Dynamic neural states underpin bradykinesia severity in Parkinsons disease

Objective.Adaptive deep brain stimulation (aDBS) for Parkinson's disease is a recently-approved therapy that adjusts stimulation in response to neurophysiologic biomarkers of motor-symptom state. Most real-time implementations of aDBS rely on instantaneous, noise-susceptible classifiers that apply simple thresholds to neurophysiologic biomarkers. We examined whether incorporating temporal history through Bayesian state-space modeling improved motor-state classification compared to instantaneous discriminant classifiers.Approach. We analyzed naturalistic neural data from three patients with Parkinson's disease chronically implanted with investigational sensing-enabled DBS systems, recording from both the subthalamic nucleus (STN) and sensorimotor cortex. Biomarkers were extracted across multiple window lengths and labeled using wearable-derived bradykinesia and dyskinesia scores. Classifier behavior was evaluated using two biomarkers (cortical stimulation-entrained gamma and STN beta oscillations) across a factorial combination of two conditions: (1) instantaneous discriminant analysis vs Bayesian time-history modeling via hidden Markov models (HMMs), and (2) single Gaussian vs Gaussian mixture modeling of each motor state's biomarker distribution. Performance metrics includedF1 scores, accuracy, prediction smoothness, latency, and computational load.Main Results. Using entrained-gamma biomarkers, incorporating time history via HMMs significantly improved hyperkinetic-state detection (F1: +12.9 ± 1.8%; accuracy: +30.0 ± 2.7%; bothpadj< 0.001) with modest decreases in hypokinetic-state performance, yielding a net increase in averageF1 (+4.7 ± 0.9%,p< 0.001). HMMs also yielded smoother and more accurate predictions for a given latency compared to simply increasing the window length used to extract neurophysiologic biomarkers. Entrained-gamma biomarkers outperformed STN beta biomarkers across all classifiers (averageF1: +12.9% ± 0.5%,p< 0.001). All methods operated within sub-millisecond prediction times and demonstrated sublinear empirical computational scaling.Significance. Bayesian time-history modeling enhanced motor-state classification while preserving the low latency and computational efficiency required for real-time aDBS. These findings, derived from chronic at-home recordings, support the translational potential of Bayesian state-space models for next-generation aDBS systems.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder and the heterogeneity of early PD leads to interrater and intrarater variability in observation-based clinical assessment. Thus, objective monitoring of PD-induced motor abnormalities has attracted significant attention to manage disease progression. Here, we proposed a hierarchical architecture to reliably detect abnormal characteristics and comprehensively quantify the multisymptom severity in patients with PD. A novel wearable device was designed to measure motor features in 15 PD patients and 15 age-matched healthy subjects, while performing five types of motor tasks. The abnormality classes of multimodal measurements were recognized by hidden Markov models (HMMs) in the first layer of the proposed architecture, aiming at motivating the evaluation of specific motor manifestations. Subsequently, in the second layer, three single-symptom models differentiated PD motor characteristics from normal motion patterns and quantified the severity of cardinal PD symptoms in parallel. In order to further analyze the disease status, the multilevel severity quantification was fused in the third layer, where machine learning algorithms were adopted to develop a multisymptom severity score. The experimental results demonstrated that the quantification of three cardinal symptoms was highly accurate to distinguish PD patients from healthy controls. Furthermore, strong correlations were observed between the Unified PD Rating Scale (UPDRS) scores and the predicted subscores for tremor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${(R = 0.75,\;P = 1.40e - 3)}$ </tex-math></inline-formula> , bradykinesia <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${(R = 0.71,\;P = 2.80e - 3)}$ </tex-math></inline-formula> , and coordination impairments <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${(R = 0.69,\;P = 4.20e - 3)}$ </tex-math></inline-formula> , and the correlation coefficient can be enhanced to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${0.88}\,\,{(P = 1.26e - 5)}$ </tex-math></inline-formula> based on the fusion schemes. In conclusion, the proposed assessment architecture holds great promise to push forward the in-home monitoring of clinical manifestations, thus enabling the self-assessment of disease progression.

