Effective Deep Brain Stimulation Research Articles

Role of electrophysiological activity and interactions of lateral habenula in the development of depression-like behavior in a chronic restraint stress model

Closed-loop deep brain stimulation (DBS) system offers a promising approach for treatment-resistant depression, but identifying universally accepted electrophysiological biomarkers for closed-loop DBS systems targeting depression is challenging. There is growing evidence suggesting a strong association between the lateral habenula (LHb) and depression. Here, we took LHb as a key target, utilizing multi-site local field potentials (LFPs) to study the acute and chronic changes in electrophysiology, functional connectivity, and brain network characteristics during the formation of a chronic restraint stress (CRS) model. Furthermore, our model combining the electrophysiological changes of LHb and interactions between LHb and other potential targets of depression can effectively distinguish depressive states, offering a new way for developing effective closed-loop DBS strategies.

Cortical signatures of sleep are altered following effective deep brain stimulation for depression

Deep brain stimulation (DBS) of the subcallosal cingulate cortex (SCC) is an experimental therapy for treatment-resistant depression (TRD). Chronic SCC DBS leads to long-term changes in the electrophysiological dynamics measured from local field potential (LFP) during wakefulness, but it is unclear how it impacts sleep-related brain activity. This is a crucial gap in knowledge, given the link between depression and sleep disturbances, and an emerging interest in the interaction between DBS, sleep, and circadian rhythms. We therefore sought to characterize changes in electrophysiological markers of sleep associated with DBS treatment for depression. We analyzed key electrophysiological signatures of sleep—slow-wave activity (SWA, 0.5–4.5 Hz) and sleep spindles—in LFPs recorded from the SCC of 9 patients who responded to DBS for TRD. This allowed us to compare the electrophysiological changes before and after 24 weeks of therapeutically effective SCC DBS. SWA power was highly correlated between hemispheres, consistent with a global sleep state. Furthermore, SWA occurred earlier in the night after chronic DBS and had a more prominent peak. While we found no evidence for changes to slow-wave power or stability, we found an increase in the density of sleep spindles. Our results represent a first-of-its-kind report on long-term electrophysiological markers of sleep recorded from the SCC in patients with TRD, and provides evidence of earlier NREM sleep and increased sleep spindle activity following clinically effective DBS treatment. Future work is needed to establish the causal relationship between long-term DBS and the neural mechanisms underlying sleep.

Optimization of Patient Specific Stimulus for Deep Brain Stimulation Using Spatially Distributed Neural Sources

Deep brain stimulation (DBS) becomes the therapy of choice in the later stages of Parkinson's disease (PD) due to the medication's side effects. For effective DBS treatment, it is important to have a controlled dosage of DBS. DBS dosage is administered using the tuning of electrical parameters of the stimulus signal. Since this tuning process is tedious, time-consuming and patient-specific, there is a need to study the properties of DBS stimulation signal for proper dose administration. We propose a simulation framework to define an optimized DBS stimulus using Electroencephalogram (EEG) signals. The objective is to provide a simulation environment inspired by a realistic brain. The framework uses spiking neurons in a reservoir modelled after real brain anatomy and is trained using a biologically inspired spike-time-dependent-plasticity learning algorithm. This reservoir is initially set to OFF-medication state and forced to drift to the ON-medication state by optimizing the synaptic changes. In later testing, the generalization of this framework is verified with EEG-inverse solutions like sLORETA which utilize time-domain EEG signals to estimate neural activations. The stimulus signal is generated by accumulating the variations in synaptic weights in the neural reservoir in the target brain region. We analyze this signal and show that the application of this signal as stimulus results in decreased <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\beta$</tex-math></inline-formula> -band power in subthalamic-nucleus local-field-potential compared to OFF-medication local-field-potential without stimulation. Using SIM4LIFE simulation software, we show that the simulation increases chaos in the local-field-potential of subthalamic-nucleus neurons and shows that neuron weight variations follow specific trajectories in reconstructed state-space. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Impact Statement:</i> The primary contribution of this paper is to present a framework that utilizes the association between target signals of any modality (EEG, MEG, fMRI) and their respective post-synaptic activations to optimize the deep brain stimulation (DBS) stimulus signal. This framework combines coordinates of neural sources with patients' EEG data to optimize the stimulus of DBS. While defining this framework, we initially proposed the usage of spiking neurons in a biological neural reservoir to estimate the internal activations for given EEG data. Later, we extended our testing to incorporate inverse EEG algorithms that estimate neural activations directly from EEG data without any conversion. This is a novel framework, and there are not many examples available in the literature for similar work. This framework is in its early stages, yet it provides an adequate starting point for an under-explored area of study. This framework can potentially evolve into a useful tool for doctors in assisting the DBS tuning process before the surgical procedure. This framework's accuracy depends on the underlying technique to estimate the neural activations from the target signals (like EEG etc.).

