Motor speech and non-motor language endophenotypes of Parkinson’s disease

The characteristics and reproducibility of motor speech functional neuroimaging in healthy controls

Introduction

Functional magnetic resonance imaging (fMRI) can improve our understanding of neural processes subserving motor speech function. Yet its reproducibility remains unclear. This study aimed to evaluate the reproducibility of fMRI using a word repetition task across two time points.

Methods

Imaging data from 14 healthy controls were analysed using a multi-level general linear model.

Results

Significant activation was observed during the task in the right hemispheric cerebellar lobules IV-V, right putamen, and bilateral sensorimotor cortices. Activation between timepoints was found to be moderately reproducible across time in the cerebellum but not in other brain regions.

Discussion

Preliminary findings highlight the involvement of the cerebellum and connected cerebral regions during a motor speech task. More work is needed to determine the degree of reproducibility of speech fMRI before this could be used as a reliable marker of changes in brain activity.

Exploring Spectrogram-Based Audio Classification for Parkinson's Disease: A Study on Speech Classification and Qualitative Reliability Verification

Patients suffering from Parkinson's disease suffer from voice impairment. In this study, we introduce models to classify normal and Parkinson's patients using their speech. We used an AST (audio spectrogram transformer), a transformer-based speech classification model that has recently outperformed CNN-based models in many fields, and a CNN-based PSLA (pretraining, sampling, labeling, and aggregation), a high-performance model in the existing speech classification field, for the study. This study compares and analyzes the models from both quantitative and qualitative perspectives. First, qualitatively, PSLA outperformed AST by more than 4% in accuracy, and the AUC was also higher, with 94.16% for AST and 97.43% for PSLA. Furthermore, we qualitatively evaluated the ability of the models to capture the acoustic features of Parkinson's through various CAM (class activation map)-based XAI (eXplainable AI) models such as GradCAM and EigenCAM. Based on PSLA, we found that the model focuses well on the muffled frequency band of Parkinson's speech, and the heatmap analysis of false positives and false negatives shows that the speech features are also visually represented when the model actually makes incorrect predictions. The contribution of this paper is that we not only found a suitable model for diagnosing Parkinson's through speech using two different types of models but also validated the predictions of the model in practice.

A bibliometric analysis of speech and language impairments in Parkinson's disease based on Web of Science

Many individuals with Parkinson's disease suffer from speech and language impairments that significantly impact their quality of life. Despite several studies on these disorders, there is a lack of relevant bibliometric analyses. This paper conducted a bibliometric analysis of 3,610 papers on speech and language impairments in Parkinson's disease patients from January 1961 to November 2023, based on the Web of Science Core Collection database. Using Citespace software, the analysis focused on annual publication volume, cooperation among countries and institutions, author collaborations, journals, co-citation references, and keywords, aiming to explore the current research status, hotspots, and frontiers in this field. The number of annual publications related to speech and language impairment in Parkinson's disease have been increasing over the years. The USA leads in the number of publications. Research hotspots include the mechanism underlying speech and language impairments, clinical symptoms, automated diagnosis and classification of patients with PD using linguistic makers, and rehabilitation interventions.

Optimizing Communication in Ataxia: A Multifaceted Approach to Alternative and Augmentative Communication (AAC)

The progression of multisystem neurodegenerative diseases such as ataxia significantly impacts speech and communication, necessitating adaptive clinical care strategies. With the deterioration of speech, Alternative and Augmentative Communication (AAC) can play an ever increasing role in daily life for individuals with ataxia. This review describes the spectrum of AAC resources available, ranging from unaided gestures and sign language to high-tech solutions like speech-generating devices (SGDs) and eye-tracking technology. Despite the availability of various AAC tools, their efficacy is often compromised by the physical limitations inherent in ataxia, including upper limb ataxia and visual disturbances. Traditional speech-to-text algorithms and eye gaze technology face challenges in accuracy and efficiency due to the atypical speech and movement patterns associated with the disease.In addressing these challenges, maintaining existing speech abilities through rehabilitation is prioritized, complemented by advances in digital therapeutics to provide home-based treatments. Simultaneously, projects incorporating AI driven solutions aim to enhance the intelligibility of dysarthric speech through improved speech-to-text accuracy.This review discusses the complex needs assessment for AAC in ataxia, emphasizing the dynamic nature of the disease and the importance of regular reassessment to tailor communication strategies to the changing abilities of the individual. It also highlights the necessity of multidisciplinary involvement for effective AAC assessment and intervention. The future of AAC looks promising with developments in brain-computer interfaces and the potential of voice banking, although their application in ataxia requires further exploration.

