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Parkinson disease (PD) is associated with α-synuclein (αS) aggregation within enteric neurons. ENT-01 inhibits the formation of αS aggregates and improved constipation in an open-label study in patients with PD.To evaluate the safety and efficacy of oral ENT-01 for constipation and neurologic symptoms in patients with PD and constipation.Randomized, placebo-controlled phase 2b study. (ClinicalTrials.gov: NCT03781791).Outpatient.150 patients with PD and constipation.ENT-01 or placebo daily for up to 25 days. After baseline assessment of constipation severity, daily dosing was escalated to the prokinetic dose, the maximum dose (250 mg), or the tolerability limit, followed by a washout period.The primary efficacy end point was the number of complete spontaneous bowel movements (CSBMs) per week. Neurologic end points included dementia (assessed using the Mini-Mental State Examination [MMSE]) and psychosis (assessed using the Scale for the Assessment of Positive Symptoms adapted for PD [SAPS-PD]).The weekly CSBM rate increased from 0.7 to 3.2 in the ENT-01 group versus 0.7 to 1.2 in the placebo group (Longer treatment periods need to be investigated in future studies.ENT-01 was safe and significantly improved constipation.Enterin, Inc.

OBJECTIVE To assess use of directional stimulation in Parkinson's disease and essential tremor patients programmed in routine clinical care. MATERIALS AND METHODS Patients with Parkinson's disease or essential tremor implanted at Cleveland Clinic with a directional deep brain stimulation (DBS) system from November 2017 to October 2019 were included in this retrospective case series. Omnidirectional was compared against directional stimulation using therapeutic current strength, therapeutic window percentage, and total electrical energy delivered as outcome variables. RESULTS Fifty-seven Parkinson's disease patients (36 males) were implanted in the subthalamic nucleus (105 leads) and 33 essential tremor patients (19 males) were implanted in the ventral intermediate nucleus of the thalamus (52 leads). Seventy-four percent of patients with subthalamic stimulation (65% of leads) and 79% of patients with thalamic stimulation (79% of leads) were programmed with directional stimulation for their stable settings. Forty-six percent of subthalamic leads and 69% of thalamic leads were programmed on single segment activation. There was no correlation between the length of microelectrode trajectory through the STN and use of directional stimulation. CONCLUSIONS Directional programming was more common than omnidirectional programming. Substantial gains in therapeutic current strength, therapeutic window, and total electrical energy were found in subthalamic and thalamic leads programmed on directional stimulation.

Background The initial COVID-19 pandemic shutdown led to the canceling of elective surgeries throughout most of the USA and Canada. Objective This survey was carried out on behalf of the Parkinson Study Group (PSG) to understand the impact of the shutdown on deep brain stimulation (DBS) practices in North America. Methods A survey was distributed through RedCap® to the members of the PSG Functional Neurosurgical Working Group. Only one member from each site was asked to respond to the survey. Responses were collected from May 15 to June 6, 2020. Results Twenty-three sites participated; 19 (83%) sites were from the USA and 4 (17%) from Canada. Twenty-one sites were academic medical centers. COVID-19 associated DBS restrictions were in place from 4 to 16 weeks. One-third of sites halted preoperative evaluations, while two-thirds of the sites offered limited preoperative evaluations. Institutional policy was the main contributor for the reported practice changes, with 87% of the sites additionally reporting patient-driven surgical delays secondary to pandemic concerns. Pre-post DBS associated management changes affected preoperative assessments 96%; electrode placement 87%; new implantable pulse generator (IPG) placement 83%; IPG replacement 65%; immediate postoperative DBS programming 74%; and routine DBS programming 91%. Conclusion The COVID-19 pandemic related shutdown resulted in DBS practice changes in almost all North American sites who responded to this large survey. Information learned could inform development of future contingency plans to reduce patient delays in care under similar circumstances.

Background Deep brain stimulation (DBS) was first approved by the United States Food and Drug Administration in 1997. Although the fundamentals of DBS remain the same, hardware, software, and imaging have evolved significantly. Objective To test our hypothesis that the aggregate complication rate in the medical literature in the past 12 years would be lower than what is often cited based on early experience with DBS surgery. Methods PubMed, PsycINFO, and EMBASE were queried for studies from 2008 to 2020 that included patients treated with DBS from 2007 to 2019. This yielded 34 articles that evaluated all complications of DBS surgery, totaling 2249 patients. Results The overall complication rate in this study was 16.7% per patient. There was found to be a systemic complication rate of 0.89%, intracranial complication rate of 2.7%, neurological complication rate of 4.6%, hardware complication rate of 2.2%, and surgical site complication rate of 3.4%. The infection and erosion rate was 3.0%. Conclusion This review suggests that surgical complication rates have decreased since the first decade after DBS was first FDA approved. Understanding how to minimize complications from the inception of a technique should receive more attention.

