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Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson's disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected neural features which may result in a less robust and biased therapy. In this study, we propose Neural-to-Gait Neural network (N2GNet), a novel deep learning-based regression model capable of tracking real-time gait performance from subthalamic nucleus local field potentials (STN LFPs). The LFP data were acquired when eighteen PWP performed stepping in place, and the ground reaction forces were measured to track their weight shifts representing gait performance. By exhibiting a stronger correlation with weight shifts compared to the higher-correlation beta power from the two leads and outperforming other evaluated model designs, N2GNet effectively leverages a comprehensive frequency band, not limited to the beta range, to track gait performance solely from STN LFPs., Competing Interests: Competing interests The authors declare no competing interests. Additional Declarations: No competing interests reported.

Adaptive deep brain stimulation (aDBS) is an emerging advancement in DBS technology; however, local field potential (LFP) signal rate detection sufficient for aDBS algorithms and the methods to set-up aDBS have yet to be defined. Here we summarize sensing data and aDBS programming steps associated with the ongoing Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) pivotal trial (NCT04547712). Sixty-eight patients were enrolled with either subthalamic nucleus or globus pallidus internus DBS leads connected to a Medtronic Percept TM PC neurostimulator. During the enrollment and screening procedures, a LFP (8-30 Hz, ≥1.2 µVp) control signal was identified by clinicians in 84.8% of patients on medication (65% bilateral signal), and in 92% of patients off medication (78% bilateral signal). The ADAPT-PD trial sensing data indicate a high LFP signal presence in both on and off medication states of these patients, with bilateral signal in the majority, regardless of PD phenotype., (© 2024. The Author(s).)

People with Parkinson's disease (PWP) face critical challenges, including lack of access to neurological care, inadequate measurement and communication of motor symptoms, and suboptimal medication management and compliance. We have developed QDG-Care: a comprehensive connected care platform for Parkinson's disease (PD) that delivers validated, quantitative metrics of all motor signs in PD in real time, monitors the effects of adjusting therapy and medication adherence and is accessible in the electronic health record. In this article, we describe the design and engineering of all components of QDG-Care, including the development and utility of the QDG Mobility and Tremor Severity Scores. We present the preliminary results and insights from an at-home trial using QDG-Care. QDG technology has enormous potential to improve access to, equity of, and quality of care for PWP, and improve compliance with complex time-critical medication regimens. It will enable rapid "Go-NoGo" decisions for new therapeutics by providing high-resolution data that require fewer participants at lower cost and allow more diverse recruitment., (© 2024. The Author(s).)

Background: Freezing of gait (FOG) is a debilitating symptom of Parkinson's disease (PD) that is often refractory to medication. Pathological prolonged beta bursts within the subthalamic nucleus (STN) are associated with both worse impairment and freezing behavior in PD, which are improved with deep brain stimulation (DBS). The goal of the current study was to investigate the feasibility, safety, and tolerability of beta burst-driven adaptive DBS (aDBS) for FOG in PD., Methods: Seven individuals with PD were implanted with the investigational Summit ™ RC+S DBS system (Medtronic, PLC) with leads placed bilaterally in the STN. A PC-in-the-loop architecture was used to adjust stimulation amplitude in real-time based on the observed beta burst durations in the STN. Participants performed either a harnessed stepping-in-place task or a free walking turning and barrier course, as well as clinical motor assessments and instrumented measures of bradykinesia, OFF stimulation, on aDBS, continuous DBS (cDBS), or random intermittent DBS (iDBS)., Results: Beta burst driven aDBS was successfully implemented and deemed safe and tolerable in all seven participants. Gait metrics such as overall percent time freezing and mean peak shank angular velocity improved from OFF to aDBS and showed similar efficacy as cDBS. Similar improvements were also seen for overall clinical motor impairment, including tremor, as well as quantitative metrics of bradykinesia., Conclusion: Beta burst driven adaptive DBS was feasible, safe, and tolerable in individuals with PD with gait impairment and FOG., Competing Interests: Competing Interests The authors declare no competing interests related to this study.

