluated.

Results

Three-dimensional reconstruction of electrodes illustrated that all leads were successfully implanted into predefined positions. The mean improvement rates (%) were 53 ± 6.2 (UPDRS-III), 82.6 ± 11.4 (tremor-related items of UPDRS), and 52.1 ± 11.4 (PDQ-39), respectively, with a mean follow-up of 11.4 months.

Conclusion

One-pass combined DBS of STN and VIM via the trans-frontal approach is an effective and safe strategy to alleviate symptoms for LRTD-PD patients.

Thalamic connections of the caudal part of the posterior parietal cortex differ from the rostral part in galagos (Otolemur garnettii)

In this study, thalamic connections of the caudal part of the posterior parietal cortex (PPCc) are described and compared to connections of the rostral part of PPC (PPCr) in strepsirrhine galagos. PPC of galagos is divided into two parts, PPCr and PPCc, based on the responsiveness to electrical stimulation. Stimulation of PPC with long trains of electrical pulses evokes different types of ethologically relevant movements from different subregions ("domains") of PPCr, while it fails to evoke any movements from PPCc. Anatomical tracers were placed in both dorsal and ventral divisions of PPCc to reveal thalamic origins and targets of PPCc connections. We found major thalamic connections of PPCc with the lateral posterior and lateral pulvinar nuclei, distinct from those of PPCr that were mainly with the ventral lateral, anterior pulvinar, and posterior nuclei. The anterior, medial, and inferior pulvinar, ventral anterior, ventral lateral, and intralaminar nuclei had fewer connections with PPCc. Dominant connections of PPCc with lateral posterior and lateral pulvinar nuclei provide evidence that unlike the sensorimotor-orientated PPCr, PPCc is more involved in visual-related functions.

Intelligibility of speech in Parkinson's disease relies on anatomically segregated subthalamic beta oscillations

BACKGROUND

Speech impairment is commonly reported in Parkinson's disease and is not consistently improved by available therapies - including deep brain stimulation of the subthalamic nucleus (STN-DBS), which can worsen communication performance in some patients. Improving the outcome of STN-DBS on speech is difficult due to our incomplete understanding of the contribution of the STN to fluent speaking.

OBJECTIVE

To assess the relationship between subthalamic neural activity and speech production and intelligibility.

METHODS

We investigated bilateral STN local field potentials (LFPs) in nine parkinsonian patients chronically implanted with DBS during overt reading. LFP spectral features were correlated with clinical scores and measures of speech intelligibility.

RESULTS

Overt reading was associated with increased beta-low ([1220) Hz) power in the left STN, whereas speech intelligibility correlated positively with beta-high ([2030) Hz) power in the right STN.

CONCLUSION

We identified separate contributions from frequency and brain lateralization of the STN in the execution of an overt reading motor task and its intelligibility. This subcortical organization could be exploited for new adaptive stimulation strategies capable of identifying the occurrence of speaking behavior and facilitating its functional execution.

Mapping Dysfunctional Circuits in the Frontal Cortex Using Deep Brain Stimulation

Frontal circuits play a critical role in motor, cognitive, and affective processing - and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)function remains largely elusive. Here, we study 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregate the frontal cortex into circuits that became dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to rostral, ranging from interconnections with sensorimotor cortices in dystonia, with the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairment in the human brain.

Connectivity Profile for Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson Disease

OBJECTIVE

This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial.

METHODS

To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baseline➔24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baseline➔24 months, MedON/StimON]).

RESULTS

Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort.

INTERPRETATION

These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.

Neuroimaging-based analysis of DBS outcomes in pediatric dystonia: Insights from the GEPESTIM registry

INTRODUCTION

Deep brain stimulation (DBS) is an established treatment in patients of various ages with pharmaco-resistant neurological disorders. Surgical targeting and postoperative programming of DBS depend on the spatial location of the stimulating electrodes in relation to the surrounding anatomical structures, and on electrode connectivity to a specific distribution pattern within brain networks. Such information is usually collected using group-level analysis, which relies on the availability of normative imaging resources (atlases and connectomes). Analysis of DBS data in children with debilitating neurological disorders such as dystonia would benefit from such resources, especially given the developmental differences in neuroimaging data between adults and children. We assembled pediatric normative neuroimaging resources from open-access datasets in order to comply with age-related anatomical and functional differences in pediatric DBS populations. We illustrated their utility in a cohort of children with dystonia treated with pallidal DBS. We aimed to derive a local pallidal sweetspot and explore a connectivity fingerprint associated with pallidal stimulation to exemplify the utility of the assembled imaging resources.