Augmented reality (AR) may be a useful tool for the delivery of dual-task training. This manuscript details the development of the Dual-task Augmented Reality Treatment (DART) platform for individuals with Parkinson’s disease (PD) and reports initial feasibility, usability, and efficacy of the DART platform in provoking dual-task interference in individuals with PD. The DART platform utilizes the head-mounted Microsoft HoloLens2 AR device to deliver concurrent motor and cognitive tasks. Biomechanical metrics of gait and cognitive responses are automatically computed and provided to the supervising clinician. To assess feasibility, individuals with PD (N = 48) completed a bout of single-task and dual-task walking using the DART platform. Usability was assessed by the System Usability Scale (SUS). Dual-task interference was assessed by comparing single-task walking and walking during an obstacle course while performing a cognitive task. Average gait velocity decreased from 1.06 to 0.82 m/s from single- to dual-task conditions. Mean SUS scores were 81.3 (11.3), which placed the DART in the “good” to “excellent” category. To our knowledge, the DART platform is the first to use a head-mounted AR system to deliver a dual-task paradigm and simultaneously provide biomechanical data that characterize cognitive and motor performance. Individuals with PD were able to successfully use the DART platform with satisfaction, and dual-task interference was provoked. The DART platform should be investigated as a platform to treat dual-task declines associated with PD.

Hybrid kinetic and kinematic intracortical brain-computer interfaces (iBCIs) have the potential to restore functional grasping and object interaction capabilities in individuals with tetraplegia. This requires an understanding of how kinetic information is represented in neural activity, and how this representation is affected by non-motor parameters such as volitional state (VoS), namely, whether one observes, imagines, or attempts an action. To this end, this work investigates how motor cortical neural activity changes when three human participants with tetraplegia observe, imagine, and attempt to produce three discrete hand grasping forces with the dominant hand. We show that force representation follows the same VoS-related trends as previously shown for directional arm movements; namely, that attempted force production recruits more neural activity compared to observed or imagined force production. Additionally, VoS-modulated neural activity to a greater extent than grasping force. Neural representation of forces was lower than expected, possibly due to compromised somatosensory pathways in individuals with tetraplegia, which have been shown to influence motor cortical activity. Nevertheless, attempted forces (but not always observed or imagined forces) could be decoded significantly above chance, thereby potentially providing relevant information towards the development of a hybrid kinetic and kinematic iBCI.

Neuromodulation, or the utilization of advanced technology for targeted electrical or chemical neuronal stimulation or inhibition, has been expanding in several neurological subspecialties. In the past decades, immune-modulating therapy has been the main focus of multiple sclerosis (MS) research with little attention to neuromodulation. However, with the recent advances in disease-modifying therapies, it is time to shift the focus of MS research to neuromodulation and restoration of function as with other neurological subspecialties. Preliminary research supports the value of intrathecal baclofen pump and functional electrical stimulation in improving spasticity and motor function in MS patients. Deep brain stimulation can improve MS-related tremor and trigeminal neuralgia. Spinal cord stimulation has been shown to be effective against MS-related pain and bladder dysfunction. Bladder overactivity also responds to sacral neuromodulation and posterior tibial nerve stimulation. Despite limited data in MS, transcranial magnetic stimulation and brain–computer interface are promising neuromodulatory techniques for symptom mitigation and neurorehabilitation of MS patients. In this review, we provide an overview of the available neuromodulatory techniques and the evidence for their use in MS.

Traditional hypotheses for the pathogenesis of dystonia, the third most common movement disorder, have focused primarily on the basal ganglia. Contemporary theories have emphasized the role of the cerebellum. The modulation of peripheral proprioception also affects dystonia. We proposed a unifying network model for dystonia where the cerebellum, basal ganglia, and peripheral proprioception are connected in a circuit that forms the neural integrator network, ensuring steady position. We suggested that impairment anywhere along this circuit leads to common phenomenology-slow drifts followed by corrective movements, resembling dystonic tremor. We tested this concept in a patient with chronic inflammatory demyelinating polyneuropathy with resulting abnormal proprioception. Quantitative assessment of tremor in this patient revealed drifts in limb position followed by corrective movements and superimposed sinusoidal oscillations-consistent with neural integrator dysfunction. This unique case of chronic inflammatory demyelinating polyneuropathy describes the role of proprioception on the unifying network model for dystonia.

Decoders optimized offline to reconstruct intended movements from neural recordings sometimes fail to achieve optimal performance online when they are used in closed-loop as part of an intracortical brain-computer interface (iBCI). This is because typical decoder calibration routines do not model the emergent interactions between the decoder, the user, and the task parameters (e.g. target size). Here, we investigated the feasibility of simulating online performance to better guide decoder parameter selection and design. Three participants in the BrainGate2 pilot clinical trial controlled a computer cursor using a linear velocity decoder under different gain (speed scaling) and temporal smoothing parameters and acquired targets with different radii and distances. We show that a user-specific iBCI feedback control model can predict how performance changes under these different decoder and task parameters in held-out data. We also used the model to optimize a nonlinear speed scaling function for the decoder. When used online with two participants, it increased the dynamic range of decoded speeds and decreased the time taken to acquire targets (compared to an optimized standard decoder). These results suggest that it is feasible to simulate iBCI performance accurately enough to be useful for quantitative decoder optimization and design.