Competing Interests: Declaration of competing interest H B–S: none. AM: none.

The deep brain stimulation (DBS) Think Tank X was held on August 17-19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation . Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the "trough of disillusionment." DBS for depression was considered as "re-emerging" and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS., Competing Interests: HM received consulting and IP licensing fees from Abbott Labs. WG received consulting fees from Biohaven and royalties from Nview, LLC and OCDscales, and LLC. EP had received research support from Mainstay, Medtronic, Neuros Medical, Nevro Corp, ReNeuron, SPR, and Saluda, personal fees from Abbott Neuromodulation, Biotronik, Medtronic Neuromodulation, Nalu, Neuros Medical, Nevro, Presidio Medical, Saluda, and Vertos, and holds stock options from SynerFuse and Neuro42. JV had received consulting fees and grant support by Medtronic and Boston Scientific both manufacturers of DBS systems, consulting fees by Newronika and CereGate and honoraria for lecturing by Abbott. JH was a consultant for Neuralink and serves on the Medical Advisory Board of Enspire DBS. SS was a consultant for Boston Scientific, Zimmer Biomet, NeuroPace, Koh Young, and is a co-founder of Motif Neurotech. RSR was employed by Medtronic Inc. MM was employed by Boston Scientific Neuromodulation Corporation. DG was employed by NeuroPace, Inc. LK, MA, LR, SMa, and AP were employed by Newronika. RG was employed by Rune Labs. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wong, Mayberg, Wang, Richardson, Halpern, Krinke, Arlotti, Rossi, Priori, Marceglia, Gilron, Cavanagh, Judy, Miocinovic, Devergnas, Sillitoe, Cernera, Oehrn, Gunduz, Goodman, Petersen, Bronte-Stewart, Raike, Malekmohammadi, Greene, Heiden, Tan, Volkmann, Voon, Li, Sah, Coyne, Silburn, Kubu, Wexler, Chandler, Provenza, Heilbronner, Luciano, Rozell, Fox, de Hemptinne, Henderson, Sheth and Okun.)

Objective . To provide a design analysis and guidance framework for the implementation of concurrent stimulation and sensing during adaptive deep brain stimulation (aDBS) with particular emphasis on artifact mitigations. Approach . We defined a general architecture of feedback-enabled devices, identified key components in the signal chain which might result in unwanted artifacts and proposed methods that might ultimately enable improved aDBS therapies. We gathered data from research subjects chronically-implanted with an investigational aDBS system, Summit RC + S, to characterize and explore artifact mitigations arising from concurrent stimulation and sensing. We then used a prototype investigational implantable device, DyNeuMo, and a bench-setup that accounts for tissue-electrode properties, to confirm our observations and verify mitigations. The strategies to reduce transient stimulation artifacts and improve performance during aDBS were confirmed in a chronic implant using updated configuration settings. Main results. We derived and validated a 'checklist' of configuration settings to improve system performance and areas for future device improvement. Key considerations for the configuration include (a) active instead of passive recharge, (b) sense-channel blanking in the amplifier, (c) high-pass filter settings, (d) tissue-electrode impedance mismatch management, (e) time-frequency trade-offs in the classifier, (f) algorithm blanking and transition rate limits. Without proper channel configuration, the aDBS algorithm was susceptible to limit-cycles of oscillating stimulation independent of physiological state. By applying the checklist, we could optimize each block's performance characteristics within the overall system. With system-level optimization, a 'fast' aDBS prototype algorithm was demonstrated to be feasible without reentrant loops, and with noise performance suitable for subcortical brain circuits. Significance . We present a framework to study sources and propose mitigations of artifacts in devices that provide chronic aDBS. This work highlights the trade-offs in performance as novel sensing devices translate to the clinic. Finding the appropriate balance of constraints is imperative for successful translation of aDBS therapies. Clinical trial: Institutional Review Board and Investigational Device Exemption numbers: NCT02649166/IRB201501021 (University of Florida), NCT04043403/IRB52548 (Stanford University), NCT03582891/IRB1824454 (University of California San Francisco). IDE #180 097., (Creative Commons Attribution license.)