Current Study on Deep Brain Stimulation for Parkinson's Disease

This paper emphasizes the evolution and application of neural electrical stimulation in the context of Parkinson's disease. During the last several decades, Deep Brain Stimulation (DBS) has become a highly successful viable treatment choice for patients with advanced stages of PD and other motor disorders. DBS utilizes a device similar to a pacemaker to administer constant electrical signals to targeted regions within the brain to help patient relieve the symptoms. The DBS has been involved in the rehabilitation process of more than 80000 people, and most of them are patients with PD. Based on the specific symptoms show by patients, several targets have been approved as effective DBS targets for patients with PD. These include subthalamic nucleus (STN), globus pallidus internus (GPi), ventral intermediate nucleus (Vim), and pedunculopontine nucleus (PPN). Hence, understanding the applications and evolution of DBS techniques have significant importance for future studies of PD and brain functions.

Deep brain stimulation for Tourette syndrome: modulation of the limbic-motor interface network.

Deep brain stimulation (DBS) is an effective treatment for medically refractory Tourette syndrome (TS). Several effective targets have been reported, but there is still controversy about the networks involved in the efficacy of DBS for TS. Here, the authors aimed to identify the basal ganglia-thalamo-cortical networks associated with tic and obsessive-compulsive behavior (OCB) improvement and the network link between the two main targets for TS. A retrospective analysis of 21 patients treated with pallidal and thalamic DBS was performed. Tics and OCB scores were recorded before and after DBS. The authors localized the electrodes in standard MNI (Montreal Neurological Institute) space and calculated the volume of tissue activated with the settings at the last follow-up to obtain areas of maximal improvement ("sweet spots") among all patients for the pallidal and thalamic targets. Tractography was used to show the white matter pathways associated with maximal tic and OCB improvement. Ten patients treated with pallidal DBS and 11 patients treated with thalamic DBS were included. Responder rates were 80% in the pallidal and 64% in the thalamic target groups. Sweet spots for tics and OCB clustered in several areas across the basal ganglia and thalamus delineated two main networks. Tic reduction in the pallidal target mapped to a limbic pallidothalamic network and in the thalamic target to the premotor thalamocortical network. Putting these two networks together will form the main output of the so-called limbic-motor interface network. However, OCB reduction mapped a dorsomedial prefrontal cortex/dorsal anterior cingulate (dmPFC/dACC) network. The authors demonstrated the involvement of the limbic-motor interface network during effective DBS for tics in patients with TS. OCB redution was associated with the additional involvement of dmPFC/dACC connections passing dorsal to the head of the globus pallidus pars externa on its way to the thalamus and midbrain.

Effective DBS treatment improves neural information transmission of patients with disorders of consciousness: an fNIRS study

Objective. Deep brain stimulation (DBS) is a potential treatment that promotes the recovery of patients with disorders of consciousness (DOC). This study quantified the changes in consciousness and the neuromodulation effect of DBS on patients with DOC. Approach. Eleven patients were recruited for this study which consists of three conditions: ‘Pre’ (two days before DBS surgery), ‘Post-On’ (one month after surgery with stimulation), and ‘Post-Off’ (one month after surgery without stimulation). Functional near-infrared spectroscopy (fNIRS) was recorded from the frontal lobe, parietal lobe, and occipital lobe of patients during the experiment of auditory stimuli paradigm, in parallel with the coma recovery scale-revised (CRS-R) assessment. The brain hemodynamic states were defined and state transition acceleration was taken to quantify the information transmission strength of the brain network. Linear regression analysis was conducted between the changes in regional and global indicators and the changes in the CRS-R index. Main results. Significant correlation was observed between the changes in the global transition acceleration indicator and the changes in the CRS-R index (slope = 55.910, p < 0.001, R 2 = 0.732). For the regional indicators, similar correlations were found between the changes in the frontal lobe and parietal lobe indicators and the changes in the CRS-R index (slope = 46.612, p < 0.01, R 2 = 0.694; slope = 47.491, p < 0.01, R 2 = 0.676). Significance. Our study suggests that fNIRS-based brain hemodynamics transition analysis can signify the neuromodulation effect of DBS treatment on patients with DOC, and the transition acceleration indicator is a promising brain functional marker for DOC.

