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Konu: Physiology × WoS Q: Q1 ×

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  • Küçük Resim
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    Associations between cerebral perfusion pressure, hemodynamic parameters, and cognitive test values in normal-tension glaucoma patients, Alzheimer’s disease patients, and healthy controls
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-24) Stoskuviene, Akvile; Chaleckas, Edvinas; Grusauskiene, Evelina; Bartusis, Laimonas; Çelikkaya, Güven; Januleviciene, Ingrida; Vaitkus, Antanas; Ragauskas, Arminas; Hamarat, Yasin
    Background/Objectives: Glaucoma and Alzheimer’s disease (AD) are neurodegenerative conditions with vascular underpinnings. This study aimed to explore the relationship between blood pressure parameters such as mean arterial pressure (MAP), pulse pressure (PP), and cerebral perfusion pressure (CPP) and cognitive performance in patients with AD, normal-tension glaucoma (NTG), and healthy controls. We hypothesized that NTG patients, like those with mild cognitive impairment (MCI), may experience subtle cognitive changes related to vascular dysregulation. Methods: Ninety-eight participants (35 NTG, 17 AD, 46 controls) were assessed for CPP, MAP, OPP, and cognitive performance. Statistical analyses compared groups and examined correlations. Results: AD patients showed lower CPP and MAP (p < 0.001), indicating systemic vascular dysfunction, while NTG patients had higher ocular perfusion pressure (OPP) (p = 0.008), suggesting compensatory mechanisms. CPP correlated with visuospatial abilities in AD (r = 0.492, p = 0.045). MAP correlated with the Clock drawing test (CDT) scores in the NTG group (r = 0.378, p = 0.025). PP negatively correlated with cognition in AD (r = −0.527, p = 0.016 for CDT scores) and controls (r = −0.440, p = 0.002 for verbal fluency and r = −0.348, p = 0.019 for total ACE scores). Conclusions: The study highlights distinct hemodynamic profiles: systemic dysfunction in AD and localized dysregulation in NTG. These findings emphasize the role of vascular dysregulation in neurodegeneration, with implications for personalized treatment approaches targeting vascular health in neurodegenerative conditions.
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    Theta and Beta1 frequency band values predict dyslexia classification
    (John Wiley and Sons Ltd, 2025-12-29) Eroğlu, Günet; Harb, Mhd Raja Abou
    Dyslexia, impacting children's reading skills, prompts families to seek cost-effective neurofeedback therapy solutions. Utilising machine learning, we identified predictive factors for dyslexia classification. Employing advanced techniques, we gathered 14-channel Quantitative Electroencephalography (QEEG) data from 200 participants, achieving 99.6% dyslexic classification accuracy through cross-validation. During validation, 48% of dyslexic children's sessions were consistently classified as normal, with a 95% confidence interval of 47.31 to 48.68. Focusing on individuals consistently diagnosed with dyslexia during therapy, we found that dyslexic individuals exhibited higher theta values and lower beta1 values compared to typically developing children. This study pioneers machine learning in predicting dyslexia classification factors, offering valuable insights for families considering neurofeedback therapy investment.