Parkinson's Disease

Anatomical Localization of Intracranial Electrodes Using Synthetic MRI Generated from Computed Tomography.

BACKGROUND AND OBJECTIVES: MRI and computed tomography (CT) are commonly combined to localize intracranial electrodes in deep brain stimulation (DBS). However, when MRI access is limited or unsafe, only CT may be available, which lacks the soft tissue contrast needed for accurate anatomical reference. SynthSR, a deep learning tool that generates synthetic T1-weighted MRI from CT, may address this ...

A task-aligned multimodal machine learning framework for studying working memory dysfunction in Parkinson's disease.

UNLABELLED: Cognitive impairment is one of the most functionally debilitating non-motor symptoms in Parkinson's disease (PD). Yet, current diagnostic and clinical practices rely heavily on subjective assessments and burdensome behavioral testing, which lack the temporal resolution to detect subtle deficits. While EEG and pupillometry offer promising non-invasive insights into cognitive processing,...

Imaging Biomarkers in Parkinson's Disease and Movement Disorders: Emerging Insights from Multimodal Neuroimaging.

This editorial introduces a special issue detailing the rapid evolution of multimodal neuroimaging biomarkers for Parkinson's disease (PD) and related...

Erjingwan Alleviates Parkinson's Disease via Activation of PPARA-Mediated Autophagy.

Parkinson's disease (PD) is characterized by progressive dopaminergic neuronal degeneration and neuroinflammation. Traditional Chinese medicine (TCM) ...

Data-driven rapid assessment of bridge responses under mixed traffic with restricted overloaded vehicles using machine learning.

For infrastructure and regional economic development, restricted overload vehicles (ROVs) are an indispensable part. These vehicles are typically of l...

Insulin like growth factor and cytokine signalling predict future cognitive impairment in Parkinson's disease.

Cognitive impairment is a common non-motor sym.ptom of neurodegenerative Parkinson's disease (PD). However, the onset and severity of cognitive impair...

Rational Molecular Design to Improve Digital Polymer Readout in Aerolysin-Based Nanopore Sequencing.

Nanopore sequencing is a promising method for decoding synthetic digital polymers, but translocation signals are often complex. This study examines th...

Clinical Validity of Wrist- and Trunk-Worn Sensor-Derived Data Models in Parkinson's Disease.

BACKGROUND: Clinical rating scales for Parkinson's disease (PD) have limitations in the accurate assessment of disease severity, which may obscure tre...

Data-driven trajectories of atrophy explain clinical heterogeneity across Lewy body diseases.

BACKGROUND: Lewy body diseases (LBD) collectively share α-synuclein Lewy pathology, yet present wide clinical heterogeneity, with overlapping motor an...

Patterns of iron deposition and classification in parkinsonian syndromes: a quantitative susceptibility mapping study.

Differential diagnosis of parkinsonian syndromes remains challenging because of overlapping clinical symptoms. We characterized brain iron deposition ...

Uncertainty-aware personalized estimation of Parkinson's disease severity from longitudinal speech.

Parkinson's disease (PD) is a progressive neurological disorder characterized by motor impairments whose severity is commonly assessed using the Unifi...

Toward the prevention of clinically manifest Parkinson's disease.

Parkinson's disease (PD) is the fastest growing neurological disorder worldwide and is projected to affect unprecedented numbers of individuals by 205...

Nonlinear neurodynamics of N2 sleep EEG predict outcomes of anterior nucleus of the thalamus deep brain stimulation in epilepsy: A pilot study.

OBJECTIVE: Anterior nucleus of the thalamus deep brain stimulation (ANT-DBS) is an effective therapeutic option for drug-resistant epilepsy (DRE); how...

Cortico-basal oscillations index naturalistic movements during deep brain stimulation.

The basal ganglia and sensorimotor cortex are essential nodes of a network that supports motor control. In Parkinson's disease, disruptions in this ne...

Automatic sleep staging and atonia detection in RBD using single-channel chin EMG.

Study ObjectivesThe diagnosis of rapid eye movement (REM) sleep behavior disorder (RBD) is of clinical interest, as there is a high rate of future con...

EEG-fMRI fusion-based source localization for the identification and mechanistic elucidation of paroxysmal kinesigenic dyskinesia.

UNLABELLED: Paroxysmal kinesigenic dyskinesia is a rare neurological disorder characterized by brief, recurrent motor attacks that significantly impai...

Leveraging machine learning with real-world data for hypothesis generation by identifying exposomic predictors in Parkinson's disease among farmers.

BackgroundMachine learning offers new avenues for complementing traditional epidemiological approaches by analyzing routinely collected, population-ba...

Integrative network pharmacology, transcriptomics, and molecular docking identify candidate Centella asiatica constituents and targets in neurodegenerative diseases.

BACKGROUND: Neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD), are progressive d...

A computational framework for fitting biophysical basal-ganglia network models, applied to Parkinsonian beta oscillations.

Objective.Fitting biophysically detailed spiking-network models to data is constrained by computational cost: simulating thousands of coupled conducta...

Integrative Analysis Reveals Interactions Between Gut Microbiota-Derived Metabolites and the Brain in Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder increasingly associated with gut microbiota alterations, yet the mechanisms by which microbia...