Dysconnectivity of the parafascicular nucleus in Parkinson's disease: A dynamic causal modeling analysis

BackgroundRecent animal model studies have suggested that the parafascicular nucleus has the potential to be an effective deep brain stimulation target for Parkinson's disease. However, our knowledge on the role of the parafascicular nucleus in Parkinson's disease patients remains limited. ObjectiveWe aimed to investigate the functional alterations of the parafascicular nucleus projections in Parkinson's disease patients. MethodsWe enrolled 72 Parkinson's disease patients and 60 healthy controls, then utilized resting-state functional MRI and spectral dynamic causal modeling to explore the effective connectivity of the bilateral parafascicular nucleus to the dorsal putamen, nucleus accumbens, and subthalamic nucleus. The associations between the effective connectivity of the parafascicular nucleus projections and clinical features were measured with Pearson partial correlations. ResultsCompared with controls, the effective connectivity from the parafascicular nucleus to dorsal putamen was significantly increased, while the connectivity to the nucleus accumbens and subthalamic nucleus was significantly reduced in Parkinson's disease patients. There was a significantly positive correlation between the connectivity of parafascicular nucleus-dorsal putamen projection and motor deficits. The connectivity from the parafascicular nucleus to the subthalamic nucleus was negatively correlated with motor deficits and apathy, while the connectivity from the parafascicular nucleus to the nucleus accumbens was negatively associated with depression. ConclusionThe present study demonstrates that the parafascicular nucleus-related projections are damaged and associated with clinical symptoms of Parkinson's disease. Our findings provide new insights into the impaired basal ganglia-thalamocortical circuits and give support for the parafascicular nucleus as a potential effective neuromodulating target of the disease.

Clinical practice guidelines on the use of deep brain stimulation for the treatment of obsessive-compulsive disorder: systematic review.

Deep brain stimulation (DBS) has been proposed to improve symptoms of obsessive-compulsive disorder (OCD) but is not yet an established therapy. To identify relevant guidelines and assess their recommendations for the use of DBS in OCD. Medline, Embase, American Psychiatric Association PsycInfo and Scopus were searched, as were websites of relevant societies and guideline development organisations. The review was based on the PRISMA recommendations, and the search strategy was verified by a medical librarian. The protocol was developed and registered with PROSPERO (CRD42022353715). The guidelines were assessed for quality using the AGREE II instrument. Nine guidelines were identified. Three guidelines scored >80% on AGREE II. 'Scope and Purpose' and 'Editorial Independence' were the highest scoring domains, but 'Applicability' scores were low. Eight guidelines recommended that DBS is used after all other treatment options have failed to alleviate OCD symptoms. One guideline did not recommend DBS beyond a research setting. Only one guideline performed a cost-effectiveness analysis; the other eight did not provide details on safe or effective DBS protocols. Despite a very limited evidence base, eight of the nine identified guidelines supported the use of DBS for OCD as a last line of therapy; however, multiple aspects of DBS provision were not addressed.

Hypotensive Effect of Electric Stimulation of Caudal Ventrolateral Medulla in Freely Moving Rats.

Background and Objectives: An altered sympathetic function is established in primary arterial hypertension (PAH) development. Therefore, PAH could be targeted by applying an electric current to the medulla where reflex centers for blood pressure control reside. This study aims to evaluate the electric caudal ventrolateral medulla (CVLM) stimulation effect on blood pressure and animal survivability in a freely moving rat model. Materials and Methods: A total of 20 Wistar rats aged 12-16 weeks were randomly assigned to either: the experimental group (n = 10; electrode tip implanted in CVLM region) or the control group (n = 10; tip implanted 4 mm above the CVLM in the cerebellum). After a period of recovery (4 days), an experimental phase ensued, divided into an "OFF stimulation" period (5-7 days post-surgery) and an "ON stimulation" period (8-14 days post-surgery). Results: Three animals (15%, one in the control, two in the experimental group) dropped out due to postoperative complications. Arterial pressure in the experimental group rats during the "OFF stimulation" period decreased by 8.23 mm Hg (p = 0.001) and heart rate by 26.93 beats/min (p = 0.008). Conclusions: From a physiological perspective, CVLM could be an effective deep brain stimulation (DBS) target for drug-resistant hypertension: able to influence the baroreflex arc directly, having no known direct integrative or neuroendocrine function. Targeting the baroreflex regulatory center, but not its sensory or effector parts, could lead to a more predictable effect and stability of the control system. Although targeting neural centers in the medullary region is considered dangerous and prone to complications, it could open a new vista for deep brain stimulation therapy. A possible change in electrode design would be required to apply CVLM DBS in clinical trials in the future.