ObjectiveTo evaluate the cognitive function of Chinese patients with Parkinson's disease PD postsubthalamic nucleus deep brain stimulation (STN‐DBS).MethodsCognitive function was assessed by neuropsychological methods in PD patients. Twenty matched healthy persons served as normal controls. t test, analysis of variance, and chi‐square analysis were used to compare the difference among the groups. Reliable change index was utilized to analyze the changes in cognition from the individual level.Results(a) Improvement in motor function was significantly better after STN‐DBS (P < .01). (b) Notably, the increase error rates of implicit SRTT (serial reaction time task) was significantly higher after STN‐DBS as compared with the conservative therapy group (P = .03). (c) The decline of verbal fluency (explicit) was also significantly higher after STN‐DBS than that in the medication therapy group (P = .03). (d) In the explicit clock‐drawing test, scores had significantly improved after STN‐DBS (P = .04).ConclusionsSTN‐DBS as a neuromodulatory tool in the Chinese PD population not only improves motor symptoms but also cognitive function to a certain extent, such as the decline of executive function and verbal fluency. The explicit cognitive decline was significantly quicker than that in patients on medication therapy. The improvement of visiospatial function was also noted. Implicit memory impairment during the 1‐year follow‐up period was not observed.

Dopamine receptors are abundant along the central nigrostriatal tract and are expressed as 5 subtypes in two receptor families. In PD, compensatory changes in dopamine receptors emerge as a consequence of the loss of dopamine nerve terminals or dopaminergic pharmacotherapy. We performed a systematic review and meta-analysis of the available PET and single-photon emission computed tomography studies that have investigated dopamine receptors in PD, PSP and MSA. The inclusion criteria were studies including human PET or single-photon emission computed tomography imaging; dopamine receptor tracers (D1-like or D2-like) and idiopathic PD, PSP, or MSA patients compared with healthy controls. The 67 included D2-like studies had 1925 patients. Data were insufficient for an analysis of D1-like studies. PD patients had higher striatal binding early in the disease, but after a disease duration of 4.36 years, PD patients had lower binding values than healthy controls. Striatal D2R binding was highest in unmedicated early PD patients and in the striatum contralateral to the predominant motor symptoms. PSP and MSA-P patients had lower striatal D2R binding than PD patients (14.2% and 21.8%, respectively). There is initial upregulation of striatal D2Rs in PD, which downregulate on average 4 years after motor symptom onset, possibly because of agonist-induced effects. The consistent upregulation of D2Rs in the PD striatum contralateral to the predominant motor symptoms indicates that receptor changes are driven by neurodegeneration and loss of striatal neuropil. Both PSP and MSA patients have clearly lower striatal D2R binding values than PD patients, which offers an opportunity for differential diagnostics. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Altered somatosensory cortex neuronal activity in a rat model of Parkinson's disease and levodopa-induced dyskinesias

The central nervous system (CNS) plays an important role in regulation of human gait. Parkinson's disease (PD) is a common neurodegenerative disease that may cause neurophysiologic change in the CNS and as a result change the gait cycle duration (stride interval). This article used the Hidden Markov Model (HMM) with Gaussian Mixtures to separate the patients with PD from healthy subjects. The results showed that the performance of the HMM classifier in classifying the gait data corresponding to 16 healthy and 15 PD subjects is comparable to the results obtained from the least squares support vector machine (LS-SVM) classifier. In this study, the leave-one-out cross-validation method was used to evaluate the performance of each classifier. The HMM method could effectively separate the gait data in terms of stride interval obtained from healthy subjects and PD patients with an accuracy rate of 90.3 % . All in all, the results showed that the proposed method can be used for distinguishing PD patients from healthy subjects based on the gait data classification.

