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Abstract The 5-2-1 criteria was developed to facilitate the identification and referral of patients with Parkinson’s Disease (PD) inadequately controlled by oral medications. The criterion was not developed to screen patients with PD for device-aided therapy eligibility. The robust design and validation of the 5-2-1 criteria minimizes over or inappropriate referrals, and supports physicians in the timely identification of patients with PD who may warrant further evaluation for treatment optimization. This response letter clarifies concerns raised by Moes et al.

Abstract Introduction Deutetrabenazine is a vesicular monoamine transporter 2 inhibitor used to treat tardive dyskinesia (TD) and chorea associated with Huntington disease (HD). To enhance detection of safety signals across individual trials, integrated safety analyses of deutetrabenazine in TD and HD chorea were conducted. Methods For TD, safety data were integrated from two 12-week pivotal studies (ARM-TD and AIM-TD) and through week 15 of the open-label extension (OLE) study (RIM-TD). Data were analyzed by deutetrabenazine treatment group and placebo. For HD, safety data were integrated from the 12-week pivotal study (First-HD) and through week 15 of the OLE study (ARC-HD) for patients previously receiving placebo. Integrated deutetrabenazine data were compared with placebo from the pivotal study. Results For TD, deutetrabenazine (n = 384) was generally well tolerated compared with placebo (n = 130). Adverse event (AE) incidence was numerically higher in the response-driven deutetrabenazine vs the fixed-dose deutetrabenazine and placebo groups, respectively (any AE, 59.5% vs 44.4–50.0% and 53.8%; treatment-related AE, 38.1% vs 18.1–25.0% and 30.8%). Serious AEs were reported for 2.8–8.3% of patients in the deutetrabenazine groups and 6.9% in the placebo group. Common AEs (≥ 4%) included headache, somnolence, nausea, anxiety, fatigue, dry mouth, and diarrhea. AE incidence was higher during the titration vs maintenance periods. For HD, AE incidence was numerically higher with deutetrabenazine (n = 84) vs placebo (n = 45; any AE, 64.3% vs 60.0%; treatment-related AE, 38.1% vs 26.7%); serious AEs were reported for similar proportions for the deutetrabenazine and placebo groups, 2.4% and 2.2%, respectively. Common AEs (≥ 4%) included irritability, fall, depression, dry mouth, and fatigue. Conclusions Data from an integrated analysis of studies in TD and an integrated analysis of studies of chorea in HD showed that deutetrabenazine has a favorable safety profile and is well tolerated across indications. Trial Registration ClinicalTrials.gov identifiers, NCT02291861, NCT02195700, NCT01795859, NCT02198794, NCT01897896.

The Unified Parkinson’s Disease Rating Scale (UPDRS) is used to recognize patients with Parkinson’s disease (PD) and rate its severity. The rating is crucial for disease progression monitoring and treatment adjustment. This study aims to advance the capabilities of PD management by developing an innovative framework that integrates deep learning with wearable sensor technology to enhance the precision of UPDRS assessments. We introduce a series of deep learning models to estimate UPDRS Part III scores, utilizing motion data from wearable sensors. Our approach leverages a novel Multi-shared-task Self-supervised Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) framework that processes raw gyroscope signals and their spectrogram representations. This technique aims to refine the estimation accuracy of PD severity during naturalistic human activities. Utilizing 526 min of data from 24 PD patients engaged in everyday activities, our methodology demonstrates a strong correlation of 0.89 between estimated and clinically assessed UPDRS-III scores. This model outperforms the benchmark set by single and multichannel CNN, LSTM, and CNN-LSTM models and establishes a new standard in UPDRS-III score estimation for free-body movements compared to recent state-of-the-art methods. These results signify a substantial step forward in bioengineering applications for PD monitoring, providing a robust framework for reliable and continuous assessment of PD symptoms in daily living settings.