Intracortical brain-computer interfaces (iBCIs) have the potential to restore hand grasping and object interaction to individuals with tetraplegia. Optimal grasping and object interaction require simultaneous production of both force and grasp outputs. However, since overlapping neural populations are modulated by both parameters, grasp type could affect how well forces are decoded from motor cortex in a closed-loop force iBCI. Therefore, this work quantified the neural representation and offline decoding performance of discrete hand grasps and force levels in two participants with tetraplegia. Participants attempted to produce three discrete forces (light, medium, hard) using up to five hand grasp configurations. A two-way Welch ANOVA was implemented on multiunit neural features to assess their modulation to force and grasp. Demixed principal component analysis was used to assess for population-level tuning to force and grasp and to predict these parameters from neural activity. Three major findings emerged from this work: 1) Force information was neurally represented and could be decoded across multiple hand grasps (and, in one participant, across attempted elbow extension as well); 2) Grasp type affected force representation within multi-unit neural features and offline force classification accuracy; and 3) Grasp was classified more accurately and had greater population-level representation than force. These findings suggest that force and grasp have both independent and interacting representations within cortex, and that incorporating force control into real-time iBCI systems is feasible across multiple hand grasps if the decoder also accounts for grasp type.Significance StatementIntracortical brain-computer interfaces (iBCIs) have emerged as a promising technology to potentially restore hand grasping and object interaction in people with tetraplegia. This study is among the first to quantify the degree to which hand grasp affects force-related – or kinetic – neural activity and decoding performance in individuals with tetraplegia. The study results enhance our overall understanding of how the brain encodes kinetic parameters across varying kinematic behaviors -- and in particular, the degree to which these parameters have independent versus interacting neural representations. Such investigations are a critical first step to incorporating force control into human-operated iBCI systems, which would move the technology towards restoring more functional and naturalistic tasks.

To assess and validate the Smart Exercise Bike designed for Parkinson's Disease (PD) rehabilitation, 47 individuals with PD were randomly assigned to either the static or dynamic cycling group, and completed three sessions of exercise. Heart rate, cadence and power data were captured and recorded for each patient during exercise. Motor function for each subject was assessed with the UPDRS Motor III test before and after the three exercise sessions to evaluate the effect of exercise on functional abilities. Individuals who completed three sessions of dynamic cycling showed an average of 13.8% improvement in the UPDRS, while individuals in the static cycling group worsened by 1.6% in UPDRS. To distinguish the static and dynamic cycling groups by biomechanical and physiological features, the complexity of the recorded signals (cadence, power, and heart rate) was examined using approximate entropy (ApEn), sample entropy (SaEn) and spectral entropy (SpEn) as measures of variability. A multiple linear regression (MLR) model was used to relate these features to changes in motor function as measured by the UPDRS Motor III scale. Pattern variability in cadence was greater in the dynamic group when compared to the static group. In contrast, variability in power was greater for the static group. UPDRS Motor III scores predicted from the pattern variability data were correlated to measured scores in both groups. These results support our previous study which explained how variability analysis results for biomechanical and physiological parameters of exercise can be used to predict improvements in motor function.

Objectives Exercise can improve motor function in people with Parkinson's disease but depression reduces the motivation to participate in regular exercise. The aim of this study was to develop a novel Enhanced Exercise Therapy program that uses manual-driven guided exercise and peer-facilitated psychoeducation for individuals with Parkinson's disease and depression. Design 24 week randomized controlled design. Methods Thirty individuals were randomized to Enhanced Exercise Therapy or self-guided therapy, and evaluated at baseline, 12-weeks and at 24-weeks. Enhanced Exercise Therapy included group exercise and group psychoeducation for 12 weeks. Between 13 and 24 weeks, individuals had access to the fitness facility but group sessions were not held. Self-guided therapy included written guidelines for a self-paced exercise program and psychoeducation. Primary outcome measures included the number of exercise sessions and International Physical Activity Questionnaire score. Secondary measures included resting heart rate, supine blood pressure, estimated VO2max and incidence of orthostatic hypotension. Results Twenty four individuals completed the study (80% retention) and both groups attended similar number of exercise sessions. There were no significant changes in cardiovascular fitness measures but there was a significant increase in the amount of physical activity in the Enhanced Exercise Therapy group and a decrease in the self-guided therapy group during the post-intervention period. Conclusions Enhanced Exercise Therapy appears to promote engagement in an exercise program and more physical activity, even after group sessions were concluded in individuals with Parkinson's disease and depression.

Objective : Recent reports indicate that making better assumptions about the user's intended movement can improve decoder calibration for intracortical brain–computer interfaces. Several methods now exist for estimating user intent, including an optimal feedback control model, a piecewise-linear feedback control model, ReFIT, and other heuristics. Which of these methods yields the best decoding performance? Methods : Using data from the BrainGate2 pilot clinical trial, we measured how a steady-state velocity Kalman filter decoder was affected by the choice of intention estimation method. We examined three separate components of the Kalman filter: dimensionality reduction, temporal smoothing, and output gain (speed scaling). Results : The decoder's dimensionality reduction properties were largely unaffected by the intention estimation method (the unsmoothed velocity vectors differed by $ in terms of how accurately they pointed at the target and how their speeds decreased near the target). In contrast, the smoothing and gain properties of the decoder were greatly affected ( $> \text{50}\% $ difference in average values). Surprisingly, simulation results show that these differences in gain and smoothing values were largely arbitrary, as all methods failed to optimize the gain and smoothing values to match the task parameters. Conclusion : Our results show that, gain and smoothing differences aside, current intention estimation methods yield nearly equivalent decoders and that simple models of user intent, such as a position error vector (target position minus cursor position), perform comparably to more elaborate models. Our results also highlight that current calibration methods yield arbitrary differences in gain and smoothing properties that can confound decoder comparisons.