On-Off and Proportional Closed-Loop Adaptive Deep Brain Stimulation Reduces Motor Symptoms in Freely Moving Hemiparkinsonian Rats

ObjectivesClosed-loop adaptive deep brain stimulation (aDBS) continuously adjusts stimulation parameters, with the potential to improve efficacy and reduce side effects of deep brain stimulation (DBS) for Parkinson’s disease (PD). Rodent models can provide an effective platform for testing aDBS algorithms and establishing efficacy before clinical investigation. In this study, we compare two aDBS algorithms, on-off and proportional modulation of DBS amplitude, with conventional DBS in hemiparkinsonian rats. Materials and MethodsDBS of the subthalamic nucleus (STN) was delivered wirelessly in freely moving male and female hemiparkinsonian (N = 7) and sham (N = 3) Wistar rats. On-off and proportional aDBS, based on STN local field potential beta power, were compared with conventional DBS and three control stimulation algorithms. Behavior was assessed during cylinder tests (CT) and stepping tests (ST). Successful model creation was confirmed via apomorphine-induced rotation test and Tyrosine Hydroxylase–immunocytochemistry. Electrode location was histologically confirmed. Data were analyzed using linear mixed models. ResultsContralateral paw use in parkinsonian rats was reduced to 20% and 25% in CT and ST, respectively. Conventional, on-off, and proportional aDBS significantly improved motor function, restoring contralateral paw use to approximately 45% in both tests. No improvement in motor behavior was observed with either randomly applied on-off or low-amplitude continuous stimulation. Relative STN beta power was suppressed during DBS. Relative power in the alpha and gamma bands decreased and increased, respectively. Therapeutically effective adaptive DBS used approximately 40% less energy than did conventional DBS. ConclusionsAdaptive DBS, using both on-off and proportional control schemes, is as effective as conventional DBS in reducing motor symptoms of PD in parkinsonian rats. Both aDBS algorithms yield substantial reductions in stimulation power. These findings support using hemiparkinsonian rats as a viable model for testing aDBS based on beta power and provide a path to investigate more complex closed-loop algorithms in freely behaving animals.

In silico development and validation of Bayesian methods for optimizing deep brain stimulation to enhance cognitive control

Objective. deep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement. Approach. we leverage prior results showing that effective VCVS DBS engages cognitive control circuitry and improves performance on the multi-source interference task, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We develop a simulation framework based on those empirical results, then combine this framework with an adaptive optimizer to simulate a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control. We explore multiple optimization options (algorithms, number of inputs, speed of stimulation parameter changes) and compare them on problems of varying difficulty. Main results. we show that an upper confidence bound algorithm outperforms other optimizers, with roughly 80% probability of convergence to a global optimum when used in a majority-vote ensemble. Significance. we show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.

Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method.

The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.

Effect of Enlarged Perivascular Spaces in Reliable Distinction of Prospective Targeting During Deep Brain Stimulation in Patients With Advanced Parkinson's Disease: A Study of Deterministic and Probabilistic Tractography.

Precise electrode position is vital for effective deep brain stimulation in treating motor symptoms in Parkinson's disease (PD). Enlarged perivascular spaces (PVSs) are associated with pathophysiology of neurodegenerative diseases including PD and may affect the microstructure of surrounding brain tissue. To quantify the clinical implications of enlarged PVS on tractography-based stereotactic targeting in patients with advanced PD selected to undergo deep brain stimulation. Twenty patients with PD underwent MRI scanning. The PVS areas were visualized and segmented. Based on the size of the PVS areas, the patient group was split into 2 categories of large vs small PVSs. Probabilistic and deterministic tractography methods were applied to a diffusion-weighted data set. Fiber assignment was performed using motor cortex as an initiation seed and the globus pallidus interna and subthalamic nucleus, separately, as inclusion masks. Two exclusion masks used consisted of cerebral peduncles and the PVS mask. The center of gravity of the tract density map was measured and compared between the tracts generated with and without consideration of the PVS mask. The average differences between the center of gravity of the tracts made by excluding PVS and without excluding PVS using deterministic and probabilistic tractography methods were less than 1 mm. Statistical analysis showed nonsignificant differences between deterministic and probabilistic methods and differences between patients with large and small PVSs ( P > .05). This study demonstrated that the presence of enlarged PVS is unlikely to affect targeting of basal ganglia nuclei based on tractography.