Abstract Background The burden of Parkinson’s disease (PD) worsens with disease progression. However, the lack of objective and uniform disease classification challenges our understanding of the incremental burden in patients with advanced Parkinson’s disease (APD) and suboptimal medication control. The 5–2-1 criteria was proposed by clinical consensus to identify patients with advancing PD. Our objective was to evaluate the screening accuracy and incremental clinical burden, healthcare resource utilization (HCRU), and humanistic burden in PD patients meeting the 5–2-1 screening criteria. Methods Data were drawn from the Adelphi Parkinson’s Disease Specific Program (DSP™), a multi-country point-in-time survey (2017–2020). People with PD who were naive to device-aided therapy and on oral PD therapy were included. Patients meeting the 5–2-1 screening criteria had one or more of the three clinical indicators of APD: (i) ≥5 doses of oral levodopa/day, OR (ii) “off” symptoms for ≥2 h of waking day, OR (iii) ≥1 h of troublesome dyskinesia. Clinician assessment of PD stage was used as the reference in this study. Clinical screening accuracy of the 5–2-1 criteria was assessed using area under the curve and multivariable logistic regression models. Incremental clinical, HCRU, and humanistic burden were assessed by known-group comparisons between 5 and 2-1-positive and negative patients. Results From the analytic sample (n = 4714), 33% of patients met the 5–2-1 screening criteria. Among physician-classified APD patients, 78.6% were 5–2-1 positive. Concordance between clinician judgment and 5–2-1 screening criteria was > 75%. 5–2-1-positive patients were nearly 7-times more likely to be classified as APD by physician judgment. Compared with the 5–2-1-negative group, 5–2-1-positive patients had significantly higher clinical, HCRU, and humanistic burden across all measures. In particular, 5–2-1-positive patients had 3.8-times more falls, 3.6-times higher annual hospitalization rate, and 3.4-times greater dissatisfaction with PD treatment. 5–2-1-positive patients also had significantly lower quality of life and worse caregiver burden. Conclusions 5–2-1 criteria demonstrated potential as a screening tool for identifying people with APD with considerable clinical, humanistic, and HCRU burden. The 5–2-1 screening criteria is an objective and reliable tool that may aid the timely identification and treatment optimization of patients inadequately controlled on oral PD medications.

Abstract Levodopa-induced dyskinesias are abnormal involuntary movements experienced by the majority of persons with Parkinson’s disease (PwP) at some point over the course of the disease. Choreiform as the most common phenomenology of levodopa-induced dyskinesias can be managed by adjusting the dose/frequency of PD medication(s) based on a PwP’s motor fluctuations over a typical day. We developed a sensor-based assessment system to provide such information. We used movement data collected from the upper and lower extremities of 15 PwPs along with a deep recurrent model to estimate dyskinesia severity as they perform different activities of daily living (ADL). Subjects performed a variety of ADLs during a 4-h period while their dyskinesia severity was rated by the movement disorder experts. The estimated dyskinesia severity scores from our model correlated highly with the expert-rated scores (r = 0.87 (p < 0.001)), which was higher than the performance of linear regression that is commonly used for dyskinesia estimation (r = 0.81 (p < 0.001)). Our model provided consistent performance at different ADLs with minimum r = 0.70 (during walking) to maximum r = 0.84 (drinking) in comparison to linear regression with r = 0.00 (walking) to r = 0.76 (cutting food). These findings suggest that when our model is applied to at-home sensor data, it can provide an accurate picture of changes of dyskinesia severity facilitating effective medication adjustments.