IMPORTANCE Collective evidence has strongly suggested that deep brain stimulation (DBS) is a promising therapy for Tourette syndrome. OBJECTIVE To assess the efficacy and safety of DBS in a multinational cohort of patients with Tourette syndrome. DESIGN, SETTING, AND PARTICIPANTS The prospective International Deep Brain Stimulation Database and Registry included 185 patients with medically refractory Tourette syndrome who underwent DBS implantation from January 1, 2012, to December 31, 2016, at 31 institutions in 10 countries worldwide. EXPOSURES Patients with medically refractory symptoms received DBS implantation in the centromedian thalamic region (93 of 163 [57.1%]), the anterior globus pallidus internus (41 of 163 [25.2%]), the posterior globus pallidus internus (25 of 163 [15.3%]), and the anterior limb of the internal capsule (4 of 163 [2.5%]). MAINOUTCOMES AND MEASURES Scores on the Yale Global Tic Severity Scale and adverse events. RESULTS The International Deep Brain Stimulation Database and Registry enrolled 185 patients (of 171 with available data, 37 females and 134 males; mean [SD] age at surgery, 29.1 [10.8] years [range, 13-58 years]). Symptoms of obsessive-compulsive disorder were present in 97 of 151 patients (64.2%) and 32 of 148 (21.6%) had a history of self-injurious behavior. The mean (SD) total Yale Global Tic Severity Scale score improved from 75.01 (18.36) at baseline to 41.19 (20.00) at 1 year after DBS implantation (P

Object Stimulation of white matter pathways near targeted structures may contribute to therapeutic effects of deep brain stimulation (DBS) for patients with Parkinson disease (PD). Two tracts linking the basal ganglia and cerebellum have been described in primates: the subthalamopontocerebellar tract (SPCT) and the dentatothalamic tract (DTT). The authors used fiber tractography to evaluate white matter tracts that connect the cerebellum to the region of the basal ganglia in patients with PD who were candidates for DBS. Methods Fourteen patients with advanced PD underwent 3-T MRI, including 30-directional diffusion-weighted imaging sequences. Diffusion tensor tractography was performed using 2 regions of interest: ipsilateral subthalamic and red nuclei, and contralateral cerebellar hemisphere. Nine patients underwent subthalamic DBS, and the course of each tract was observed relative to the location of the most effective stimulation contact and the volume of tissue activated. Results In all patients 2 distinct tracts were identified that corresponded closely to the described anatomical features of the SPCT and DTT, respectively. The mean overall distance from the active contact to the DTT was 2.18 ± 0.35 mm, and the mean proportional distance relative to the volume of tissue activated was 1.35 ± 0.48. There was a nonsignificant trend toward better postoperative tremor control in patients with electrodes closer to the DTT. Conclusions The SPCT and the DTT may be related to the expression of symptoms in PD, and this may have implications for DBS targeting. The use of tractography to identify the DTT might assist with DBS targeting in the future.

Ablation or deep brain stimulation in the internal segment of the globus pallidus (GPi) is an effective therapy for the treatment of Parkinson's disease (PD). Yet many patients receive only partial benefit, including varying levels of improvement across different body regions, which may relate to a differential effect of GPi surgery on the different body regions. Unfortunately, our understanding of the somatotopic organization of human GPi is based on a small number of studies with limited sample sizes, including several based upon only a single recording track or plane. To fully address the three-dimensional somatotopic organization of GPi, we examined the receptive field properties of pallidal neurons in a large cohort of patients undergoing stereotactic surgery. The response of neurons to active and passive movements of the limbs and orofacial structures was determined, using a minimum of three tracks across at least two medial-lateral planes. Neurons (3183) were evaluated from 299 patients, of which 1972 (62%) were modulated by sensorimotor manipulation. Of these, 1767 responded to a single, contralateral body region, with the remaining 205 responding to multiple and/or ipsilateral body regions. Leg-related neurons were found dorsal, medial and anterior to arm-related neurons, while arm-related neurons were dorsal and lateral to orofacial-related neurons. This study provides a more detailed map of individual body regions as well as specific joints within each region and provides a potential explanation for the differential effect of lesions or DBS of the GPi on different body parts in patients undergoing surgical treatment of movement disorders.

Objective Functional electrical stimulation (FES) is a promising technology for restoring movement to paralyzed limbs. Intracortical brain-computer interfaces (iBCIs) have enabled intuitive control over virtual and robotic movements, and more recently over upper extremity FES neuroprostheses. However, electrical stimulation of muscles creates artifacts in intracortical microelectrode recordings that could degrade iBCI performance. Here, we investigate methods for reducing the cortically recorded artifacts that result from peripheral electrical stimulation. Approach One participant in the BrainGate2 pilot clinical trial had two intracortical microelectrode arrays placed in the motor cortex, and thirty-six stimulating intramuscular electrodes placed in the muscles of the contralateral limb. We characterized intracortically recorded electrical artifacts during both intramuscular and surface stimulation. We compared the performance of three artifact reduction methods: blanking, common average reference (CAR) and linear regression reference (LRR), which creates channel-specific reference signals, composed of weighted sums of other channels. Main results Electrical artifacts resulting from surface stimulation were 175 × larger than baseline neural recordings (which were 110 µV peak-to-peak), while intramuscular stimulation artifacts were only 4 × larger. The artifact waveforms were highly consistent across electrodes within each array. Application of LRR reduced artifact magnitudes to less than 10 µV and largely preserved the original neural feature values used for decoding. Unmitigated stimulation artifacts decreased iBCI decoding performance, but performance was almost completely recovered using LRR, which outperformed CAR and blanking and extracted useful neural information during stimulation artifact periods. Significance The LRR method was effective at reducing electrical artifacts resulting from both intramuscular and surface FES, and almost completely restored iBCI decoding performance (>90% recovery for surface stimulation and full recovery for intramuscular stimulation). The results demonstrate that FES-induced artifacts can be easily mitigated in FES + iBCI systems by using LRR for artifact reduction, and suggest that the LRR method may also be useful in other noise reduction applications.