Abnormal neural oscillations during gait and dual-task in Parkinson's disease.

Gait dysfunctions are debilitating motor symptoms of Parkinson’s disease (PD) and may result in frequent falling with health complications. The contribution of the motor-cognitive network to gait disturbance can be studied more thoroughly by challenging motor-cognitive dual-task gait performances. Gait is a complex motor task that requires an appropriate contribution from motor and cognitive networks, reflected in frequency modulations among several cortical and subcortical networks. Electrophysiological recordings by scalp electroencephalography and implanted deep brain stimulation (DBS) electrodes have unveiled modulations of specific oscillatory patterns in the cortical-subcortical circuits in PD. In this review, we summarize oscillatory contributions of the cortical, basal ganglia, mesencephalic locomotor, and cerebellar regions during gait and dual-task activities in PD. We detail the involvement of the cognitive network in dual-task settings and compare how abnormal oscillations in the specific frequency bands in the cortical and subcortical regions correlate with gait deficits in PD, particularly freezing of gait (FOG). We suggest that altered neural oscillations in different frequencies can cause derangements in broader brain networks, so neuromodulation and pharmacological therapies should be considered to normalize those network oscillations to improve challenged gait and dual-task motor functions in PD. Specifically, the theta and beta bands in premotor cortical areas, subthalamic nucleus, as well as alpha band activity in the brainstem prepontine nucleus, modulate under clinically effective levodopa and DBS therapies, improving gait and dual-task performance in PD with FOG, compared to PD without FOG and age-matched healthy control groups.

A comparison of an implanted accelerometer with a wearable accelerometer for closed-loop DBS.

Sensing technology, as well as cloud communication, is enabling the development of closed-loop deep brain stimulation (DBS) for Parkinson's disease. The accelerometer is a practical sensor that can provide information about the disease/health state of the patient as well as physical activity levels, all of which in the long-term can provide feedback information to an adaptive closed-loop control algorithm for more effective and personalized DBS therapy. In this paper, we present for the first time, acceleration streamed from Medtronic's RC+S device in patients with Parkinson's disease while at home, and compare it to accel-eration acquired concurrently from the patient's Apple Watch. We examined correlation between the accelerometer signals at varying time scales. We also compared the spectral band power obtained from the two accelerometers. While there was an average correlation of 0.37 for subject 1 and 0.50 for subject 2 between the two acceleration signals on a time scale of 10 minutes, the correlation was lower for shorter time scales on the order of seconds. There was greater spectral power in the Parkinsonian tremor band of 4-7 Hz for the externally worn accelerometer than the internal accelerometer, but the internal accelerometer showed greater relative power distributed in the higher frequencies (7-30 Hz). Thus, based on this preliminary analysis, we expect that the internal accelerometer may be used to assess patient activity and state for closed loop DBS but tremor detection may require more sophisticated signal processing. Furthermore, the internal accelerometer may contain information in higher frequency bands that reveal information about the patient state. Clinical relevance - Closed-loop DBS is expected to improve patient outcomes for the tens of thousands of Parkinson's disease patients using DBS [1], [2]. Eliminating an additional external device in order to implement closed-loop adaptive deep brain stimulation would benefit DBS patients however an understanding of what information is lost by doing so is needed to justify the ultimate design of closed-loop DBS.