Abstract Background Unified Parkinson Disease Rating Scale-part III (UPDRS III) is part of the standard clinical examination performed to track the severity of Parkinson’s disease (PD) motor complications. Wearable technologies could be used to reduce the need for on-site clinical examinations of people with Parkinson’s disease (PwP) and provide a reliable and continuous estimation of the severity of PD at home. The reported estimation can be used to successfully adjust the dose and interval of PD medications. Methods We developed a novel algorithm for unobtrusive and continuous UPDRS-III estimation at home using two wearable inertial sensors mounted on the wrist and ankle. We used the ensemble of three deep-learning models to detect UPDRS-III-related patterns from a combination of hand-crafted features, raw temporal signals, and their time–frequency representation. Specifically, we used a dual-channel, Long Short-Term Memory (LSTM) for hand-crafted features, 1D Convolutional Neural Network (CNN)-LSTM for raw signals, and 2D CNN-LSTM for time–frequency data. We utilized transfer learning from activity recognition data and proposed a two-stage training for the CNN-LSTM networks to cope with the limited amount of data. Results The algorithm was evaluated on gyroscope data from 24 PwP as they performed different daily living activities. The estimated UPDRS-III scores had a correlation of $$0.79\, (\textit{p}

BackgroundPatient groups traditionally affected by health disparities were less likely to use video teleneurology (TN) care during the initial COVID-19 pandemic surge in the United States. Whether this asymmetry persisted later in the pandemic or was accompanied with a loss of access to care remains unknown.MethodsWe conducted a retrospective cohort study using patient data from a multicenter healthcare system in New York City. We identified all established pediatric or adult neurology patients with at least two prior outpatient visits between June 16th, 2019 and March 15th, 2020 using our electronic medical record. For this established pre-COVID cohort, we identified telephone, in-person, video TN or emergency department visits and hospital admissions for any cause between March 16th and December 15th, 2020 (“COVID period”). We determined clinical, sociodemographic, income, and visit characteristics. Our primary outcome was video TN utilization, and our main secondary outcome was loss to follow-up during the COVID period. We used multivariable logistic regression to model the relationship between patient-level characteristics and both outcomes.ResultsWe identified 23,714 unique visits during the COVID period, which corresponded to 14,170 established patients from our institutional Neurology clinics during the pre-COVID period. In our cohort, 4,944 (34.9%) utilized TN and 4,997 (35.3%) were entirely lost to follow-up during the COVID period. In the adjusted regression analysis, Black or African-American race [adjusted odds ratio (aOR) 0.60, 97.5%CI 0.52–0.70], non-English preferred language (aOR 0.49, 97.5%CI 0.39–0.61), Medicaid insurance (aOR 0.50, 97.5%CI 0.44–0.57), and Medicare insurance (aOR 0.73, 97.5%CI 0.65–0.83) had decreased odds of TN utilization. Older age (aOR 0.98, 97.5%CI 0.98–0.99), female sex (aOR 0.90 97.5%CI 0.83–0.99), and Medicaid insurance (aOR 0.78, 0.68–0.90) were associated with decreased odds of loss to follow-up.ConclusionIn the first 9 months of the COVID-19 pandemic, we found sociodemographic patterns in TN utilization that were similar to those found very early in the pandemic. However, these sociodemographic characteristics were not associated with loss to follow-up, suggesting that lack of TN utilization may not have coincided with loss of access to care.

BackgroundDeutetrabenazine is a vesicular monoamine transporter 2 inhibitor approved for the treatment of tardive dyskinesia (TD) in adults. In two 12-week pivotal studies, deutetrabenazine demonstrated statistically significant improvements in Abnormal Involuntary Movement Scale (AIMS) scores, with favorable safety/tolerability in TD patients. This study reports long-term efficacy and safety of deutetrabenazine in a 3-year, single-arm, open-label extension (OLE) study.MethodsPatients who completed the pivotal studies could enroll in this single-arm OLE study, titrating up to 48 mg/day based on dyskinesia control and tolerability. Efficacy was assessed based on change from baseline in total motor AIMS score, Clinical Global Impression of Change (CGIC) and Patient Global Impression of Change (PGIC), and quality of life (QOL) assessments. Safety evaluation included adverse event (AE) incidence, reported using exposure-adjusted incidence rates, and safety scales.Results343 patients enrolled in the study (6 patients were excluded). At Week 145 (mean dose: 39.4 ± 0.83 mg/day), mean ± SE change from baseline in total motor AIMS score was −6.6 ± 0.37 and 67% of patients achieved ≥50% improvement in total motor AIMS score. Based on CGIC and PGIC, 73% and 63% of patients achieved treatment success, respectively. QOL improvements were also observed. Deutetrabenazine was generally well tolerated, with low rates of mild-to-moderate AEs and no new safety signals; most safety scales remained unchanged over time.ConclusionsLong-term deutetrabenazine treatment was associated with sustained improvement in AIMS scores, indicative of clinically meaningful long-term benefit, and was generally well tolerated. Results suggest deutetrabenazine may provide increasing benefit over time without increases in dose.