OBJECTIVE: Brain Computer Interfaces (BCIs) can enable individuals with tetraplegia to communicate and control external devices. Though much progress has been made in improving the speed and robustness of neural control provided by intracortical BCIs, little research has been devoted to minimizing the amount of time spent on decoder calibration. APPROACH: We investigated the amount of time users needed to calibrate decoders and achieve performance saturation using two markedly different decoding algorithms: the steady-state Kalman filter, and a novel technique using Gaussian process regression (GP-DKF). MAIN RESULTS: Three people with tetraplegia gained rapid closed-loop neural cursor control and peak, plateaued decoder performance within three minutes of initializing calibration. We also show that a BCI-naïve user (T5) was able to rapidly attain closed-loop neural cursor control with the GP-DKF using self-selected movement imagery on his first-ever day of closed-loop BCI use, acquiring a target 37 seconds after initiating calibration. SIGNIFICANCE: These results demonstrate the potential for an intracortical BCI to be used immediately after deployment by people with paralysis, without the need for user learning or extensive system calibration.

Objective: Deep brain stimulation (DBS) surgeries commonly rely on brain atlases and microelectrode recordings (MER) to help identify the target location for electrode implantation. We present an automated method for optimally fitting a 3-dimensional brain atlas to intraoperative MER and predicting a target DBS electrode location in stereotactic coordinates for the patient. Methods: We retrospectively fit a 3-dimensional brain atlas to MER points from 10 DBS surgeries targeting the subthalamic nucleus (STN). We used a constrained optimization algorithm to maximize the MER points correctly fitted (i.e., contained) within the appropriate atlas nuclei. We compared our optimization approach to conventional anterior commissure-posterior commissure (AC/PC) scaling, and to manual fits performed by four experts. A theoretical DBS electrode target location in the dorsal STN was customized to each patient as part of the fitting process and compared to the location of the clinically defined therapeutic stimulation contact. Results: The human expert and computer optimization fits achieved significantly better fits than the AC/PC scaling (80, 81, and 41% of correctly fitted MER, respectively). However, the optimization fits were performed in less time than the expert fits and converged to a single solution for each patient, eliminating interexpert variance. Conclusions and Significance: DBS therapeutic outcomes are directly related to electrode implantation accuracy. Our automated fitting techniques may aid in the surgical decision-making process by optimally integrating brain atlas and intraoperative neurophysiological data to provide a visual guide for target identification.

Objective: Despite the clinical success of deep brain stimulation (DBS) for the treatment of Parkinson’s disease (PD), little is known about the electrical spread of the stimulation. The primary goal of this study was to integrate neuroimaging, neurophysiology and neurostimulation data sets from 10 patients with PD, unilaterally implanted with subthalamic nucleus (STN) DBS electrodes, to identify the theoretical volume of tissue activated (VTA) by clinically defined therapeutic stimulation parameters. Methods: Each patient specific model was created with a series of five steps: (1) definition of the neurosurgical stereotactic coordinate system within the context of preoperative imaging data; (2) entry of intraoperative microelectrode recording locations from neurophysiologically defined thalamic, subthalamic and substantia nigra neurons into the context of the imaging data; (3) fitting a three dimensional brain atlas to the neuroanatomy and neurophysiology of the patient; (4) positioning the DBS electrode in the documented stereotactic location, verified by postoperative imaging data; and (5) calculation of the VTA using a diffusion tensor based finite element neurostimulation model. Results: The patient specific models show that therapeutic benefit was achieved with direct stimulation of a wide range of anatomical structures in the subthalamic region. Interestingly, of the five patients exhibiting a greater than 40% improvement in their Unified PD Rating Scale (UPDRS), all but one had the majority of their VTA outside the atlas defined borders of the STN. Furthermore, of the five patients with less than 40% UPDRS improvement, all but one had the majority of their VTA inside the STN. Conclusions: Our results are consistent with previous studies suggesting that therapeutic benefit is associated with electrode contacts near the dorsal border of the STN, and provide quantitative estimates of the electrical spread of the stimulation in a clinically relevant context.

Deep brain stimulation (DBS) may improve disabling tics in severely affected medication and behaviorally resistant Tourette syndrome (TS). Here we review all reported cases of TS DBS and provide updated recommendations for selection, assessment, and management of potential TS DBS cases based on the literature and implantation experience. Candidates should have a Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM V) diagnosis of TS with severe motor and vocal tics, which despite exhaustive medical and behavioral treatment trials result in significant impairment. Deep brain stimulation should be offered to patients only by experienced DBS centers after evaluation by a multidisciplinary team. Rigorous preoperative and postoperative outcome measures of tics and associated comorbidities should be used. Tics and comorbid neuropsychiatric conditions should be optimally treated per current expert standards, and tics should be the major cause of disability. Psychogenic tics, embellishment, and malingering should be recognized and addressed. We have removed the previously suggested 25-year-old age limit, with the specification that a multidisciplinary team approach for screening is employed. A local ethics committee or institutional review board should be consulted for consideration of cases involving persons younger than 18 years of age, as well as in cases with urgent indications. Tourette syndrome patients represent a unique and complex population, and studies reveal a higher risk for post-DBS complications. Successes and failures have been reported for multiple brain targets; however, the optimal surgical approach remains unknown. Tourette syndrome DBS, though still evolving, is a promising approach for a subset of medication refractory and severely affected patients.