Background: Freezing of gait, a common symptom of Parkinson's disease, presents as sporadic episodes in which an individual's feet suddenly feel stuck to the ground. Inertial measurement units (IMUs) promise to enable at-home monitoring and personalization of therapy, but there is a lack of consensus on the number and location of IMUs for detecting freezing of gait. The purpose of this study was to assess IMU sets in the context of both freezing of gait detection performance and patient preference., Methods: Sixteen people with Parkinson's disease were surveyed about sensor preferences. Raw IMU data from seven people with Parkinson's disease, wearing up to eleven sensors, were used to train convolutional neural networks to detect freezing of gait. Models trained with data from different sensor sets were assessed for technical performance; a best technical set and minimal IMU set were identified. Clinical utility was assessed by comparing model- and human-rater-determined percent time freezing and number of freezing events., Results: The best technical set consisted of three IMUs (lumbar and both ankles, AUROC = 0.83), all of which were rated highly wearable. The minimal IMU set consisted of a single ankle IMU (AUROC = 0.80). Correlations between these models and human raters were good to excellent for percent time freezing (ICC = 0.93, 0.89) and number of freezing events (ICC = 0.95, 0.86) for the best technical set and minimal IMU set, respectively., Conclusions: Several IMU sets consisting of three IMUs or fewer were highly rated for both technical performance and wearability, and more IMUs did not necessarily perform better in FOG detection. We openly share our data and software to further the development and adoption of a general, open-source model that uses raw signals and a standard sensor set for at-home monitoring of freezing of gait., (© 2022. The Author(s).)

Background: Assessment of motor signs in Parkinson's disease (PD) requires an in-person examination. However, 50% of people with PD do not have access to a neurologist. Wearable sensors can provide remote measures of some motor signs but require continuous monitoring for several days. A major unmet need is reliable metrics of all cardinal motor signs, including rigidity, from a simple short active task that can be performed remotely or in the clinic., Objective: Investigate whether thirty seconds of repetitive alternating finger tapping (RAFT) on a portable quantitative digitography (QDG) device, which measures amplitude and timing, produces reliable metrics of all cardinal motor signs in PD., Methods: Ninety-six individuals with PD and forty-two healthy controls performed a thirty-second QDG-RAFT task and clinical motor assessment. Eighteen individuals were followed longitudinally with repeated assessments for an average of three years and up to six years., Results: QDG-RAFT metrics showed differences between PD and controls and provided correlated metrics for total motor disability (MDS-UPDRS III) and for rigidity, bradykinesia, tremor, gait impairment, and freezing of gait (FOG). Additionally, QDG-RAFT tracked disease progression over several years off therapy and showed differences between akinetic-rigid and tremor-dominant phenotypes, as well as people with and without FOG., Conclusions: QDG is a reliable technology, which could be used in the clinic or remotely. This could improve access to care, allow complex remote disease management based on data received in real time, and accurate monitoring of disease progression over time in PD. QDG-RAFT also provides the comprehensive motor metrics needed for therapeutic trials.

Freezing of gait (FOG), a debilitating symptom of Parkinson's disease (PD), can be safely studied using the stepping in place (SIP) task. However, clinical, visual identification of FOG during SIP is subjective and time consuming, and automatic FOG detection during SIP currently requires measuring the center of pressure on dual force plates. This study examines whether FOG elicited during SIP in 10 individuals with PD could be reliably detected using kinematic data measured from wearable inertial measurement unit sensors (IMUs). A general, logistic regression model (area under the curve = 0.81) determined that three gait parameters together were overall the most robust predictors of FOG during SIP: arrhythmicity, swing time coefficient of variation, and swing angular range. Participant-specific models revealed varying sets of gait parameters that best predicted FOG for each participant, highlighting variable FOG behaviors, and demonstrated equal or better performance for 6 out of the 10 participants, suggesting the opportunity for model personalization. The results of this study demonstrated that gait parameters measured from wearable IMUs reliably detected FOG during SIP, and the general and participant-specific gait parameters allude to variable FOG behaviors that could inform more personalized approaches for treatment of FOG and gait impairment in PD.