Background: The efficacy of deep brain stimulation (DBS) therapy in Parkinson’s disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients’ symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent.Methods: Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline.Results: We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, n = 3 STNs). The selected tracks were characterized by higher activity in beta (11–32 Hz) and high-frequency (200–400 Hz) bands (p < 0.01) of LFPs and stronger non-linear coupling between these bands (p < 0.05).Conclusion: Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting.

Impulsivity and compulsivity are prominent non-motor problems in Parkinson’s disease (PD). Despite 20 years of research, there is still an ongoing debate as to whether subthalamic deep brain stimulation (STN DBS) for PD exacerbates or improves these symptoms. Here, we review how STN DBS affects clinical symptoms and neurocognitive aspects of impulsivity and compulsivity. When comparing patients post- to pre-surgery, in the majority of studies STN DBS for PD is associated with a decrease in clinically diagnosed impulse-control disorders and disorders of compulsivity. To avoid confounds, such as post-surgical decreases in dopaminergic medication doses, comparisons can also be made between DBS “On” versus “Off” conditions. These experimentally assayed effects of STN DBS with respect to neurocognitive aspects of impulsivity and compulsivity are more mixed. STN DBS improves behavioral flexibility without impairing negative feedback learning, delay discounting, or inhibitory control, as long as stimulation is restricted to the dorsal STN. However, STN DBS may drive impulsive actions when a subject is faced with competing choices. We discuss how motivated responses may be either enhanced or impaired by STN DBS depending on engagement of dorsal or ventral STN-mediated circuits. Future studies should combine structural and functional circuit measures with behavioral testing in PD patients on and off medication and stimulation. A more sophisticated understanding of how to modulate cortico-striatal-thalamo-cortical loops will increase the likelihood that these circuit manipulation techniques can successfully be applied to a wider range of neuropsychiatric disorders.

Single cell neuronal activity (SUA) and local field potentials (LFP) in the subthalamic nucleus (STN) of unmedicated Parkinson's disease (PD) patients undergoing deep brain stimulation (DBS) surgery have been well-characterized during microelectrode recordings (MER). However, there is limited knowledge about the changes in the firing patterns and oscillations above and within the territories of STN after the intake of dopaminergic medication. Here, for the first time, we report the STN single cell and oscillatory neural dynamics in a medicated patient with idiopathic PD using intraoperative MER. We recorded LFP and SUA with microelectrodes at various depths during bilateral STN-DBS electrode implantation. We isolated 26 neurons in total and observed that tonic and irregular firing patterns of individual neurons predominated throughout the territories of STN. While burst-type firings have been well-characterized in the dorsal territories of STN in unmedicated patients, interestingly, this activity was not observed in our medicated subject. LFP recordings lacked the excessive beta (8–30 Hz) activity, characteristic of the unmedicated state and signal energy was mainly dominated by slow oscillations below 8 Hz. We observed sharp gamma oscillations between 70 and 90 Hz within and above the STN. Despite the presence of a broadband high frequency activity in 200–400 Hz range, no cross-frequency interaction in the form of phase-amplitude coupling was noted between low and high frequency oscillations of LFPs. While our results are in agreement with the previously reported LFP recordings from the DBS lead in medicated PD patients, the sharp gamma peak present throughout the depth recordings and the lack of bursting firings after levodopa intake have not been reported before. The lack of bursting in SUA, the lack of excessive beta activity and cross frequency coupling between HFOs and lower rhythms further validate the link between bursting firing regime of neurons and pathological oscillatory neural activity in PD-STN. Overall, these observations not only validate the existing literature on the PD electrophysiology in healthy/medicated animal models but also provide insights regarding the underlying electro-pathophysiology of levodopa-induced dyskinesias in PD patients through demonstration of multiscale relationships between single cell firings and field potentials.