Deep brain stimulation (DBS) is the procedure of choice for Parkinson's disease (PD). It has been used in PD patients younger than 70 years because of better perceived intra- and postoperative outcomes than in patients 70 years or older. However, previous studies with limited follow-up have demonstrated benefits associated with the treatment of elderly patients. This study aims to evaluate the long-term outcomes in elderly PD patients treated with DBS in comparison with a younger population. PD patients treated with DBS at the authors' institution from 2008 to 2014 were divided into 2 groups: 1) elderly patients, defined as having an age at surgery ≥ 70 years, and 2) young patients, defined as those < 70 years at surgery. Functional and medical treatment outcomes were evaluated using the Unified Parkinson's Disease Rating Scale part III (UPDRS III), levodopa-equivalent daily dose (LEDD), number of daily doses, and number of anti-PD medications. Study outcomes were compared using univariate analyses, 1-sample paired t-tests, and 2-sample t-tests. A total of 151 patients were studied, of whom 24.5% were ≥ 70 years. The most common preoperative Hoehn and Yahr stages for both groups were 2 and 3. On average, elderly patients had more comorbidities at the time of surgery than their younger counterparts (1 vs 0, p = 0.0001) as well as a higher average LEDD (891 mg vs 665 mg, p = 0.008). Both groups experienced significant decreases in LEDD following surgery (elderly 331.38 mg, p = 0.0001; and young 108.6 mg, p = 0.0439), with a more significant decrease seen in elderly patients (young 108.6 mg vs elderly 331.38 mg, p = 0.0153). Elderly patients also experienced more significant reductions in daily doses (young 0.65 vs elderly 3.567, p = 0.0344). Both groups experienced significant improvements in motor function determined by reductions in UPDRS III scores (elderly 16.29 vs young 12.85, p < 0.0001); however, reductions in motor score between groups were not significant. Improvement in motor function was present for a mean follow-up of 3.383 years postsurgery for the young group and 3.51 years for the elderly group. The average follow-up was 40.6 months in the young group and 42.2 months in the elderly group. This study found long-term improvements in motor function and medication requirements in both elderly and young PD patients treated with DBS. These outcomes suggest that DBS can be successfully used in PD patients ≥ 70 years. Further studies will expand on these findings.

BackgroundEarly diagnosis is crucial for ensuring that patients with Parkinson disease (PD) receive timely treatment, which can improve their quality of life and prolong lifespan. Wearable sensors have emerged as promising tools for early PD diagnosis, offering noninvasive, continuous symptom monitoring.ObjectiveThis review aimed to evaluate how wearable sensors have been applied in early diagnosis of PD over the past decade, focusing on sensor types, methods, findings, and limitations.MethodsThe systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were sourced from PubMed, IEEE Xplore, Scopus, and Web of Science and screened based on predefined criteria. The inclusion criteria were as follows: (1) the study was observational or experimental, (2) wearable sensors were applied for the early diagnosis of PD, (3) participants were diagnosed with early-stage or prodromal PD, (4) the study included at least 10 participants with PD, and (5) the article was published between 2013 and 2023. Studies were excluded if they focused solely on treatment, rehabilitation, symptom monitoring, or nonwearable devices; lacked diagnostic clarity; were not published in English; or were not primary research articles. All the selected studies were assessed for quality using the Quality Assessment of Diagnostic Accuracy Studies-2, the quality assessment tool recommended by the Cochrane Collaboration.ResultsOverall, 1888 records were retrieved from the selected databases, with 1044 records remaining after duplicate removal. Following the screening of titles and abstracts, 949 ineligible records were excluded, leaving 95 articles for eligibility. Eventually, of the 1044 studies, 12 (1.12%) met the inclusion criteria, validating the feasibility of wearable sensors in the early diagnosis of PD. Most (10/12, 83%) were cross-sectional studies, with 1 longitudinal and 1 mixed-design study. Of the 12 studies, 4 (33%) focused on identification diagnosis, 2 (17%) addressed the staged diagnosis of PD, and 1 (8%) focused on the identification of specific symptoms. Of the 12 studies, 5 (42%) assessed the overall feasibility and performance of wearable sensors in early PD detection without targeting specific classification purposes. The main wearable sensors used were inertial measurement units (8/12, 67%) and accelerometers (4/12, 33%), which primarily captured motion-related data. While initial findings suggest that wearable sensors are feasible for early PD diagnosis, the evidence is still limited by small sample sizes and short study durations.ConclusionsWearable sensors show promise in supporting the early diagnosis of PD, particularly for motor symptoms monitoring. However, several limitations remain in validating and applying wearable sensors in clinical contexts, including cross-sectional designs and limited diagnostic standardization. More diverse studies are needed to further validate these findings and address existing shortcomings to better advance the use of wearable sensors in the early diagnosis of PD.Trial RegistrationPROSPERO CRD42024544198; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024544198