Subthalamic Oscillatory Activity of Reward and Loss Processing Using the Monetary Incentive Delay Task in Parkinson Disease

BackgroundThe subthalamic nucleus (STN) is an effective deep brain stimulation target for Parkinson disease (PD) and obsessive-compulsive disorder and has been implicated in reward and motivational processing. In this study, we assessed the STN and prefrontal oscillatory dynamics in the anticipation and receipt of reward and loss using a task commonly used in imaging. Materials and MethodsWe recorded intracranial left subthalamic local field potentials from deep brain stimulation electrodes and prefrontal scalp electroencephalography in 17 patients with PD while they performed a monetary incentive delay task. ResultsDuring the expectation phase, enhanced left STN delta-theta activity was observed in both reward and loss vs neutral anticipation, with greater STN delta-theta activity associated with greater motivation specifically to reward. In the consummatory outcome phase, greater left STN delta activity was associated with a rewarding vs neutral outcome, particularly with more ventral contacts along with greater delta-theta coherence with the prefrontal cortex. We highlight a differential activity in the left STN to loss vs reward anticipation, demonstrating a distinct STN high gamma activity. Patients with addiction-like behaviors show lower left STN delta-theta activity to loss vs neutral outcomes, emphasizing impaired sensitivity to negative outcomes. ConclusionsTogether, our findings highlight a role for the left STN in reward and loss processing and a potential role in addictive behaviors. These findings emphasize the cognitive-limbic function of the STN and its role as a physiologic target for neuropsychiatric disorders.

Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation.

Accurate electrode placement is key to effective deep brain stimulation (DBS). The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for the treatment of essential tremor (ET). Retrospective tractography-based analysis of electrode placement has associated successful outcomes with modulation of motor input to VIM, but no study has yet evaluated the feasibility and efficacy of prospective presurgical tractography-based targeting alone. Therefore, the authors sought to demonstrate the safety and efficacy of probabilistic tractography-based VIM targeting in ET patients and to perform a systematic comparison of probabilistic and deterministic tractography. Fourteen patients with ET underwent preoperative diffusion imaging. Probabilistic tractography was applied for preoperative targeting, and deterministic tractography was performed as a comparison between methods. Tractography was performed using the motor and sensory areas as initiation seeds, the ipsilateral thalamus as an inclusion mask, and the contralateral dentate nucleus as a termination mask. Tract-density maps consisted of voxels with 10% or less of the maximum intensity and were superimposed onto anatomical images for presurgical planning. Target planning was based on probabilistic tract-density images and indirect target coordinates. Patients underwent robotic image-guided, image-verified implantation of directional DBS systems. Postoperative tremor scores with and without DBS were recorded. The center of gravity and Dice similarity coefficients were calculated and compared between tracking methods. Prospective probabilistic targeting of VIM was successful in all 14 patients. All patients experienced significant tremor reduction. Formal postoperative tremor scores were available for 9 patients, who demonstrated a mean 68.0% tremor reduction. Large differences between tracking methods were observed across patients. Probabilistic tractography-identified VIM fibers were more anterior, lateral, and superior than deterministic tractography-identified fibers, whereas probabilistic tractography-identified ventralis caudalis fibers were more posterior, lateral, and superior than deterministic tractography-identified fibers. Deterministic methods were unable to clearly distinguish between motor and sensory fibers in the majority of patients, but probabilistic methods produced distinct separation. Probabilistic tractography-based VIM targeting is safe and effective for the treatment of ET. Probabilistic tractography is more precise than deterministic tractography for the delineation of VIM and the ventralis caudalis nucleus of the thalamus. Deterministic algorithms tended to underestimate separation between motor and sensory fibers, which may have been due to its limitations with crossing fibers. Larger studies across multiple centers are necessary to further validate this method.

P 35 Local Field Potential Guided Determination of Effective Deep Brain Stimulation Contacts from an Implantable Pulse Generator – A Pilot Study