Systematic Review and Meta-Analyses of Word Production Abilities in Dysfunction of the Basal Ganglia: Stroke, Small Vessel Disease, Parkinson's Disease, and Huntington's Disease

Clinical populations with basal ganglia pathologies may present with language production impairments, which are often described in combination with comprehension measures or attributed to motor, memory, or processing-speed problems. In this systematic review and meta-analysis, we studied word production in four (vascular and non-vascular) pathologies of the basal ganglia: stroke affecting the basal ganglia, small vessel disease, Parkinson's disease, and Huntington's disease. We compared scores of these clinical populations with those of matched cognitively unimpaired adults on four well-established production tasks, namely picture naming, category fluency, letter fluency, and past-tense verb inflection. We conducted a systematic search in PubMed and PsycINFO with terms for basal ganglia structures, basal ganglia disorders and language production tasks. A total of 114 studies were included, containing results for one or more of the tasks of interest. For each pathology and task combination, effect sizes (Hedges' g) were extracted comparing patient versus control groups. For all four populations, performance was consistently worse than that of cognitively unimpaired adults across the four language production tasks (p-values < 0.010). Given that performance in picture naming and verb inflection across all pathologies was quantified in terms of accuracy, our results suggest that production impairments cannot be fully explained by motor or processing-speed deficits. Our review shows that while language production difficulties in these clinical populations are not negligible, more evidence is necessary to determine the exact mechanism that leads to these deficits and whether this mechanism is the same across different pathologies.

ParkinSong Online: Feasibility of Telehealth Delivery and Remote Data Collection for a Therapeutic Group Singing Study in Parkinson's

BACKGROUND

Parkinson's disease can negatively affect vocal functioning and social wellbeing, particularly in the latter stages of disease progression. Face-to-face group singing interventions can improve communication and wellbeing outcomes, yet not all people can access in-person sessions. To help overcome barriers to participation, exploration of the feasibility and utility of online therapeutic singing programs is needed.

OBJECTIVES

To evaluate the feasibility, acceptability, and preliminary efficacy of a 12-week ParkinSong Online intervention on speech and wellbeing for people with Parkinson's disease.

METHODS

A total of 28 participants with idiopathic Parkinson's disease were recruited to a single-arm feasibility study. Weekly 90-minute online sessions were co-facilitated by a music therapist and speech pathologist. Speech and wellbeing assessments were conducted pre and post intervention. Participant and facilitator surveys were administered after each session, with focus group interviews at the end of the program.

RESULTS

The recruitment rate was high (90%) with no attrition, adverse events, or safety issues. There was good intervention fidelity, attendance (average 89%), and positive participant experience. Feasibility was good, with technology reported as the main challenge (connecting and navigating Zoom). No improvements were seen in voice measures or wellbeing outcomes in this small trial. The online format used in this study did not provide the same benefits as in-person ParkinSong sessions.

CONCLUSIONS

ParkinSong Online is feasible for recreational purposes and social engagement provided that people have adequate technological knowledge or support. The optimal online delivery format to achieve communication improvements in Parkinson's awaits confirmation.

Towards interpretable speech biomarkers: exploring MFCCs

While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical interpretability. As an example, Mel frequency cepstral coefficients (MFCCs) have been identified in several studies as a useful marker of disease, but are regarded as uninterpretable. Here we explore correlations between MFCC coefficients and more interpretable speech biomarkers. In particular we quantify the MFCC2 endpoint, which can be interpreted as a weighted ratio of low- to high-frequency energy, a concept which has been previously linked to disease-induced voice changes. By exploring MFCC2 in several datasets, we show how its sensitivity to disease can be increased by adjusting computation parameters.

Bridging the Gap: Association between Objective and Subjective Outcomes of Communication Performance in People with Parkinson's Disease Evaluated for Deep Brain Stimulation

Background

Decrements in verbal fluency following deep brain stimulation (DBS) in people with Parkinson's disease (PwP) are common. As such, verbal fluency tasks are used in assessing DBS candidacy and target selection. However, the correspondence between testing performance and the patient's perception of communication abilities is not well-established.