Background: Deep brain stimulation (DBS) of the subthalamic region is an established therapy for advanced Parkinson's disease (PD). However, patients often require time-intensive post-operative management to balance their coupled stimulation and medication treatments. Given the large and complex parameter space associated with this task, we propose that clinical decision support systems (CDSS) based on machine learning algorithms could assist in treatment optimization. Objective: Develop a proof-of-concept implementation of a CDSS that incorporates patient-specific details on both stimulation and medication. Methods: Clinical data from 10 patients, and 89 post-DBS surgery visits, were used to create a prototype CDSS. The system was designed to provide three key functions: 1) information retrieval; 2) visualization of treatment, and; 3) recommendation on expected effective stimulation and drug dosages, based on three machine learning methods that included support vector machines, Naïve Bayes, and random forest. Results: Measures of medication dosages, time factors, and symptom-specific pre-operative response to levodopa were significantly correlated with post-operative outcomes (P

High-frequency deep brain stimulation (DBS) of the thalamus or basal ganglia represents an effective clinical technique for the treatment of several medically refractory movement disorders (e.g., Parkinson's disease, essential tremor, and dystonia). In addition, new clinical applications of DBS for other neurologic and psychiatric disorders (e.g., epilepsy and obsessive-compulsive disorder) have been vaulted forward. Although DBS has been effective in the treatment of movement disorders and is rapidly being explored for the treatment of other neurologic disorders, the scientific understanding of its mechanisms of action remains unclear and continues to be debated in the scientific community. Optimization of DBS technology for present and future therapeutic applications will depend on identification of the therapeutic mechanism(s) of action. The goal of this review is to address the present knowledge of the effects of high frequency stimulation within the central nervous system and comment on the functional implications of this knowledge for uncovering the mechanism(s) of DBS. Four general hypotheses have been developed to explain the mechanism(s) of DBS: depolarization blockade, synaptic inhibition, synaptic depression, and stimulation-induced modulation of pathologic network activity. Using the results from microdialysis, neural recording, functional imaging, and neural modeling experiments, the authors address the main hypotheses and attempt to reconcile what have been considered conflicting results from different research modalities.

OBJECTIVE Do movements made with an intracortical BCI (iBCI) have the same movement time properties as able-bodied movements? Able-bodied movement times typically obey Fitts' law: [Formula: see text] (where MT is movement time, D is target distance, R is target radius, and [Formula: see text] are parameters). Fitts' law expresses two properties of natural movement that would be ideal for iBCIs to restore: (1) that movement times are insensitive to the absolute scale of the task (since movement time depends only on the ratio [Formula: see text]) and (2) that movements have a large dynamic range of accuracy (since movement time is logarithmically proportional to [Formula: see text]). APPROACH Two participants in the BrainGate2 pilot clinical trial made cortically controlled cursor movements with a linear velocity decoder and acquired targets by dwelling on them. We investigated whether the movement times were well described by Fitts' law. MAIN RESULTS We found that movement times were better described by the equation [Formula: see text], which captures how movement time increases sharply as the target radius becomes smaller, independently of distance. In contrast to able-bodied movements, the iBCI movements we studied had a low dynamic range of accuracy (absence of logarithmic proportionality) and were sensitive to the absolute scale of the task (small targets had long movement times regardless of the [Formula: see text] ratio). We argue that this relationship emerges due to noise in the decoder output whose magnitude is largely independent of the user's motor command (signal-independent noise). Signal-independent noise creates a baseline level of variability that cannot be decreased by trying to move slowly or hold still, making targets below a certain size very hard to acquire with a standard decoder. SIGNIFICANCE The results give new insight into how iBCI movements currently differ from able-bodied movements and suggest that restoring a Fitts' law-like relationship to iBCI movements may require non-linear decoding strategies.

Deep brain stimulation (DBS) is an established therapy for the management of advanced Parkinson's disease (PD). However, the coupled adjustment of pharmacologic therapy and stimulation parameter settings is a time-consuming process and treatment outcomes are not always optimal. In this study, we develop a linear function that relates the DBS parameters, the levodopa dosage, and patient-specific preoperative clinical data with the actual treatment motor outcomes. To this end, we incorporate image-based patient-specific computer models of the volume of tissue activated by DBS in a multilinear regression analysis (6 PD patients; 60 follow up visits). The resulting predictor function was highly correlated with the actual motor outcomes (r = 0.76; p0.05). These results demonstrate that the outcomes of a combined pharmacologic-DBS therapy can be predicted and may facilitate patient-specific treatment optimization for maximal benefits and minimal adverse effects.

BACKGROUND Microelectrode recording helps surgeons accurately localize boundaries of the subthalamic nucleus (STN) and surrounding structures in deep brain stimulation. OBJECTIVE To describe a novel adaptation of the Ben gun device to optimize efficient mapping. METHODS Patients who underwent STN deep brain stimulation over a 3-year period were reviewed. For the final year, the Ben gun was rotated 45° and the target was offset 1.4 mm lateral and anterior in the plane orthogonal to the intended trajectory to allow for simultaneous parallel tracks at target, 2.8 mm anterior (localizing the front of STN), and 2.8 mm lateral (identifying the internal capsule). Before this step, the initial pass consisted of 1 to 2 tracks with the frame center targeted to STN. The primary outcome measure was the number of passes required for accurate localization of the nucleus and boundaries. RESULTS Eighty-three electrodes were implanted in 45 patients (mean age, 62; range, 37-78 years), of which 29 electrodes were placed by the use of the new technique. One electrode (4%) required more than 1 pass using the new technique compared with 36 (67%) using the older technique (P < .01). The distance from original target to final electrode position increased from 0.67 ± 0.13 mm to 1.06 ± 0.15 mm (P < .05) with a greater tendency to move the final electrode position posteriorly. There was no statistically significant difference in benefit from neurostimulation. CONCLUSION This technique facilitates reliable localization of the STN with fewer passes, possibly decreasing the risks associated with more passes and longer duration of surgery.