METHODS

An average pediatric brain template (the MNI brain template 4.5-18.5 years) was implemented and used to localize the DBS electrodes in 20 patients from the GEPESTIM registry cohort. A pediatric subcortical atlas, analogous to the DISTAL atlas known in DBS research, was also employed to highlight the anatomical structures of interest. A local pallidal sweetspot was modeled, and its degree of overlap with stimulation volumes was calculated as a correlate of individual clinical outcomes. Additionally, a pediatric functional connectome of 100 neurotypical subjects from the Consortium for Reliability and Reproducibility was built to allow network-based analyses and decipher a connectivity fingerprint responsible for the clinical improvements in our cohort.

RESULTS

We successfully implemented a pediatric neuroimaging dataset that will be made available for public use as a tool for DBS analyses. Overlap of stimulation volumes with the identified DBS-sweetspot model correlated significantly with improvement on a local spatial level (R = 0.46, permuted p = 0.019). The functional connectivity fingerprint of DBS outcomes was determined to be a network correlate of therapeutic pallidal stimulation in children with dystonia (R = 0.30, permuted p = 0.003).

CONCLUSIONS

Local sweetspot and distributed network models provide neuroanatomical substrates for DBS-associated clinical outcomes in dystonia using pediatric neuroimaging surrogate data. Implementation of this pediatric neuroimaging dataset might help to improve the practice and pave the road towards a personalized DBS-neuroimaging analyses in pediatric patients.

A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders

Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.

Structural-Functional Correlates of Response to Pedunculopontine Stimulation in a Randomized Clinical Trial for Axial Symptoms of Parkinson's Disease

BACKGROUND

Axial symptoms of Parkinson's disease (PD) can be debilitating and are often refractory to conventional therapies such as dopamine replacement therapy and deep brain stimulation (DBS) of the subthalamic nuclei (STN).

OBJECTIVE

Evaluate the efficacy of bilateral DBS of the pedunculopontine nucleus area (PPNa) and investigate structural and physiological correlates of clinical response.

METHODS

A randomized, double-blind, cross-over clinical trial was employed to evaluate the efficacy of bilateral PPNa-DBS on axial symptoms. Lead positions and neuronal activity were evaluated with respect to clinical response. Connectomic cortical activation profiles were generated based on the volumes of tissue activated.

RESULTS

PPNa-DBS modestly improved (p = 0.057) axial symptoms in the medication-off condition, with greatest positive effects on gait symptoms (p = 0.027). Electrode placements towards the anterior commissure (ρ= 0.912; p = 0.011) or foramen caecum (ρ= 0.853; p = 0.031), near the 50% mark of the ponto-mesencephalic junction, yielded better therapeutic responses. Recording trajectories of patients with better therapeutic responses (i.e., more anterior electrode placements) had neurons with lower firing-rates (p = 0.003) and higher burst indexes (p = 0.007). Structural connectomic profiles implicated activation of fibers of the posterior parietal lobule which is involved in orienting behavior and locomotion.

CONCLUSION

Bilateral PPNa-DBS influenced gait symptoms in patients with PD. Anatomical and physiological information may aid in localization of a favorable stimulation target.

Clinical outcome of imaging-based programming for anterior thalamic nucleus deep brain stimulation

OBJECTIVE

The authors hypothesized that the proximity of deep brain stimulator contacts to the anterior thalamic nucleus-mammillothalamic tract (ANT-MMT) junction determines responsiveness to treatment with ANT deep brain stimulation (DBS) in drug-resistant epilepsy and conducted this study to test that hypothesis.