We evaluated the frequency and severity of excessive daytime sleepiness in an outpatient population with Parkinson's disease in comparison to age-matched controls and examined its relationship with antiparkinsonian drug therapy and sleep history. Increased daytime sleepiness and involuntary sleep episodes have been described in Parkinson's disease, but the etiology is not completely understood. The Epworth Sleepiness Scale (ESS), a validated questionnaire for daytime sleepiness, was prospectively administered to 99 consecutive outpatients with Parkinson's disease and 44 age-matched controls. In addition, a short sleep-screening questionnaire was used. The ESS revealed significantly increased daytime sleepiness in PD patients compared to controls (7.5 +/- 4.6 vs. 5.8 +/- 3.0, P = 0.013). The ESS score was abnormally high (10 or more) in 33 % of PD patients and 11.4% of controls (P = 0.001). ESS was not different between PD patients on levodopa monotherapy and those on levodopa and dopamine agonists, or between patients taking ergoline or non-ergoline dopamine agonists. In PD patients and in controls, sleepiness was significantly associated with reported heavy snoring. Increased daytime sleepiness is more frequent in patients with PD than in elderly controls. Similar to controls, increased daytime sleepiness in PD patients is correlated with heavy snoring.

Background:Due to the short half-life of levodopa, immediate-release carbidopa-levodopa (IR CD-LD) produces fluctuating LD concentrations, contributing to a risk of eventual motor complications. IPX066 was designed to rapidly attain therapeutic LD concentrations and maintain them to allow a dosing interval of ∼6 hours.Objective:To extensively analyze the dosing data collected in IPX066 studies during open-label conversions from IR CD-LD alone or with entacapone (CLE) and identify patterns relevant for managing conversion in the clinical setting.Methods:Patients had ≥2.5 hours/day of “off” time despite a stable IR or CLE regimen. Suggested initial dosing conversion tables based on prior LD daily dosage were provided.Results:Of 450 patients previously treated with IR CD-LD and 110 with CLE, 87.3% and 82.7% completed conversion to IPX066, respectively. At the end of conversion, average IPX066 LD daily dosages were higher than pre-conversion dosages, with a mean conversion ratio of 2.1±0.6 for IR CD-LD and 2.8±0.8 for CLE; >90% of patients took IPX066 3 or 4 times/day, compared with a median of 5 times/day at baseline in both studies. After conversion, daily “off” time significantly decreased, with no significant increase in troublesome dyskinesia. The most common adverse event reported during conversion was nausea, with an incidence of 5.3% for conversion from IR and 7.3% from CLE.Conclusions:Among PD patients with substantial “off” time, a majority were safely converted to IPX066. The sustained LD profile from the IPX066 formulation allowed an increase in LD dose accompanied by improved motor functions, without increased troublesome dyskinesia.

The aim of the present study was to examine the frequency of self-reported sleep problems and their associated factors in a large cohort of PD patients. PD patients and controls, recruited from 35 centers of Spain from the COPPADIS cohort were included in this cross-sectional study. Sleep problems were assessed by the Spanish version of the Parkinson's disease Sleep Scale version 1 (PDSS-1). An overall score below 82 or a score below 5 on at least 1 item was defined as sleep problems. The frequency of sleep problems was nearly double in PD patients compared to controls: 65.8% (448/681) vs 33.5% (65/206) (p < 0.0001). Mean total PDSS score was lower in PD patients than controls: 114.9 ± 28.8 vs 132.8 ± 16.3 (p < 0.0001). Quality of life (QoL) was worse in PD patients with sleep problems compared to those without: PDQ-39SI, 19.3 ± 14 vs 13 ± 11.6 (p < 0.0001); EUROHIS-QoL8, 3.7 ± 0.5 vs 3.9 ± 0.5 (p < 0.0001). Non-motor symptoms burden (NMSS; OR = 1.029; 95%CI 1.015-1.043; p < 0.0001) and impulse control behaviors (QUIP-RS; OR = 1.054; 95%CI 1.009-1.101; p = 0.018) were associated with sleep problems after adjustment for age, gender, disease duration, daily equivalent levodopa dose, H&Y, UPDRS-III, UPDRS-IV, PD-CRS, BDI-II, NPI, VAS-Pain, VAFS, FOGQ, and total number of non-antiparkinsonian treatments. Sleep problems were frequent in PD patients and were related to both a worse QoL and a greater non-motor symptoms burden in PD. These findings call for increased awareness of sleep problems in PD patients.