We describe a case of pseudobulbar crying associated with deep brain stimulation (DBS) in the region of the subthalamic nucleus (STN). Patients with pseudobulbar crying show no other evidence of subjective feelings of depression such as dysphoria, anhedonia, or vegetative signs. This may be accompanied by other symptoms of pseudobulbar palsy and has been reported to occur with ischaemic or structural lesions in both cortical and subcortical regions of the brain. Although depression has been observed to result from DBS in the region of the STN, pseudobulbar crying has not been reported. A single patient who reported the symptoms of pseudobulbar crying after placement of an STN DBS was tested in the off DBS and on DBS conditions. The patient was tested using all four DBS lead contacts and the observations and results of the examiners were recorded. The Geriatric Depression Scale was used to evaluate for depression in all of the conditions. The patient exhibited pseudobulbar crying when on monopolar stimulation at all four lead contacts. The pseudobulbar crying resolved off stimulation. This case describes another type of affective change that may be associated with stimulation in the region of or within the STN. Clinicians should be aware of this potential complication, the importance of differentiating it from stimulation induced depression, and its response to a serotonin reuptake inhibitor, such as sertraline.

Objective. When using an intracortical BCI (iBCI), users modulate their neural population activity to move an effector towards a target, stop accurately, and correct for movement errors. We call the rules that govern this modulation a 'feedback control policy'. A better understanding of these policies may inform the design of higher-performing neural decoders. Approach. We studied how three participants in the BrainGate2 pilot clinical trial used an iBCI to control a cursor in a 2D target acquisition task. Participants used a velocity decoder with exponential smoothing dynamics. Through offline analyses, we characterized the users' feedback control policies by modeling their neural activity as a function of cursor state and target position. We also tested whether users could adapt their policy to different decoder dynamics by varying the gain (speed scaling) and temporal smoothing parameters of the iBCI. Main results. We demonstrate that control policy assumptions made in previous studies do not fully describe the policies of our participants. To account for these discrepancies, we propose a new model that captures (1) how the user's neural population activity gradually declines as the cursor approaches the target from afar, then decreases more sharply as the cursor comes into contact with the target, (2) how the user makes constant feedback corrections even when the cursor is on top of the target, and (3) how the user actively accounts for the cursor's current velocity to avoid overshooting the target. Further, we show that users can adapt their control policy to decoder dynamics by attenuating neural modulation when the cursor gain is high and by damping the cursor velocity more strongly when the smoothing dynamics are high. Significance. Our control policy model may help to build better decoders, understand how neural activity varies during active iBCI control, and produce better simulations of closed-loop iBCI movements.

Gait and balance disturbances in Parkinson's disease (PD) can be debilitating and may lead to increased fall risk. Deep brain stimulation (DBS) is a treatment option once therapeutic benefits from medication are limited due to motor fluctuations and dyskinesia. Optimizing DBS parameters for gait and balance can be significantly more challenging than for other PD motor symptoms. Furthermore, inter-rater reliability of the standard clinical PD assessment scale, Unified Parkinson's Disease Rating Scale (UPDRS), may introduce bias and washout important features of gait and balance that may respond differently to PD therapies. Study objectives were to evaluate clinician UPDRS gait and balance scoring inter-rater reliability, UPDRS sensitivity to different aspects of gait and balance, and how kinematic features extracted from motion sensor data respond to stimulation. Forty-two subjects diagnosed with PD were recruited with varying degrees of gait and balance impairment. All subjects had been prescribed dopaminergic medication, and 20 subjects had previously undergone DBS surgery. Subjects performed seven items of the gait and balance subset of the UPDRS while wearing motion sensors on the sternum and each heel and thigh. Inter-rater reliability varied by UPDRS item. Correlation coefficients between at least one kinematic feature and corresponding UPDRS scores were greater than 0.75 for six of the seven items. Kinematic features improved (p0.05) from DBS-OFF to DBS-ON for three UPDRS items. Despite achieving high correlations with the UPDRS, evaluating individual kinematic features may help address inter-rater reliability issues and rater bias associated with focusing on different aspects of a motor task.

