An interpretable model based on graph learning for diagnosis of Parkinson's disease with voice-related EEG.

Parkinson's disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained by the interpretable features and the stochastic nature of resting-state EEG. The present study proposes a novel and interpretable deep learning model, graph signal processing-graph convolutional networks (GSP-GCNs), using event-related EEG data obtained from a specific task involving vocal pitch regulation for PD diagnosis. By incorporating both local and global information from single-hop and multi-hop networks, our proposed GSP-GCNs models achieved an averaged classification accuracy of 90.2%, exhibiting a significant improvement of 9.5% over other deep learning models. Moreover, the interpretability analysis revealed discriminative distributions of large-scale EEG networks and topographic map of microstate MS5 learned by our models, primarily located in the left ventral premotor cortex, superior temporal gyrus, and Broca's area that are implicated in PD-related speech disorders, reflecting our GSP-GCN models' ability to provide interpretable insights identifying distinctive EEG biomarkers from large-scale networks. These findings demonstrate the potential of interpretable deep learning models coupled with voice-related EEG signals for distinguishing PD patients from healthy controls with accuracy and elucidating the underlying neurobiological mechanisms.

Continuous theta burst stimulation over right cerebellum for speech impairment in Parkinson's disease: study protocol for a randomized, sham-controlled, clinical trial.

Background: Speech impairment is a common symptom of Parkinson's disease (PD) that worsens with disease progression and affects communication and quality of life. Current pharmacological and surgical treatments for PD have inconsistent effects on speech impairment. The cerebellum is an essential part of sensorimotor network that regulates speech production and becomes dysfunctional in PD. Continuous theta-burst stimulation (cTBS) is a non-invasive brain stimulation technique that can modulate the cerebellum and its connections with other brain regions. Objective: To investigate whether cTBS over the right cerebellum coupled with speech-language therapy (SLT) can improve speech impairment in PD. Methods: In this randomized controlled trial (RCT), 40 patients with PD will be recruited and assigned to either an experimental group (EG) or a control group (CG). Both groups will receive 10 sessions of standard SLT. The EG will receive real cTBS over the right cerebellum, while the CG will receive sham stimulation. Blinded assessors will evaluate the treatment outcome at three time points: pre-intervention, post-intervention, and at a 12-week follow-up. The primary outcome measures are voice/speech quality and neurobehavioral parameters of auditory-vocal integration. The secondary outcome measures are cognitive function, quality of life, and functional connectivity determined by resting-state functional magnetic resonance imaging (fMRI). Significance: This trial will provide evidence for the efficacy and safety of cerebellar cTBS for the treatment of speech impairment in PD and shed light on the neural mechanism of this intervention. It will also have implications for other speech impairment attributed to cerebellar dysfunctions. Clinical trial registration: www.chictr.org.cn, identifier ChiCTR2100050543.

Photo-Fenton Process over an Fe-Free 3%-CuO/Sr0.76Ce0.16WO4 Photocatalyst under Simulated Sunlight.

Photo-Fenton is a promising photocatalytic technology that utilizes sunlight. Herein, an Fe-free 3%-CuO/Sr0.76Ce0.16WO4 photocatalyst was synthesized to apply simulated wastewater degradation via a photo-Fenton process under simulated sunlight. The photodegradation efficiency of RhB solution over the 3%-CuO/Sr0.76Ce0.16WO4 photocatalyst is 93.2% in the first 3 h; its photocatalytic efficiency remains at 91.6% even after three cycle experiments. The kinetic constant of the 3%-CuO/Sr0.76Ce0.16WO4 photocatalyst is 0.0127 min-1, which is 2.8-fold that of an intrinsic Sr0.76Ce0.16WO4 sample. The experiment of radical quenching revealed that the photogenerated electrons and holes are transferred to CuO to form hydroxyl radicals. Besides, the photocatalyst was characterized by scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), diffused reflectance spectroscopy (DRS), and X-ray photoelectron spectroscopy (XPS) measurements. It has some reference significance for the design of iron-free photocatalysts.

Neurobehavioral Effects of LSVT® LOUD on Auditory-Vocal Integration in Parkinson's Disease: A Preliminary Study.

Individuals with Parkinson's disease (PD) are impaired in auditory-vocal integration, characterized by abnormal compensatory responses to auditory feedback errors during self-monitoring of vocal production. The present study examined whether auditory feedback control of vocal pitch production in PD can benefit from Lee Silverman voice treatment (LSVT® LOUD), a high effort, intensive speech treatment for hypokinetic dysarthria in PD. Before and immediately after LSVT LOUD, 12 individuals with PD were instructed to produce sustained vowel sounds while hearing their voice unexpectedly pitch-shifted by -200 cents. Their vocal responses and event-related potentials (ERPs) to pitch perturbations were measured to assess the treatment outcomes. A group of 12 healthy controls were one-to-one pair matched by age, sex, and language. Individuals with PD exhibited abnormally enhanced vocal and ERP P2 responses to pitch perturbations relative to healthy controls. Successful treatment with LSVT LOUD, however, led to significantly smaller and faster vocal compensations that were accompanied by significantly larger P2 responses. Moreover, improved vocal loudness during passage reading was significantly correlated with reduced vocal compensations for pitch perturbations. These preliminary findings provide the first neurobehavioral evidence for beneficial effects of LSVT LOUD on impaired auditory-vocal integration associated with PD, which may be related to improved laryngeal motor functions and a top-down modulation of the speech motor network by LSVT LOUD.

Photocatalytic Reduction of Cr(VI) on a 3.0% Au/Sr0.70Ce0.20WO4 Photocatalyst.

Herein, a 3.0%-Au/Sr0.70Ce0.20WO4 sample was prepared for the photocatalytic reduction of the Cr2O7 2- ion. The photocatalyst was characterized by X-ray diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, and ultraviolet-visible diffuse reflectance spectra. The Sr0.70Ce0.20WO4 sample presented a photocatalytic reduction activity that is better than those of the Ce-doped sample and the intrinsic sample. Thereafter, different metal elements, Cu, Ag, Au, and Pt, were used as cocatalysts, which were loaded on the Sr0.70Ce0.20WO4 sample. The 3.0%-Au/Sr0.70Ce0.20WO4 photocatalyst showed optimal photocatalytic reduction activity in a 8 vol % methanol solution (pH = 7) under visible light irradiation. The kinetic constant of the optimal one is 0.0039 min-1, which is 1.86 times that of the Sr0.70Ce0.20WO4 sample. The photocatalyst is stable enough after a 24 h photocatalytic experiment.