Introduction: Reliable and accurate measures of rigidity have remained elusive in remote assessments of Parkinson's disease (PD). This has severely limited the utility of telemedicine in the care and treatment of people with PD. It has also had a large negative impact on the scope of available outcomes, and on the costs, of multicenter clinical trials in PD. The goal of this study was to determine if quantitative measures from an engineered keyboard were sensitive and related to clinical measures of rigidity., Methods: Sixteen participants with idiopathic PD, off antiparkinsonian medications, and eleven age-matched control participants performed a 30 second repetitive alternating finger tapping task on an engineered keyboard and were assessed with the Unified Parkinson's Disease Rating Scale - motor (UPDRS-III)., Results: The speed of the key release was significantly slower in the PD compared to control cohorts (p < 0.0001). In the PD cohort key release speed correlated with the lateralized upper extremity UPDRS III rigidity score (r = - 0.58, p < 0.0001), but not with the lateralized upper extremity tremor score (r = - 0.14, p = 0.43)., Conclusions: This validated measure of rigidity complements our previous validation of temporal metrics of the repetitive alternating finger tapping task with the UPDRS III, bradykinesia and with the ability to quantify tremor, arrhythmicity and freezing episodes, and suggests that 30 seconds of alternating finger tapping on a portable engineered keyboard could transform the treatment of PD with telemedicine and the precision of multicenter clinical trials., (Copyright © 2020. Published by Elsevier Ltd.)

Freezing of gait (FOG) is a devastating motor symptom of Parkinson's disease that leads to falls, reduced mobility, and decreased quality of life. Reliably eliciting FOG has been difficult in the clinical setting, which has limited discovery of pathophysiology and/or documentation of the efficacy of treatments, such as different frequencies of subthalamic deep brain stimulation (STN DBS). In this study we validated an instrumented gait task, the turning and barrier course (TBC), with the international standard FOG questionnaire question 3 (FOG-Q3, r = 0.74, p < 0.001). The TBC is easily assembled and mimics real-life environments that elicit FOG. People with Parkinson's disease who experience FOG (freezers) spent more time freezing during the TBC compared to during forward walking (p = 0.007). Freezers also exhibited greater arrhythmicity during non-freezing gait when performing the TBC compared to forward walking (p = 0.006); this difference in gait arrhythmicity between tasks was not detected in non-freezers or controls. Freezers' non-freezing gait was more arrhythmic than that of non-freezers or controls during all walking tasks (p < 0.05). A logistic regression model determined that a combination of gait arrhythmicity, stride time, shank angular range, and asymmetry had the greatest probability of classifying a step as FOG (area under receiver operating characteristic curve = 0.754). Freezers' percent time freezing and non-freezing gait arrhythmicity decreased, and their shank angular velocity increased in the TBC during both 60 Hz and 140 Hz STN DBS (p < 0.05) to non-freezer values. The TBC is a standardized tool for eliciting FOG and demonstrating the efficacy of 60 Hz and 140 Hz STN DBS for gait impairment and FOG. The TBC revealed gait parameters that differentiated freezers from non-freezers and best predicted FOG; these may serve as relevant control variables for closed loop neurostimulation for FOG in Parkinson's disease., Competing Interests: Dr. Helen Bronte-Stewart is a member of a clinical advisory board for Medtronic Inc. and Scott Delp is a scientific advisor and board member of Cala Health, Circuit Therapeutics, and Zebra Medical Technologies, and receives compensation for this service. Dr.Helen Bronte-Stewart and Johanna O’Day have submitted a provisional patent as co-inventors of systems and methods for deep brain stimulation kinematic controllers (patent #S19-551). This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Clinical deep brain stimulation (DBS) technology is evolving to enable chronic recording of local field potentials (LFPs) that represent electrophysiological biomarkers of the underlying disease state. However, little is known about the biophysical basis of LFPs, or how the patient's unique brain anatomy and electrode placement impact the recordings. Therefore, we developed a patient-specific computational framework to analyze LFP recordings within a clinical DBS context. We selected a subject with Parkinson's disease implanted with a Medtronic Activa PC+S DBS system and reconstructed their subthalamic nucleus (STN) and DBS electrode location using medical imaging data. The patient-specific STN volume was populated with 235,280 multicompartment STN neuron models, providing a neuron density consistent with histological measurements. Each neuron received time-varying synaptic inputs and generated transmembrane currents that gave rise to the LFP signal recorded at DBS electrode contacts residing in a finite element volume conductor model. We then used the model to study the role of synchronous beta-band inputs to the STN neurons on the recorded power spectrum. Three bipolar pairs of simultaneous clinical LFP recordings were used in combination with an optimization algorithm to customize the neural activity parameters in the model to the patient. The optimized model predicted a 2.4-mm radius of beta-synchronous neurons located in the dorsolateral STN. These theoretical results enable biophysical dissection of the LFP signal at the cellular level with direct comparison to the clinical recordings, and the model system provides a scientific platform to help guide the design of DBS technology focused on the use of subthalamic beta activity in closed-loop algorithms. NEW & NOTEWORTHY The analysis of deep brain stimulation of local field potential (LFP) data is rapidly expanding from scientific curiosity to the basis for clinical biomarkers capable of improving the therapeutic efficacy of stimulation. With this growing clinical importance comes a growing need to understand the underlying electrophysiological fundamentals of the signals and the factors contributing to their modulation. Our model reconstructs the clinical LFP from first principles and highlights the importance of patient-specific factors in dictating the signals recorded.