Obsessive compulsive disorder (OCD) is a common, disabling psychiatric disease characterized by persistent, intrusive thoughts and ritualistic, repetitive behaviors. Deep brain stimulation (DBS) is thought to alleviate OCD symptoms by modulating underlying disturbances in normal cortico-striato-thalamo-cortical (CSTC) circuitry. Stimulation of the ventral portion of the anterior limb of the internal capsule (ALIC) and underlying ventral striatum (“ventral capsule/ventral striatum” or “VC/VS” target) received U.S. FDA approval in 2009 for patients with severe, treatment-refractory OCD. Over the decades, DBS surgical outcome studies have led to an evolution in the electrical stimulation target. In parallel, advancements in neuroimaging techniques have allowed investigators to better visualize and define CSTC circuits underlying the pathophysiology of OCD. A critical analysis of these new data suggests that the therapeutic mechanism of DBS for OCD likely involves neuromodulation of a widespread cortical/subcortical network, accessible by targeting fiber bundles in the ventral ALIC that connect broad network regions. Future studies will include advances in structural and functional imaging, analysis of physiological recordings, and utilization of next-generation DBS devices. These tools will enable patient-specific optimization of DBS therapy, which will hopefully further improve outcomes.

The annual Deep Brain Stimulation (DBS) Think Tank provides a focal opportunity for a multidisciplinary ensemble of experts in the field of neuromodulation to discuss advancements and forthcoming opportunities and challenges in the field. The proceedings of the fifth Think Tank summarize progress in neuromodulation neurotechnology and techniques for the treatment of a range of neuropsychiatric conditions including Parkinson's disease, dystonia, essential tremor, Tourette syndrome, obsessive compulsive disorder, epilepsy and cognitive, and motor disorders. Each section of this overview of the meeting provides insight to the critical elements of discussion, current challenges, and identified future directions of scientific and technological development and application. The report addresses key issues in developing, and emphasizes major innovations that have occurred during the past year. Specifically, this year's meeting focused on technical developments in DBS, design considerations for DBS electrodes, improved sensors, neuronal signal processing, advancements in development and uses of responsive DBS (closed-loop systems), updates on National Institutes of Health and DARPA DBS programs of the BRAIN initiative, and neuroethical and policy issues arising in and from DBS research and applications in practice.

Tremor is one of the main symptoms of Parkinson’s Disease (PD) that reduces the quality of life. Tremor is measured as part of the Unified Parkinson Disease Rating Scale (UPDRS) part III. However, the assessment is based on onsite physical examinations and does not fully represent the patients’ tremor experience in their day-to-day life. Our objective in this paper was to develop algorithms that, combined with wearable sensors, can estimate total Parkinsonian tremor as the patients performed a variety of free body movements. We developed two methods: an ensemble model based on gradient tree boosting and a deep learning model based on long short-term memory (LSTM) networks. The developed methods were assessed on gyroscope sensor data from 24 PD subjects. Our analysis demonstrated that the method based on gradient tree boosting provided a high correlation (r = 0.96 using held-out testing and r = 0.93 using subject-based, leave-one-out cross-validation) between the estimated and clinically assessed tremor subscores in comparison to the LSTM-based method with a moderate correlation (r = 0.84 using held-out testing and r = 0.77 using subject-based, leave-one-out cross-validation). These results indicate that our approach holds great promise in providing a full spectrum of the patients’ tremor from continuous monitoring of the subjects’ movement in their natural environment.