Methods

The Communication Participation Item Bank (CPIB) was administered to 85 PwP during pre-DBS neuropsychological evaluations. Central tendencies for CPIB responses and correlations between CPIB total scores, clinical and demographic factors, and language-based tasks were examined.

Results

Most PwP indicated some degree of communication interference on the CPIB. Worse scores on semantic fluency and greater motor impairment were associated with more communication interference.

Conclusions

Our findings suggest an incomplete correspondence between commonly used language-based tests and patient-reported outcomes of communication abilities. The need for a functional communication instrument that reflects the different aspects of communication abilities in functional contexts is emphasized.

Self-perceived affective, behavioral, and cognitive reactions associated with voice use in people with Parkinson's disease: a pilot study

PURPOSE

This study aimed to compare the affective, behavioral, and cognitive reactions related to vocal function in people with Parkinson's disease (PWPD) and healthy controls using the Behavior Assessment Battery - Voice (BAB-Voice). The test's internal consistency was also described.

METHODS

31 PWPD and 19 healthy controls were recruited from September 2020 to March 2021. Participants completed four BAB-Voice subtests: Speech Situation Checklist - Emotional Reaction (SSC-ER), the Speech Situation Checklist - Speech Disruption (SSC-SD), Behavior Checklist (BCL), and Communication Attitude Test for Adults (BigCAT), describing the experienced negative emotional reaction, voice disruptions, coping behaviors, and negative attitude regarding communication respectively. Subtest scores were calculated and analyzed.

RESULTS

The scores of the PWPD were significantly different from those of the controls (Pillai's Trace = 0.344, F[4] = 5.508, p = .001, ηp2 = .344): PWPD showed more negative emotions and voice problems, more coping behaviors, and more negative speech-related attitude compared to healthy controls. All subtests showed excellent internal consistency.

CONCLUSIONS

The BAB-Voice proved a tool with a good internal consistency that measured different psychosocial reactions in PWPD versus controls. PWPD exhibited significantly more negative emotions and voice problems in specific speech situations, more coping behaviors, and a more negative speech-related attitude. The specificity of information obtained from the BAB-Voice may aid in improving the treatment planning of voice disorders in PWPD.

Disease Delineation for Multiple Sclerosis, Friedreich Ataxia, and Healthy Controls Using Supervised Machine Learning on Speech Acoustics

Neurodegenerative disease often affects speech. Speech acoustics can be used as objective clinical markers of pathology. Previous investigations of pathological speech have primarily compared controls with one specific condition and excluded comorbidities. We broaden the utility of speech markers by examining how multiple acoustic features can delineate diseases. We used supervised machine learning with gradient boosting (CatBoost) to delineate healthy speech from speech of people with multiple sclerosis or Friedreich ataxia. Participants performed a diadochokinetic task where they repeated alternating syllables. We subjected 74 spectral and temporal prosodic features from the speech recordings to machine learning. Results showed that Friedreich ataxia, multiple sclerosis and healthy controls were all identified with high accuracy (over 82%). Twenty-one acoustic features were strong markers of neurodegenerative diseases, falling under the categories of spectral qualia, spectral power, and speech rate. We demonstrated that speech markers can delineate neurodegenerative diseases and distinguish healthy speech from pathological speech with high accuracy. Findings emphasize the importance of examining speech outcomes when assessing indicators of neurodegenerative disease. We propose large-scale initiatives to broaden the scope for differentiating other neurological diseases and affective disorders.

Intelligibility of speech in Parkinson's disease relies on anatomically segregated subthalamic beta oscillations

BACKGROUND

Speech impairment is commonly reported in Parkinson's disease and is not consistently improved by available therapies - including deep brain stimulation of the subthalamic nucleus (STN-DBS), which can worsen communication performance in some patients. Improving the outcome of STN-DBS on speech is difficult due to our incomplete understanding of the contribution of the STN to fluent speaking.

OBJECTIVE

To assess the relationship between subthalamic neural activity and speech production and intelligibility.

METHODS

We investigated bilateral STN local field potentials (LFPs) in nine parkinsonian patients chronically implanted with DBS during overt reading. LFP spectral features were correlated with clinical scores and measures of speech intelligibility.

RESULTS

Overt reading was associated with increased beta-low ([1220) Hz) power in the left STN, whereas speech intelligibility correlated positively with beta-high ([2030) Hz) power in the right STN.