METHODS

This retrospective study evaluated patients who had undergone ANT DBS electrode implantation and whose devices were programmed to stimulate nearest the ANT-MMT junction based on direct MRI visualization. The proximity of the active electrode to the ANT and the ANT-MMT junction was compared between responders (≥ 50% reduction in seizure frequency) and nonresponders. Linear regression was performed to assess the percentage of seizure reduction and distance to both the ANT and the ANT-MMT junction.

RESULTS

Four (57.1%) of 7 patients had ≥ 50% reduction in seizures. All 4 responders had at least one contact within 1 mm of the ANT-MMT junction, whereas the 3 patients with < 50% seizure improvement did not have a contact within 1 mm of the ANT-MMT junction. Additionally, the 4 responders demonstrated contact positioning closer to the ANT-MMT junction than the 3 nonresponders (mean distance from MMT: 0.7 mm on the left and 0.6 mm on the right in responders vs 3.0 mm on the left and 2.3 mm on the right in nonresponders). However, proximity of the electrode contact to any point in the ANT nucleus did not correlate with seizure reduction. Greater seizure improvement was correlated with a contact position closer to the ANT-MMT junction (R2 = 0.62, p = 0.04). Seizure improvement was not significantly correlated with proximity of the contact to any ANT border (R2 = 0.24, p = 0.26).

CONCLUSIONS

Obtained using a combination of direct visualization and targeted programming of the ANT-MMT junction, data in this study support the hypothesis that proximity to the ANT alone does not correlate with seizure reduction in ANT DBS, whereas proximity to the ANT-MMT junction does. These findings support the importance of direct targeting in ANT DBS, as well as imaging-informed programming. Additionally, the authors provide supportive evidence for future prospective trials using ANT-MMT junction for direct surgical targeting.

Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum

Objective. Deep brain stimulation is a treatment option for patients with refractory obsessive-compulsive disorder. A new generation of stimulators hold promise for closed loop stimulation, with adaptive stimulation in response to biologic signals. Here we aimed to discover a suitable biomarker in the ventral striatum in patients with obsessive compulsive disorder using local field potentials.Approach.We induced obsessions and compulsions in 11 patients undergoing deep brain stimulation treatment using a symptom provocation task. Then we trained machine learning models to predict symptoms using the recorded intracranial signal from the deep brain stimulation electrodes.Main results.Average areas under the receiver operating characteristics curve were 62.1% for obsessions and 78.2% for compulsions for patient specific models. For obsessions it reached over 85% in one patient, whereas performance was near chance level when the model was trained across patients. Optimal performances for obsessions and compulsions was obtained at different recording sites.Significance. The results from this study suggest that closed loop stimulation may be a viable option for obsessive-compulsive disorder, but that intracranial biomarkers are patient and not disorder specific.Clinical Trial:Netherlands trial registry NL7486.

Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Stimulation of non-motor subthalamic nucleus impairs selective response inhibition via prefrontal connectivity

Given the inconsistent results in the past, there is an ongoing debate whether and how deep brain stimulation in the subthalamic nucleus modifies cognitive control processes like response inhibition in persons with Parkinson's disease. In this study, we examined how the location of the stimulation volume within the subthalamic nucleus affects the performance in an antisaccade task but also how its structural connectivity is related to response inhibition. Antisaccade error rates and latencies were collected in 14 participants on and off deep brain stimulation in a randomized order. Stimulation volumes were computed based on patient-specific lead localizations using preoperative MRI and postoperative CT scans. Structural connectivity of the stimulation volumes with pre-defined cortical oculomotor control regions as well as whole-brain connectivity was estimated using a normative connectome. We showed that the detrimental effect of deep brain stimulation on response inhibition, measured as antisaccade error rate, depended upon the magnitude of the intersection of volumes of activated tissue with the non-motor subregion of the subthalamic nucleus and on its structural connectivity with regions of the prefrontal oculomotor network including bilateral frontal eye fields and right anterior cingulate cortex. Our results corroborate previous recommendations for avoidance of stimulation in the ventromedial non-motor subregion of the subthalamic nucleus which connects to the prefrontal cortex to prevent stimulation-induced impulsivity. Furthermore, antisaccades were initiated faster with deep brain stimulation when the stimulation volume was connected to fibres passing the subthalamic nucleus laterally and projecting onto the prefrontal cortex, indicating that improvement of voluntary saccade generation with deep brain stimulation may be an off-target effect driven by stimulation of corticotectal fibres directly projecting from the frontal and supplementary eye fields onto brainstem gaze control areas. Taken together, these findings could help implement individualized circuit-based deep brain stimulation strategies that avoid impulsive side effects while improving voluntary oculomotor control.

