2 research outputs found

    A comprehensive review of the movement imaginary brain-computer interface methods: Challenges and future directions

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    Brain-computer interface (BCI) aims to translate human intention into a control output signal. In motor-imaginary (MI) BCI, the imagination of movement modifies the cortex brain activity. Such activities are then used in pattern recognition to identify certain movement classes. MI-BCI could be used to enhance the life quality of physically impaired subjects. Several challenges exist in MI-BCI, including selecting appropriate channels, usually linked with a suitable classifier choice. The entire procedure must be real time in practical applications. A variety of channel selection and classification methods were used for MI-BCI in the literature. Also, hybrid machine learning (ML) and deep learning (DL) methods were used in the literature. In this chapter, different channel selection, ML and DL methods, validation frameworks, and performance indices of EEG-based methods were investigated. Three hundred and twenty-two papers published between January 2000 and March 2021 were analyzed in this systematic review. Specific challenges and future directions were then provided.Peer ReviewedPostprint (author's final draft

    Optical Imaging Demonstrates Tissue-Specific Metabolic Perturbations in Mblac1 Knockout Mice

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    Objective: Metabolic changes have been extensively documented in neurodegenerative brain disorders, including Parkinson’s disease and Alzheimer’s disease (AD). Mutations in the C. elegans swip-10 gene result in dopamine (DA) dependent motor dysfunction accompanied by DA neuron degeneration. Recently, the putative human ortholog of swip-10 (MBLAC1) was implicated as a risk factor in AD, a disorder that, like PD, has been associated with mitochondrial dysfunction. Interestingly, the AD risk associated with MBLAC1 arises in subjects with cardiovascular morbidity, suggesting a broader functional insult arising from reduced MBLAC1 protein expression and one possibly linked to metabolic alterations. Methods: Our current studies, utilizing Mblac1 knockout (KO) mice, seek to determine whether mitochondrial respiration is affected in the peripheral tissues of these mice. We quantified the levels of mitochondrial coenzymes, NADH, FAD, and their redox ratio (NADH/FAD, RR) in livers and kidneys of wild-type (WT) mice and their homozygous KO littermates of males and females, using 3D optical cryo-imaging. Results: Compared to WT, the RR of livers from KO mice was significantly reduced, without an apparent sex effect, driven predominantly by significantly lower NADH levels. In contrast, no genotype and sex differences were observed in kidney samples. Serum analyses of WT and KO mice revealed significantly elevated glucose levels in young and aged KO adults and diminished cholesterol levels in the aged KOs, consistent with liver dysfunction. Discussion/Conclusion: As seen with C. elegans swip-10 mutants, loss of MBLAC1 protein results in metabolic changes that are not restricted to neural cells and are consistent with the presence of peripheral comorbidities accompanying neurodegenerative disease in cases where MBLAC1 expression changes impact risk
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