Reward hypersensitization is a common feature of neuropsychiatric disorders, manifesting as impulsivity for anticipated incentives. Temporally specific changes in activity within the nucleus accumbens (NAc), which occur during anticipatory periods preceding consummatory behavior, represent a critical opportunity for intervention. However, no available therapy is capable of automatically sensing and therapeutically responding to this vulnerable moment in time when anticipation-related neural signals may be present. To identify translatable biomarkers for an off-the-shelf responsive neurostimulation system, we record local field potentials from the NAc of mice and a human anticipating conventional rewards. We find increased power in 1- to 4-Hz oscillations predominate during reward anticipation, which can effectively trigger neurostimulation that reduces consummatory behavior in mice sensitized to highly palatable food. Similar oscillations are present in human NAc during reward anticipation, highlighting the translational potential of our findings in the development of a treatment for a major unmet need., Competing Interests: Conflict of interest statement: A.G.M., S.A.S., and H.B.-S. were coauthors on a meeting report published in 2015., (Copyright © 2017 the Author(s). Published by PNAS.)

The goal of this study was to investigate subthalamic (STN) neural features of Freezers and Non-Freezers with Parkinson's disease (PD), while freely walking without freezing of gait (FOG) and during periods of FOG, which were better elicited during a novel turning and barrier gait task than during forward walking., Methods: Synchronous STN local field potentials (LFPs), shank angular velocities, and ground reaction forces were measured in fourteen PD subjects (eight Freezers) off medication, OFF deep brain stimulation (DBS), using an investigative, implanted, sensing neurostimulator (Activa® PC+S, Medtronic, Inc.). Tasks included standing still, instrumented forward walking, stepping in place on dual forceplates, and instrumented walking through a turning and barrier course., Results: During locomotion without FOG, Freezers showed lower beta (13-30Hz) power (P=0.036) and greater beta Sample Entropy (P=0.032), than Non-Freezers, as well as greater gait asymmetry and arrhythmicity (P<0.05 for both). No differences in alpha/beta power and/or entropy were evident at rest. During periods of FOG, Freezers showed greater alpha (8-12Hz) Sample Entropy (P<0.001) than during walking without FOG., Conclusions: A novel turning and barrier course was superior to FW in eliciting FOG. Greater unpredictability in subthalamic beta rhythms was evident during stepping without freezing episodes in Freezers compared to Non-Freezers, whereas greater unpredictability in alpha rhythms was evident in Freezers during FOG. Non-linear analysis of dynamic neural signals during gait in freely moving people with PD may yield greater insight into the pathophysiology of FOG; whether the increases in STN entropy are causative or compensatory remains to be determined. Some beta LFP power may be useful for rhythmic, symmetric gait and DBS parameters, which completely attenuate STN beta power may worsen rather than improve FOG., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Subthalamic nucleus (STN) local field potential (LFP) recordings demonstrate beta (13-30Hz) band oscillations in Parkinson's disease (PD) defined as elevations of spectral power. The amount of attenuation of beta band power on therapeutic levels of high frequency (HF) deep brain stimulation (DBS) and/or dopaminergic medication has been correlated with the degree of improvement in bradykinesia and rigidity from the therapy, which has led to the suggestion that elevated beta band power is a marker of PD motor disability. A fundamental question has not been answered: whether there is a prolonged attenuation of beta band power after withdrawal of chronic HF DBS and whether this is related to a lack of progression or even improvement in the underlying motor disability. Until now, in human PD subjects, STN LFP recordings were only attainable