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

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

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

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

Interrater reliability of deep brain stimulation electrode localizations

Lead-DBS is an open-source, semi-automatized and widely applied software tool facilitating precise localization of deep brain stimulation electrodes both in native as well as in standardized stereotactic space. While automatized preprocessing steps within the toolbox have been tested and validated in previous studies, the interrater reliability in manual refinements of electrode localizations using the tool has not been objectified so far. Here, we investigate the variance introduced in this processing step by different raters when localizing electrodes based on postoperative CT or MRI. Furthermore, we compare the performance of novel trainees that received a structured training and more experienced raters with an expert user. We show that all users yield similar results with an average difference in localizations ranging between 0.52-0.75 mm with 0.07-0.12 mm increases in variability when using postoperative MRI and following normalization to standard space. Our findings may pave the way toward formal training for using Lead-DBS and demonstrate its reliability and ease-of-use for imaging research in the field of deep brain stimulation.

Machine Learning Approaches to Classify Anatomical Regions in Rodent Brain from High Density Recordings

Identifying different functional regions during a brain surgery is a challenging task usually performed by highly specialized neurophysiologists. Progress in this field may be used to improve in situ brain navigation and will serve as an important building block to minimize the number of animals in preclinical brain research required by properly positioning implants intraoperatively. The study at hand aims to correlate recorded extracellular signals with the volume of origin by deep learning methods. Our work establishes connections between the position in the brain and recorded high-density neural signals. This was achieved by evaluating the performance of BLSTM, BGRU, QRNN and CNN neural network architectures on multisite electrophysiological data sets. All networks were able to successfully distinguish cortical and thalamic brain regions according to their respective neural signals. The BGRU provides the best results with an accuracy of 88.6 % and demonstrates that this classification task might be solved in higher detail while minimizing complex preprocessing steps.

Low-frequency oscillations link frontal and parietal cortex with subthalamic nucleus in conflicts

Low-frequency oscillations (LFOs, 28 Hz) in the subthalamic nucleus(STN) are known to reflect cognitive conflict. However, it is unclear if LFOs mediate communication and functional interactions among regions implicated in conflict processing, such as the motor cortex (M1), premotor cortex (PMC), and superior parietal lobule (SPL). To investigate the potential contribution of LFOs to cognitive conflict mediation, we recorded M1, PMC, and SPL activities by right subdural electrocorticography (ECoG) simultaneously with bilateral STN local field potentials (LFPs) by deep brain stimulation electrodes in 13 patients with Parkinson's disease who performed the arrow version of the Eriksen flanker task. Elevated cue-related LFO activity was observed across patients during task trials, with the earliest onset in PMC and SPL. At cue onset, LFO power exhibited a significantly greater increase or a trend of a greater increase in the PMC, M1, and STN, and less increase in the SPL during high-conflict (incongruent) trials than in low-conflict (congruent) trials. The local LFO power increases in PMC, SPL, and right STN were correlated with response time, supporting the notion that these structures are critical hubs for cognitive conflict processing. This power increase was accompanied by increased functional connectivity between the PMC and right STN, which was correlated with response time across subjects. Finally, ipsilateral PMC-STN Granger causality was enhanced during high-conflict trials, with direction from STN to PMC. Our study indicates that LFOs link the frontal and parietal cortex with STN during conflicts, and the ipsilateral PMC-STN connection is specifically involved in this cognitive conflict processing.