CONCLUSION

We identified separate contributions from frequency and brain lateralization of the STN in the execution of an overt reading motor task and its intelligibility. This subcortical organization could be exploited for new adaptive stimulation strategies capable of identifying the occurrence of speaking behavior and facilitating its functional execution.

Optimising verbal fluency analysis in neurological patients with dysarthria: examples from Parkinson's disease and hereditary ataxia

BACKGROUND

Verbal fluency tests (VFTs) are widely used to assess cognitive-linguistic performance in neurological diseases. However, the influence of dysarthria on performance in tests requiring oral responses is unclear in ataxia and Parkinson's disease.

OBJECTIVES

To determine the impact of dysarthria on VFT performance and evaluate the validity and reliability of alternative methods for analyzing VFT data.

METHOD

Trained raters evaluated dysarthria using VFT recordings in people with ataxia (N = 61) or Parkinson's disease (PD; N = 69). Total Correct Items scores and qualitative parameters (intrusions, ambiguous verbalizations, perseverations, and interjections) were compared across semantic, phonemic, and alternating fluency tasks. Disease severity was considered as a covariate in the regression model.

RESULTS

VFT dysarthria ratings correlated with the benchmark (ground truth) dysarthria scores derived from a monologue. Ambiguous responses resulting from unclear speech impeded the rater's ability to determine if a response was correct. Regression analysis indicated that more severe dysarthria ratings predicted diminished scores in all three tasks (semantic fluency, phonemic fluency and alternating fluency) in the ataxia group. The contribution of disease severity to semantic, phonemic and alternating fluency was reduced substantially in the ataxia group after accounting for dysarthria severity in the model in both groups.

CONCLUSIONS

Dysarthria severity can be estimated based on speech samples derived from VFT. Dysarthria can lead to lower total correct items and is associated with more ambiguous verbalizations in VFT. Dysarthria severity should be considered when interpreting VFT performance in common movement disorders.

Effects of Music-Based Interventions on Motor and Non-Motor Symptoms in Patients with Parkinson's Disease: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis examined previous studies on music-based interventions for individuals with Parkinson’s disease (PD). The effectiveness of the interventions on various motor and non-motor outcomes was evaluated. This review was conducted by searching PubMed, CINAHL, PsycINFO, and Cochrane Library CENTRAL prior to June 2022 for randomized controlled trial (RCT) and controlled clinical trial (CCT) studies published in English. Data were expressed as weighted/standardized mean difference (MD/SMD) with 95% confidence intervals (CI). I2 index was used for heterogeneity. The initial search identified 745 studies, and 13 studies involving 417 participants with PD which met the inclusion criteria included in this review. The results of the meta-analysis revealed that music-based interventions can significantly improve walking velocity (MD = 0.12, 95% CI = 0.07~0.16, p < 0.00001), stride length (MD = 0.04, 95% CI = 0.02~0.07, p = 0.002), and mobility (MD = −1.05, 95% CI = −1.53~−0.57, p < 0.0001). However, the results did not support significant effects for music-based interventions on cadence (MD = 3.21, 95% CI = −4.15~10.57, p = 0.39), cognitive flexibility (MD = 20.91, 95% CI = −10.62~52.44, p = 0.19), inhibition (SMD = 0.07, 95% CI = −0.40~0.55, p = 0.76), and quality of life (SMD = −0.68, 95% CI= −1.68~0.32, p = 0.18). The findings suggest that music-based interventions are effective for the improvement of some motor symptoms, but evidence for non-motor symptoms is limited. Further high-quality studies with a larger sample size are required to obtain the robust effects of music-based interventions on various outcomes among patients with PD.

On the Relationship between Speech Intelligibility and Fluency Indicators among English-Speaking Individuals with Parkinson’s Diseases

The purpose of the study is to investigate how much of variance in Parkinson's Disease (PD) individuals' speech intelligibility could be predicted by seven speech fluency indicators (i.e., repetition, omission, distortion, correction, unfilled pauses, filled pauses, and speaking rate). Speech data were retrieved from a database containing a reading task produced by a group of 16 English-speaking individuals with PD (Jaeger, Trivedi & Stadtchnitzer, 2019). The results from a multiple regression indicated that an addition of 54% of variance in the speech intelligibility scores among individuals with PD could be accounted for after the speakers' PD severity level measured based on Hoehn and Yahr's (1967) disease stage was included as a covariate. In addition, omission and correction were the two fluency indicators that contributed to the general intelligibility score in a statistically significant way. Specifically, for every one-unit gain in the number of correction and omission, speech intelligibility scores would decline by 0.687 and 0.131 point (out of a 7-point scale), respectively. The current study hence supported Magee, Copland, and Vogel's (2019) view that the language production abilities and quantified dysarthria measures among individuals with PD should be explored together. Additionally, the clinical implications based on the current findings were discussed.

Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson's disease

Digital health technologies enable remote and therefore frequent measurement of motor signs, potentially providing reliable and valid estimates of motor sign severity and progression in Parkinson’s disease (PD). The Roche PD Mobile Application v2 was developed to measure bradykinesia, bradyphrenia and speech, tremor, gait and balance. It comprises 10 smartphone active tests (with ½ tests administered daily), as well as daily passive monitoring via a smartphone and smartwatch. It was studied in 316 early-stage PD participants who performed daily active tests at home then carried a smartphone and wore a smartwatch throughout the day for passive monitoring (study NCT03100149). Here, we report baseline data. Adherence was excellent (96.29%). All pre-specified sensor features exhibited good-to-excellent test–retest reliability (median intraclass correlation coefficient = 0.9), and correlated with corresponding Movement Disorder Society–Unified Parkinson's Disease Rating Scale items (rho: 0.12–0.71). These findings demonstrate the preliminary reliability and validity of remote at-home quantification of motor sign severity with the Roche PD Mobile Application v2 in individuals with early PD.

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

Feasibility of a Telerehabilitation Adaptation of the Be Clear Speech Treatment Program for Non-Progressive Dysarthria

This study evaluated the feasibility and outcomes of a telerehabilitation adaptation of the Be Clear speech treatment program for adults with non-progressive dysarthria to determine clinical delivery viability and future research directions. Treatment effects on speech clarity, intelligibility, communication effectiveness, and participation, as well as psychosocial outcomes in 15 participants with non-progressive dysarthria, were explored. Intervention involved daily 1-h online sessions (4 days per week for 4 weeks, totalling 16 sessions) and daily home practice. Outcome measures were obtained at baseline (PRE), post-treatment (POST), and 12 weeks following treatment (FUP). Feasibility measures targeting participant satisfaction, treatment adherence and fidelity, and technical viability were also employed. The programme was feasible concerning technical viability and implementation, treatment adherence and fidelity. High levels of participant satisfaction were reported. Increases in overall ratings of communication participation and effectiveness were identified at POST and FUP. Reductions in speech rate were identified at FUP. Improvements in aspects of lingual and laryngeal function were also noted after treatment. Over time, improvements relating to the negative impact of dysarthria were identified. Naïve listeners perceived negligible changes in speech clarity following treatment. Online delivery of the Be Clear speech treatment program was feasible, and some positive speech benefits were observed. Due to the small sample size included in this research, statistically significant findings related to speech outcomes must be interpreted with caution. An adequately powered randomised controlled trial of Be Clear online is warranted to evaluate treatment efficacy.

ParkinSong Online: protocol for a telehealth feasibility study of therapeutic group singing for people with Parkinson's disease

INTRODUCTION

Parkinson's disease can be associated with speech deterioration and low communication confidence which in turn compromises social interaction. Therapeutic singing is an engaging method for combatting speech decline; however, face-to-face delivery can limit access to group singing. The aim of this study is to test the feasibility and acceptability of an online mode of delivery for a Parkinson's singing intervention (ParkinSong) as well as remote data collection procedures.

METHODS AND ANALYSIS

This ParkinSong Online feasibility trial is a single-arm, pre-post study of online singing delivery and remote data collection for 30 people living with Parkinson's. The primary outcome measure is feasibility: recruitment, retention, attendance, safety, intervention fidelity, acceptability and associated costs. Secondary outcomes are speech (loudness, intelligibility, quality, communication-related quality of life) and wellbeing (apathy, depression, anxiety, stress, health-related quality of life). This mode of delivery aims to increase the accessibility of singing interventions.

ETHICS AND DISSEMINATION

Ethics approval was obtained from The University of Melbourne Human Research Ethics Committee (2021-14465-16053-3) and the trial has been prospectively registered. Results will be presented at national and international conferences, published in a peer-reviewed journal, and disseminated to the Parkinson's community, researchers and policymakers.

TRIAL REGISTRATION NUMBER

ACTRN12621000940875.