The success of medication adjustment in Parkinson’s disease (PD) patients with motor fluctuation relies on the knowledge about their fluctuation severity. However, because of the temporal and spatial variability in motor fluctuations, a single clinical examination often fails to capture the spectrum of motor impairment experienced in routine daily life. In this study, we developed an algorithm to estimate the degree of motor fluctuation severity from two wearable sensors’ data during subjects’ free body movements. Specifically, we developed a new hybrid feature extraction method to represent the longitudinal changes of motor function from the sensor data. Next, we developed a classification model based on random forest to learn the changes in the patterns of the sensor data as the severity of the motor function changes. We evaluated our algorithm using data from 24 subjects with idiopathic PD as they performed a variety of daily routine activities. A leave-one-subject-out assessment of the algorithm resulted in 83.33% accuracy, indicating that our approach holds a great promise to passively detect degree of motor fluctuation severity from continuous monitoring of an individual’s free body movements. Such a sensor-based assessment system and algorithm combination could provide the objective and comprehensive information about the fluctuation severity that can be used by the treating physician to effectively adjust therapy for PD patients with troublesome motor fluctuation.

Background: Deutetrabenazine, an inhibitor of vesicular monoamine transporter type 2 (VMAT2) depletes presynaptic dopamine and is useful in the treatment of hyperkinetic movement disorders. This study explored the safety, tolerability, and preliminary efficacy of deutetrabenazine in adolescents with moderate-to-severe tics associated with Tourette syndrome (TS). Methods: In this open-label study of 12–18-year-old patients with TS-related tics, deutetrabenazine was titrated up to 36 mg/day over 6 weeks to adequately suppress tics without bothersome adverse effects (AEs), followed by maintenance at optimal dose for 2 weeks. An independent blinded rater assessed tic severity using the Yale Global Tic Severity Scale (YGTSS), which was the primary outcome measure. Secondary outcome measures included the TS Clinical Global Impression (TS-CGI) and TS Patient Global Impression of Change (TS-PGIC). Results: Twenty-three enrolled patients received deutetrabenazine and had at least 1 post-baseline YGTSS assessment. The mean (SD [standard deviation]) baseline YGTSS Total Tic Severity Score (TTS) was 31.6 (7.9) and had decreased by 11.6 (8.2) points at week 8, a 37.6% reduction in tic severity (p Discussion: The results of this open-label 8-week study suggest that deutetrabenazine is safe and associated with improvement in tic severity in adolescents with TS and troublesome tics.

This paper provides an overview of current progress in the technological advances and the use of deep brain stimulation (DBS) to treat neurological and neuropsychiatric disorders, as presented by participants of the Fourth Annual Deep Brain Stimulation Think Tank, which was convened in March 2016 in conjunction with the Center for Movement Disorders and Neurorestoration at the University of Florida, Gainesveille FL, USA. The Think Tank discussions first focused on policy and advocacy in DBS research and clinical practice, formation of registries, and issues involving the use of DBS in the treatment of Tourette Syndrome. Next, advances in the use of neuroimaging and electrochemical markers to enhance DBS specificity were addressed. Updates on ongoing use and developments of DBS for the treatment of Parkinson’s disease, essential tremor, Alzheimer’s disease, depression, post-traumatic stress disorder, obesity, addiction were presented, and progress toward innovation(s) in closed-loop applications were discussed. Each section of these proceedings provides updates and highlights of new information as presented at this year’s international Think Tank, with a view toward current and near future advancement of the field.

Background: Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson’s disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic. Methods: We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest. Results: In all PD patients, we noted excessive beta band activity (13-30Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200-400Hz, indicating the presence of beta-HFO CFC. In all 3 TS patients at rest, we observed theta band activity (4-7Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200-400Hz) and gamma band (35-200Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5-10Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects. Conclusions: To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5-10Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present.