Retrospective analysis of diet and gut microbiota diversity and clinical pharmacology outcomes in patients with Parkinsonism syndrome

Quantification of wheezing by a sensor system consisting of a wearable wireless acoustic sensor and smartphone performing respiratory sound classification may contribute to the diagnosis, long-term control, and lowering treatment costs of asthma. In such battery-powered sensor system, compressive sensing (CS) was verified as a method for simultaneously cutting down power cost of signal acquisition, compression, and communication on the wearable sensor. Matching real-time CS reconstruction algorithms, such as orthogonal matching pursuit (OMP), have been demonstrated on the smartphone. However, their lossy performance limits the accuracy of wheeze detection from CS-recovered short-term Fourier spectra (STFT), when using existing respiratory sound classification algorithms. Thus, here we present a novel, robust algorithm tailored specifically for wheeze detection from the CS-recovered STFT. The proposed algorithm identifies occurrence and tracks multiple individual wheeze frequency lines using hidden Markov model. The algorithm yields 89.34% of sensitivity, 96.28% of specificity, and 94.91% of accuracy on Nyquist-rate sampled respiratory sounds STFT. It enables for less than 2% loss of classification accuracy when operating over STFT reconstructed by OMP, at the signal compression ratio of up to 4 $\times$ (classification from only 25% signal samples). It features execution speed comparable to referent algorithms, and offers good prospects for parallelism.

The increase in oscillations in beta-band (13–30 Hz) of the basal ganglia (BG) is a hallmark neural dynamic feature of Parkinson’s disease (PD). Physiological studies have shown that striatum microcircuits also play an important role in the pathogenesis of this disease, but the relevant biophysical mechanism still remains unclear. Based on the previous striatal inhibitory model, we propose an extended thalamic-basal ganglia model containing medium spine neurons (MSNs) and fast-spiking interneurons (FSIs). Using this model, we demonstrate here that decreasing M-current conductance of the MSNs results in beta oscillations in the striatum and is transmitted to the globus pallidus pars interna (GPi) neurons through direct and indirect channels. Spectral power of local field potential shows that increased inhibition of GPi and globus pallidus pars externa by striatum also causes oscillatory activity in beta-band of BG, and leads to the bursting oscillations of the GPi neurons. In addition, beta-band oscillations in GPi can emerge because of dopamine depletion. And also, gap junction (GJ) between FSIs regulates the peak activity of GPi neurons through the striatum. Especially, in the Parkinson’s state, removal of GJ can reduce the energy of the beta-band slightly. These results not only highlight the roles of the striatum in controlling but also provide new ideas for studying PD in the future.

BackgroundNotwithstanding the large improvement in motor function in Parkinson’s disease (PD) patients treated with deep brain stimulation (DBS), apathy may increase. Postoperative apathy cannot always be related to a dose reduction of dopaminergic medication and stimulation itself may play a role. ObjectiveWe studied whether apathy in DBS-treated PD patients could be a stimulation effect. MethodsIn 26 PD patients we acquired apathy scores before and >6 months after DBS of the subthalamic nucleus (STN). Magnetoencephalography recordings (ON and OFF stimulation) were performed ≥6 months after DBS placement. Change in apathy severity was correlated with (i) improvement in motor function and dose reduction of dopaminergic medication, (ii) stimulation location (merged MRI and CT-scans) and (iii) stimulation-related changes in functional connectivity of brain regions that have an alleged role in apathy. ResultsAverage apathy severity significantly increased after DBS (p < 0.001) and the number of patients considered apathetic increased from two to nine. Change in apathy severity did not correlate with improvement in motor function or dose reduction of dopaminergic medication. For the left hemisphere, increase in apathy was associated with a more dorsolateral stimulation location (p = 0.010). The increase in apathy severity correlated with a decrease in alpha1 functional connectivity of the dorsolateral prefrontal cortex (p = 0.006), but not with changes of the medial orbitofrontal or the anterior cingulate cortex. ConclusionsThe present observations suggest that apathy after STN-DBS is not necessarily related to dose reductions of dopaminergic medication, but may be an effect of the stimulation itself. This highlights the importance of determining optimal DBS settings based on both motor and non-motor symptoms.