in the peri-operative period and after short periods of stimulation. For the first time, using an investigational, implanted sensing neurostimulator (Activa® PC+S, Medtronic, Inc.), STN LFPs and motor disability were recorded/assessed after withdrawal of chronic (6 and 12month) HF DBS in freely moving PD subjects. Beta band power was similar within 14s and 60min after stimulation was withdrawn, suggesting that "off therapy" experiments can be conducted almost immediately after stimulation is turned off. After withdrawal of 6 and 12months of STN DBS, beta band power was significantly lower (P<0.05 at 6 and 12months) and off therapy UPDRS scores were better (P<0.05 at 12months) compared to before DBS was started. The attenuation in beta band power was correlated with improvement in motor disability scores (P<0.05). These findings were supported by evidence of a gradual increase in beta band power in two unstimulated STNs after 24months and could not be explained by changes in lead impedance. This suggests that chronic HF DBS exerts long-term plasticity in the sensorimotor network, which may contribute to a lack of progression in underlying motor disability in PD., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Arrhythmokinesis, the variability in repetitive movements, is a fundamental feature of Parkinson's disease (PD). We hypothesized that unimanual repetitive alternating finger tapping (AFT) would reveal more arrhythmokinesis compared to bimanual single finger alternating hand tapping (SFT), in PD., Methods: The variability of inter-strike interval (CVISI) and of amplitude (CVAMP) during AFT and SFT were measured on an engineered, MRI-compatible keyboard in sixteen PD subjects off medication and in twenty-four age-matched controls., Results: The CVISI and CVAMP of the more affected (MA) and less affected (LA) sides in PD subjects were greater during AFT than SFT (P < 0.05). However, there was no difference between AFT and SFT for controls. Both CVISI and CVAMP were greater in the MA and LA hands of PD subjects versus controls during AFT (P < 0.01). The CVISI and CVAMP of the MA, but not the LA hand, were greater in PDs versus controls during SFT (P < 0.05). Also, AFT, but not SFT, detected a difference between the MA and LA hands of PDs (P < 0.01)., Conclusions: Unimanual, repetitive alternating finger tapping brings out more arrhythmokinesis compared to bimanual, single finger tapping in PDs but not in controls. Arrhythmokinesis during unimanual, alternating finger tapping captured a significant difference between both the MA and LA hands of PD subjects and controls, whereas that during a bimanual, single finger tapping task only distinguished between the MA hand and controls. Arrhythmokinesis underlies freezing of gait and may also underlie the freezing behavior documented in fine motor control if studied using a unimanual alternating finger tapping task.

Current deep brain stimulation paradigms deliver continuous stimulation to deep brain structures to ameliorate the symptoms of Parkinson's disease. This continuous stimulation has undesirable side effects and decreases the lifespan of the unit's battery, necessitating earlier replacement. A closed-loop deep brain stimulator that uses brain signals to determine when to deliver stimulation based on the occurrence of symptoms could potentially address these drawbacks of current technology. Attempts to detect Parkinsonian tremor using brain signals recorded during the implantation procedure have been successful. However, the ability of these methods to accurately detect tremor over extended periods of time is unknown. Here we use local field potentials recorded during a deep brain stimulation clinical follow-up visit 1 month after initial programming to build a tremor detection algorithm and use this algorithm to detect tremor in subsequent visits up to 8 months later. Using this method, we detected the occurrence of tremor with accuracies between 68-93%. These results demonstrate the potential of tremor detection methods for efficacious closed-loop deep brain stimulation over extended periods of time.

The proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Unlabelled: Freezing of gait (FOG) is associated with gait asymmetry and arrhythmicity, cognitive impairment in Parkinson's disease (PD). However, the role of postural instability (PI) in and the effect of dopaminergic medication (meds) on FOG are unclear. We investigated the effect of meds on FOG using a validated metric, Stepping in Place (SIP) and the relationship between PI and FOG., Methods: We assessed static posturography (off meds), SIP, UPDRS-III (off/on meds) and the FOG-questionnaire (FOG-Q) in 15 freezers/15 non-freezers and 14 healthy controls., Results: UPDRS-III, rigidity, tremor (P < 0.01) and axial subscores (P < 0.05) improved with meds in freezers. Only UPDRS-III and tremor improved in non-freezers (P < 0.01). Meds improved freezing episode (FE) frequency, duration and stride duration in freezers (P < 0.01). Over 73% of freezers did not freeze on meds, although one freezer had more and longer duration FEs. Meds did not improve SIP cycle asymmetry and arrhythmicity, which remained greater in freezers compared to other groups on and off meds (P < 0.01, P < 0.05 respectively). Center of pressure (CoP) mediolateral displacement and velocity (VCoP) in both directions were larger in freezers (P < 0.05). FOG-Q was correlated with CoP anteroposterior displacement and mediolateral VCoP (R = 0.42; R = 0.40, P < 0.05). The improvement of FOG frequency and duration but not of gait asymmetry and arrhythmicity on meds suggests that both dopaminergic and non-dopaminergic networks contribute to FOG. The correlations between postural instability and FOG severity and SIP asymmetry on meds, suggest that as the disease progresses, postural instability interferes with gait symmetry and lead to on meds FOG and falls., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

People with Parkinson's disease (PD) perceive that their movement amplitude is greater than what they actually perform. The neural mechanisms underlying one's perception of movement are believed to involve the sensorimotor integration process (SIP). How PD affects the SIP is not well understood. A previous study interrogating the SIP showed healthy adults (HAs) overestimated their limb position in the direction of movement and the error and its variance (VOE) depended on movement duration. We asked if PDs showed errors in perceived limb position and if the dependence on movement duration was different from HAs. We used an existing computational model of the SIP to explore mechanisms for the error and VOE as a function of movement duration. Twenty PDs, off medication, and 20 age-matched HAs were asked to estimate the position of their hand after performing 50, slow, non-visually guided wrist flexion or extension movements for a random period of time (<4.0 s). Both groups overestimated the amount they moved; however, the PDs' error and VOE were larger (p<0.001). HAs showed increasing error/VOE for small movement durations that reduced/stabilized for longer movement durations. PDs however showed increasing error/VOE with increasing movement duration that did not significantly improve/stabilize. The model suggested that the basis for such perceptual deficits may be abnormal proprioceptive feedback and/or processing of an abnormal internal impression (prediction) that underestimates movement amplitude. Simulation results imply that the PD's SIP could no longer effectively access sensory (proprioceptive) feedback to correct errors in other components of the SIP due to the abnormal processing of sensory feedback. We suggest from this study that an impaired perception of movement amplitude and sensory processing deficits contribute to hypokinesia in PD., (Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.)