Consonantal Landmarks as Predictors of Dysarthria among English-Speaking Adults with Cerebral Palsy

The current study explored the possibility that the consonantal landmarks served as predictors of dysarthric speech produced by English-speaking adults with cerebral palsy (CP). Additionally, the relationship between the perceptual severity of dysarthric speech and the consonantal landmarks was explored. The analyses included 210 sentences from the TORGO database produced by seven English-speaking CP speakers with dysarthria and seven typically developing controls matched in age and gender. The results indicated that the clinical group produced more total landmark features than did the control group. A binominal regression analysis revealed that the improper control of laryngeal vibration and the inability to tactically control the energy in a voiced segment would lead to the higher likelihood of dysarthric speech. A multinominal regression analysis revealed that producing too many +v and −v landmark features would lead to higher perceptual severity levels among the CP speakers. Together with literature, the current study proposed that the landmark-based acoustic analysis could quantify the differences in consonantal productions between dysarthric and non-dysarthric speech and reflect the underlying speech motor deficits of the population in concern.

Cognitive Determinants of Dysarthria in Parkinson's Disease: An Automated Machine Learning Approach

BACKGROUND

Dysarthric symptoms in Parkinson's disease (PD) vary greatly across cohorts. Abundant research suggests that such heterogeneity could reflect subject-level and task-related cognitive factors. However, the interplay of these variables during motor speech remains underexplored, let alone by administering validated materials to carefully matched samples with varying cognitive profiles and combining automated tools with machine learning methods.

OBJECTIVE

We aimed to identify which speech dimensions best identify patients with PD in cognitively heterogeneous, cognitively preserved, and cognitively impaired groups through tasks with low (reading) and high (retelling) processing demands.

METHODS

We used support vector machines to analyze prosodic, articulatory, and phonemic identifiability features. Patient groups were compared with healthy control subjects and against each other in both tasks, using each measure separately and in combination.

RESULTS

Relative to control subjects, patients in cognitively heterogeneous and cognitively preserved groups were best discriminated by combined dysarthric signs during reading (accuracy = 84% and 80.2%). Conversely, patients with cognitive impairment were maximally discriminated from control subjects when considering phonemic identifiability during retelling (accuracy = 86.9%). This same pattern maximally distinguished between cognitively spared and impaired patients (accuracy = 72.1%). Also, cognitive (executive) symptom severity was predicted by prosody in cognitively preserved patients and by phonemic identifiability in cognitively heterogeneous and impaired groups. No measure predicted overall motor dysfunction in any group.

CONCLUSIONS

Predominant dysarthric symptoms appear to be best captured through undemanding tasks in cognitively heterogeneous and preserved cohorts and through cognitively loaded tasks in patients with cognitive impairment. Further applications of this framework could enhance dysarthria assessments in PD. © 2021 International Parkinson and Movement Disorder Society.

Stopwatch training improves cognitive functions in patients with Parkinson's disease

Parkinson's disease (PD) impairs various cognitive functions, including time perception. Dysfunctional time perception in PD is poorly understood, and no study has investigated the rehabilitation of time perception in patients with PD. We aimed to induce the recovery of time perception in PD patients and investigated the potential relationship between recovery and cognitive functions/domains other than time perception. Sixty patients with PD (27 females) and 20 healthy controls (10 females) were recruited. The participants underwent a feedback training protocol for 4 weeks to improve the accuracy of subjective spatial distance or time duration using a ruler or stopwatch, respectively. They participated in three tests at weekly intervals, each comprising 10 types of cognitive tasks and assessments. After duration feedback training for 1 month, performance on the Go/No-go task, Stroop task, and impulsivity assessment improved in patients with PD, while no effect was observed after distance feedback training. Additionally, the effect of training on duration production correlated with extended reaction time and improved accuracy in the Go/No-go and Stroop tasks. These findings suggest that time perception is functionally linked to inhibitory systems. If the feedback training protocol can modulate and maintain time perception, it may improve various cognitive/psychiatric functions in patients with PD. It may also be useful in the treatment of diseases other than PD that cause dysfunctions in temporal processing.

