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Spinocerebellar ataxia (SCA) is a group of hereditary neurological diseases caused by gene mutations leading to degenerative changes in the cerebellum, brainstem, and spinal cord. A key pathogenic mechanism of SCA is the repeated expansion of cytosine - adenine - guanine (CAG) trinucleotides in the coding region of specific genes. These repeated expansions are translated into abnormally large polyglutamine (PolyQ) tracts in proteins. These polyglutamine (PolyQ) tracts can cause changes in the excitability of the cerebral cortex in SCA patients. Quantitative electroencephalogram analysis (qEEG) is a modern type of electroencephalogram analysis that uses complex mathematical algorithms to process, transform, and analyze EEG signals, bringing new technologies for EEG signal feature extraction: specific frequency band and signal complexity analysis, connectivity analysis, and network analysis. It is sensitive to early neurodegenerative lesions. Using spectral analysis, nonlinear dynamics analysis, and functional connectivity analysis, we can explore the changes in cortical excitability and abnormal brain networks in SCA patients. Currently, the exploration of the quantitative electroencephalogram characteristics of SCA patients is still insufficient.
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60 participants in 2 patient groups
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