相关论文: A hierarchical coding-window model of Parkinson's …
Deep brain stimulation (DBS) can alleviate the movement disorders like Parkinson's disease (PD). Indeed, it is known that aberrant beta (13-30Hz)oscillations and the loss of dopaminergic neurons in the basal ganglia-thalamus (BGTH) and…
The globus pallidus (GPe) of the basal ganglia has been underappreciated for decades due to poor understanding of its cells and circuits. The advent of molecular tools has sparked a resurgence in interest in the GPe. Here, we review a…
Parkinson's disease is a progressive neurodegenerative disorder affecting motor and non-motor functions, with speech impairments among its earliest symptoms. Speech impairments offer a valuable diagnostic opportunity, with machine learning…
Parkinson's disease (PD), characterized by its incurable nature, rapid progression, and severe disability, poses significant challenges to the lives of patients and their families. Given the aging population, the need for early detection of…
Spontaneous brain activity generically displays transient spatiotemporal coherent structures, which can selectively be affected in various neurological and psychiatric pathologies. Here we model the full brain's electroencephalographic…
Parkinson's disease (PD), a severe and progressive neurological illness, affects millions of individuals worldwide. For effective treatment and management of PD, an accurate and early diagnosis is crucial. This study presents a deep…
People with Parkinson's disease must be regularly monitored by their physician to observe how the disease is progressing and potentially adjust treatment plans to mitigate the symptoms. Monitoring the progression of the disease through a…
Parkinson's disease (PD) is a chronic neurodegenerative disease. Early diagnosis is essential to mitigate the progressive deterioration of patients' quality of life. The most characteristic motor symptoms are very mild in the early stages,…
This paper represents a groundbreaking advancement in Parkinson disease (PD) research by employing a novel machine learning framework to categorize PD into distinct subtypes and predict its progression. Utilizing a comprehensive dataset…
Computational models of neurodegeneration aim to emulate the evolving pattern of pathology in the brain during neurodegenerative disease, such as Alzheimer's disease. Previous studies have made specific choices on the mechanisms of…
Parkinson's disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0.1-1 %, and an annual incidence between 1.3-2.0/10000 inhabitants. The mean age at diagnosis of PD is 55 and…
This paper focuses on the detection of Parkinson's disease based on the analysis of a patient's gait. The growing popularity and success of Transformer networks in natural language processing and image recognition motivated us to develop a…
Neurodegenerative diseases are characterized by the accumulation of misfolded proteins and widespread disruptions in brain function. Computational modeling has advanced our understanding of these processes, but efforts have traditionally…
The pedunculopontine nucleus (PPN) is a heterogeneous brainstem locomotor hub implicated in Parkinson's disease and potentially relevant for its treatment. We propose single-compartment, conductance-based models for three classes of PPN…
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms. However, traditional diagnostic approaches may suffer from…
We seek to identify genes involved in Parkinson's Disease (PD) by combining information across different experiment types. Each experiment, taken individually, may contain too little information to distinguish some important genes from…
Longitudinal voice biomarkers provide a non-invasive source of information for monitoring Parkinson's disease progression, but their statistical analysis is difficult because repeated measurements from the same subject are correlated,…
Current diagnosis and prognosis for Parkinson's disease (PD) face formidable challenges due to the heterogeneous nature of the disease course, including that (i) the impairment severity varies hugely between patients, (ii) whether a symptom…
Parkinson's Disease (PD) is one of the most common types of neurological diseases caused by progressive degeneration of dopamin- ergic neurons in the brain. Even though there is no fixed cure for this neurodegenerative disease, earlier…
At present, the vast majority of human subjects with neurological disease are still diagnosed through in-person assessments and qualitative analysis of patient data. In this paper, we propose to use Topological Data Analysis (TDA) together…