Objectives: 1) To characterize patterns of globus pallidus interna neural synchrony in patients with secondary dystonia; 2) to determine whether neural hypersynchrony in the globus pallidus externa (GPe) and interna (GPi) is attenuated during high frequency deep brain stimulation (HF DBS) in a patient with DYT3+ dystonia and in a patient with secondary dystonia due to childhood encephalitis., Materials and Methods: We recorded local field potentials from the DBS lead in the GPi of four patients (seven hemispheres) with secondary dystonia and from one patient (two hemispheres) with primary DYT3+ dystonia. In two patients, we also recorded pallidal local field potentials during the administration of 10 sec epochs of HF DBS., Results: Power spectral densities during rest demonstrated visible peaks in the beta band in seven out of nine cases. In DYT3+ dystonia, power in the alpha and beta bands, but not theta band, was attenuated during HF DBS in the GPe and in GPi, and attenuation was most prominent in the high beta band. This patient demonstrated an early and maintained improvement in dystonia. There was no beta peak and the power spectrum was not attenuated during HF DBS in a patient with secondary dystonia due to childhood encephalitis., Conclusions: These results suggest that beta hypersynchrony, demonstrated now in both primary and secondary dystonia, may play a pathophysiological role in pathological hyperkinesis. Further investigation is needed in a larger cohort of well-characterized primary and secondary dystonia patients., (© 2012 International Neuromodulation Society.)

High frequency deep brain stimulation is an effective therapy for motor symptoms in Parkinson's disease. However, the relative clinical efficacy of regular versus non-regular temporal patterns of stimulation in Parkinson's disease remains unclear. To determine the temporal characteristics of non-regular temporal patterns of stimulation important for the treatment of Parkinson's disease, we compared the efficacy of temporally regular stimulation with four non-regular patterns of stimulation in subjects with Parkinson's disease using an alternating finger tapping task. The patterns of stimulation were also evaluated in a biophysical model of the parkinsonian basal ganglia that exhibited prominent oscillatory activity in the beta frequency range. The temporal patterns of stimulation differentially improved motor task performance. Three of the non-regular patterns of stimulation improved performance of the finger tapping task more than temporally regular stimulation. In the computational model all patterns of deep brain stimulation suppressed beta band oscillatory activity, and the degree of suppression was strongly correlated with the clinical efficacy across stimulation patterns. The three non-regular patterns of stimulation that improved motor performance over regular stimulation also suppressed beta band oscillatory activity in the computational model more effectively than regular stimulation. These data demonstrate that the temporal pattern of stimulation is an important consideration for the clinical efficacy of deep brain stimulation in Parkinson's disease. Furthermore, non-regular patterns of stimulation may ameliorate motor symptoms and suppress pathological rhythmic activity in the basal ganglia more effectively than regular stimulation. Therefore, non-regular patterns of deep brain stimulation may have useful clinical and experimental applications., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Parkinson's disease (PD) is marked by excessive synchronous activity in the beta (8-35 Hz) band throughout the cortico-basal ganglia network. The optimal location of high frequency deep brain stimulation (HF DBS) within the subthalamic nucleus (STN) region and the location of maximal beta hypersynchrony are currently matters of debate. Additionally, the effect of STN HF DBS on neural synchrony in functionally connected regions of motor cortex is unknown and is of great interest. Scalp EEG studies demonstrated that stimulation of the STN can activate motor cortex antidromically, but the spatial specificity of this effect has not been examined. The present study examined the effect of STN HF DBS on neural synchrony within the cortico-basal ganglia network in patients with PD. We measured local field potentials dorsal to and within the STN of PD patients, and additionally in the motor cortex in a subset of these patients. We used diffusion tensor imaging (DTI) to guide the placement of subdural cortical surface electrodes over the DTI-identified origin of the hyperdirect pathway (HDP) between motor cortex and the STN. The results demonstrated that local beta power was attenuated during HF DBS both dorsal to and within the STN. The degree of attenuation was monotonic with increased DBS voltages in both locations, but this voltage-dependent effect was greater in the central STN than dorsal to the STN (p < 0.05). Cortical signals over the estimated origin of the HDP also demonstrated attenuation of beta hypersynchrony during DBS dorsal to or within STN, whereas signals from non-specific regions of motor cortex were not attenuated. The spatially-specific suppression of beta synchrony in the motor cortex support the hypothesis that DBS may treat Parkinsonism by reducing excessive synchrony in the functionally connected sensorimotor network.