Depression has been estimated to affect 1 in 3 individuals with Parkinson's disease (PD) and can lead to worse health outcomes and decreased quality of life. Anxiety further complicates PD outcomes. Pharmacologic treatments of depression and anxiety can have negative side effects in patients with PD, including exacerbation of PD symptoms. There is a critical need for alternative treatment approaches that address depression and anxiety among patients with PD. Psychosocial or behavioral approaches are known to be effective for depression generally, but only a handful of studies have examined the role of psychosocial treatments of patients with depression in PD.The aim of this article was to review published psychosocial treatment studies of depression and anxiety in patients with PD.The PubMed database was searched for articles published in English before April 2011 using the terms Parkinson's disease, depression, anxiety, psychotherapy, cognitive therapy, behavioral treatment, behavioral therapy, nonpharmacologic treatment, psychoeducation, education, psychosocial treatment, and stress management. Articles included were prospective clinical trials utilizing specific depression or anxiety assessments as primary or secondary outcomes in patients with PD.Nine reports derived from 8 separate studies fit the inclusion criteria and were included in this review. All studies were published between 1997 and 2011, and all but 3 had small sample sizes (40 patients). Interventions included cognitive behavioral therapy (CBT), psychodrama, education, and behavior therapy as well as multidisciplinary rehabilitation. Cognitive behavioral therapy was the most studied and was shown to decrease depressive and anxiety symptoms in patients with PD. Other individual and group therapies may improve depression and anxiety in patients with PD, but the general paucity of studies and study methods limit the interpretation of these results.There have been few studies on psychosocial treatments that specifically assess change in depression and anxiety among patients with PD. While results for CBT and other modes of therapy are promising for acute management of depression and anxiety, longer term effects after treatment have been variable. There is a need for additional studies on psychosocial interventions in people with PD.

The objective was to develop and evaluate algorithms for quantifying gait and lower extremity bradykinesia in patients with Parkinson's disease using kinematic data recorded on a heel-worn motion sensor unit. Subjects were evaluated by three movement disorder neurologists on four domains taken from the Movement Disorders Society Unified Parkinson's Disease Rating Scale while wearing the motion sensor unit. Multiple linear regression models were developed based on the recorded kinematic data and clinician scores and produced outputs highly correlated to clinician scores with an average correlation coefficient of 0.86. The newly developed models have been integrated into a home-based system for monitoring Parkinson's disease motor symptoms.

Summary Since the early 1930s, physicians have developed and refined various surgical therapies for the treatment of Parkinson's disease. In this review we examine some of the problems associated with early surgical therapies, the development of new techniques and targets, and the results of clinical trials examining the safety and efficacy of these techniques. Ablative techniques include pallidotomy, thalamotomy, and, more recently, subthalamotomy. Because of concern over the high incidence of side-effects associated with bilateral ablative procedures, alternative approaches were explored. Deep brain stimulation (DBS) was subsequently developed and successfully applied in the internal globus pallidus, subthalamic nucleus, and thalamus for the treatment of Parkinson's disease. Recent approaches include biological neurorestorative techniques—surgical therapies with transplantation, gene therapy, and growth factors are all being studied. Although a great deal of work remains to be done, advances in surgical therapies for the treatment of Parkinson's disease are moving forward at an unprecedented pace.

Autonomic dysfunction is common in parkinsonian syndromes, particularly those involving dysregulation of alpha-synuclein, and may result from neurodegeneration in autonomic regulatory regions of the brain or peripherial autonomic ganglia. The most limiting cardiovascular autonomic dysfunction in these diseases is orthostatic hypotension, which is particularly prominent in multiple system atrophy. Postprandial hypotension and supine hypertension, as well as dopaminergic therapy, often complicate the management of orthostatic hypotension in patients with parkinsonian syndromes.

Objective: To investigate whether a single daily dose of testosterone replacement gel has beneficial effects on testosterone deficiency symptoms, cognitive function, nonmotor symptoms of Parkinson disease (PD), and motor symptoms of PD. Background: Recently it has been observed that testosterone replacement therapy improves refractory nonmotor symptoms in testosterone-deficient men with PD. Many of the symptoms of testosterone deficiency are nonspecific and overlap with the nonmotor symptoms of PD, such as decreased enjoyment of life, lack of energy, sexual dysfunction, and depression. Replacement therapy for men with PD and comorbid testosterone deficiency may be an important addition to antiparkinsonian management strategies. Methods: A prospective open-labeled pilot study of testosterone topical gel (5 g of AndroGel; Unimed Pharmaceutical Inc, Deerfield, Ill) administered daily to testosterone-deficient (free testosterone80 pg/mL) men with PD. All 10 patients were followed up for 1 month and 6 patients were followed up for a total of 3 months. Patients were administered a battery of testosterone deficiency questionnaires, cognitive studies, and scales of PD nonmotor and motor function at baseline, 1, and 3 months. Results: With the daily transdermal testosterone gel, patients had an average increase in levels of free testosterone from baseline (53 pg/mL) to a 1-month follow-up visit (131 pg/mL; P=.06) and to a 3-month follow-up visit (98 pg/mL; P=.04). Testosterone deficiency symptoms improved in these patients (St Louis Testosterone Deficiency Questionnaire) from baseline (7.9 deficiency symptoms) to 1 month (5.6 deficiency symptoms, P=.04) and 3 months (5.8 deficiency symptoms, P=.08). The Unified Parkinson’s Disease Rating Scale IV showed improvement at 1 month (P=.008). Additionally, there were trends toward improvement in the following scales: Unified Parkinson’s Disease Rating Scale I at the 3-month follow-up (P = .09), Letter Fluency at the 3-month follow-up (P=.08), and the Hamilton Anxiety Scale at the 1-month follow-up (P=.09). Conclusions: A daily dose of transdermal testosterone gel improved testosterone deficiency symptoms in men with PD. Although there were trends in improvement in other nonmotor and motor symptoms of PD, future placebo control studies will need to be powered to answer these important questions. Whether testosterone deficiency is simply a comorbidity in PD or whether it plays a role in the pathogenesis of disease also remains for future study. Arch Neurol. 2002;59:1750-1753