Question : Local field potential (LFP) activity in the beta band (13-35 Hz) has been suggested as a biomarker for motor symptoms in Parkinson’s disease (PD). Up to date, intraoperative recordings remain the only predictor of clinically effective deep brain stimulation (DBS) contacts. With the introduction of novel systems, however, LFP activity can be recorded from chronically implanted DBS leads. Consecutively, we aim to investigate how postoperative LFP recordings can be used as a reliable predictor for clinically effective stimulation contacts. Methods : Here, we present LFP recordings from an ongoing analysis. A sample of 6 PD patients (11 hemispheres) was recorded in the nucleus subthalamicus. 5 patients received newly implanted directional DBS leads for the treatment of PD (9 hemispheres), whereas 1 patient (2 hemispheres) underwent pulse generator exchange on chronically implanted non–directional DBS leads. All recordings were obtained while the patient being at rest. LFPs were recorded in a bipolar fashion from all possible contact configurations and then assigned to the respective single contacts using a weighted average. Normalised power around beta peak activity (±2 Hz) of each contact was correlated to its clinical stimulation results determined during a standardised monopolar review performed 3 months postoperatively. If no clear visual beta peak was present, total power in the low beta band (13-20 Hz) was used. Results : Preliminary results from newly implanted patients (n = 5) indicate that clinically determined effective contacts correspond to those contacts that exhibit the highest ß-activity in (5/9) hemispheres investigated. Strikingly, recordings that revealed a clear visual beta peak were the most reliable predictor of DBS outcome (2/5 hemispheres), while total power in the low beta band resulted in poorer prediction of effective stimulation contacts (3/5 hemispheres). Finally, recordings from 1 patient (2 hemispheres) that underwent IPG exchange revealed poor recording quality in terms of signal-to-noise ratio and predictive power of effective stimulation contacts. Conclusion : Our preliminary results indicate that postoperative bipolar recordings from chronically implanted electrodes provide a useful tool to guide selection of effective simulation contacts. In the future, this approach may be useful for clinical decision-making and offers determination of effective stimulation contacts without time-consuming and burdensome systematic stimulation testing.

Metabolic Imaging of Deep Brain Stimulation in Meige Syndrome.

ObjectivesThe subthalamic nucleus (STN) has been shown to be a safe and effective deep brain stimulation (DBS) surgical target for the treatment of Meige syndrome. The aim of this study was to compare changes in brain metabolism before and 6 months after STN-DBS surgery.MethodsTwenty-five patients with primary Meige syndrome underwent motor function assessment, including the Burke–Fahn–Marsden Dystonia Rating Scale movement (BFMDRS-M) and disability subscale (BFMDRS-D) and positron emission tomography with an 18[F]-fluorodeoxyglucose scan before and 6 months after STN-DBS surgery. For the voxelwise metabolic change assessment, the p-value was controlled for multiple comparisons using the familywise error rate.ResultsThere was a significant decrease in BFMDRS-M scores 6 months after STN-DBS, from 10.02 ± 3.99 to 4.00 ± 2.69 (p < 0.001). The BFMDRS-D scores also decreased significantly from 4.52 ± 2.90 to 0.64 ± 1.29 (p < 0.001). In the left hemisphere, hypermetabolism was found in the occipital lobe, superior parietal gyrus, postcentral gyrus and thalamus. In the right hemisphere, hypermetabolism was found in the lentiform nucleus, precuneus and precentral gyrus in patients with Meige syndrome receiving DBS. In addition, the bilateral inferior temporal gyrus and middle frontal gyrus exhibited glucose hypermetabolism.ConclusionOur findings indicate that STN-DBS has a significant effect on metabolic level in the brain, which may be an important mechanism for the treatment of Meige syndrome using STN-DBS.

The Intraoperative Microlesion Effect Positively Correlates With the Short-Term Clinical Effect of Deep Brain Stimulation in Parkinson's Disease

ObjectiveDuring the surgical procedure of deep brain stimulation (DBS), insertion of an electrode in the subthalamic nucleus (STN) frequently causes a temporary improvement of motor symptoms, known as the microlesion effect (MLE). The objective of this study was to determine the correlation between the intraoperative MLE and the clinical effect of DBS. Materials and MethodsThirty Parkinson's disease (PD) patients with Movement Disorder Society (MDS) Unified Parkinson's Disease Rating Scale (UPDRS) part III (MDS-UPDRS III) scores during bilateral STN-DBS implantation were included in this retrospective study. MDS-UPDRS III subscores (resting tremor, rigidity, and bradykinesia) of the contralateral upper extremity were used. During surgery, these subscores were assessed directly before and after insertion of the electrode. Also, these subscores were determined in the outpatient clinic after 11 weeks on average (on-stimulation). All assessments were performed in an off-medication state (at least 12 hours of medication washout). ResultsPostinsertion MDS-UPDRS motor scores decreased significantly compared to preinsertion scores (p < 0.001 for both hemispheres). The MLE showed a positive correlation with the clinical effect of DBS in both hemispheres (rho = 0.68 for the primarily treated hemisphere, p < 0.001, and rho = 0.59 for the secondarily treated hemisphere, p < 0.01). ConclusionThe MLE has a clinically relevant correlation with the effect of DBS in PD patients. These results suggest that the MLE can be relied upon as evidence of a clinically effective DBS electrode placement.