Insight into an unsupervised two-step sparse transfer learning algorithm for speech diagnosis of Parkinson's disease

Speech diagnosis of Parkinson’s disease (PD) as a non-invasive and simple diagnosis method is particularly worth exploring. However, the number of samples of speech-based PD is relatively small, and there exist discrepancies in the distribution between subjects. In order to solve the two problems, a novel unsupervised two-step sparse transfer learning is proposed in this paper to tackle with PD speech diagnosis. In the first step, convolution sparse coding with the coordinate selection of samples and features is designed to learn speech structure from the source domain to replenish sample information of the target domain. In the second step, joint local structure distribution alignment is designed to maintain the neighbor relationship between the respective samples of the training set and test set, and reduce the distribution difference between the two domains at the same time. Two representative public PD speech datasets and one real-world PD speech dataset were exploited to verify the proposed method on PD speech diagnosis. Experimental results demonstrate that each step of the proposed method has a positive effect on the PD speech classification results, and it also delivers superior performance over the existing relative methods.

The relationship between dorsal stream connections to the caudate and verbal fluency in Parkinson disease

Performance in verbal fluency tasks are widely used as a marker of cognitive impairment in Parkinson disease. However, the anatomical substrate of its impairment remains undetermined. Based on the dual-stream language model, we hypothesized cortical input to the subcortical circuitry would be a crucial determinant of fluency. We performed a retrospective study using individual whole-brain structural connectomes derived from 135 individuals with PD and assessed the relationship between white matter integrity and verbal fluency tasks. Controlling for multiple factors, including dysarthria, we observed higher integrity of dorsal stream-caudate connectivity was associated with better letter fluency. This preliminary study indicates the possible dissociation between dorsal and ventral stream connectivity and letter fluency in PD. In addition, it suggests a non-motor role of the frontostriatal fibers in letter fluency.

Perceptual Characterization of Voice Quality in Nonadvanced Stages of Parkinson's Disease

INTRODUCTION

Parkinson's disease (PD) is a neurodegenerative disorder that impacts motor and nonmotor systems, and consequently influences voice. In later stages of the disease, people with PD develop salient hypokinetic dysarthria. However, it is unclear how extensive the voice impairment is in the nonadvanced stages of PD. Therefore, the aim of the current research was to investigate the auditory-perceptual characteristics of voice in people with Parkinson's disease (PWPD) in nonadvanced stages.

METHODS

29 PWPD and 32 healthy older controls were recruited. For each participant, a recording of the sentence "We were away a year ago" was acquired. These recordings were evaluated by 2 licensed and experienced speech-language pathologists, who provided perceptual ratings of overall dysphonia severity, breathiness, roughness, and perceived age.

RESULTS

MANCOVA analysis showed that, when controlling for age and intensity, there was a significant effect of group (P = 0.001) on perceptual voice quality. PWPD were perceived to be significantly older, more breathy and more severely dysphonic than the older healthy controls. No differences were found for the perceived roughness.

CONCLUSIONS

The results suggest that perceptual features of hypokinetic dysarthria in voice, specifically breathiness, are present in nonadvanced stages of PWPD and may contribute to listener perceptions of speaker age. Moreover, the perceptual voice profiles in PWPD showed great variability, possibly reflecting the heterogeneity of disease impact on individuals. The results of this study may inform how research targets rehabilitation and maintenance of voice and laryngeal function in PWPD at nonadvanced stages.

Speech-based characterization of dopamine replacement therapy in people with Parkinson's disease

People with Parkinson's (PWP) disease are under constant tension with respect to their dopamine replacement therapy (DRT) regimen. Waiting too long between doses results in more prominent symptoms, loss of motor function, and greater risk of falling per step. Shortened pill cycles can lead to accelerated habituation and faster development of disabling dyskinesias. The Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is the gold standard for monitoring Parkinson's disease progression but requires a neurologist to administer and therefore is not an ideal instrument to continuously evaluate short-term disease fluctuations. We investigated the feasibility of using speech to detect changes in medication states, based on expectations of subtle changes in voice and content related to dopaminergic levels. We calculated acoustic and prosodic features for three speech tasks (picture description, reverse counting, and diadochokinetic rate) for 25 PWP, each evaluated "ON" and "OFF" DRT. Additionally, we generated semantic features for the picture description task. Classification of ON/OFF medication states using features generated from picture description, reverse counting and diadochokinetic rate tasks resulted in cross-validated accuracy rates of 0.89, 0.84, and 0.60, respectively. The most discriminating task was picture description which provided evidence that participants are more likely to use action words in ON than in OFF state. We also found that speech tempo was modified by DRT. Our results suggest that automatic speech assessment can capture changes associated with the DRT cycle. Given the ease of acquiring speech data, this method shows promise to remotely monitor DRT effects.