کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6810177 | 1433603 | 2011 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Brain ERP components predict which individuals progress to Alzheimer's disease and which do not
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کلمات کلیدی
Posterior probability - احتمال عقب ماندگیMild cognitive impairment (MCI) - اختلال شناختی خفیف (MCI)Alzheimer's disease (AD) - بیماری آلزایمر (AD)Biomarker - بیومارکرPrincipal components analysis (PCA) - تجزیه و تحلیل اجزای اصلی (PCA)Discriminant analysis - تجزیه و تحلیل دائمیDiagnosis - تشخیصEarly detection - تشخیص زود هنگامEEG - نوار مغزیNeurophysiology - نوروفیزیولوژیEvent-related potentials (ERP) - پتانسیل مربوط به رویداد (ERP)Prediction - پیش بینی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
سالمندی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Predicting which individuals will progress to Alzheimer's disease (AD) is important in both clinical and research settings. We used brain Event-Related Potentials (ERPs) obtained in a perceptual/cognitive paradigm with various processing demands to predict which individual Mild Cognitive Impairment (MCI) subjects will develop AD versus which will not. ERP components, including P3, memory “storage” component, and other earlier and later components, were identified and measured by Principal Components Analysis. When measured for particular task conditions, a weighted set of eight ERP component_conditions performed well in discriminant analysis at predicting later AD progression with good accuracy, sensitivity, and specificity. The predictions for most individuals (79%) had high posterior probabilities and were accurate (88%). This method, supported by a cross-validation where the prediction accuracy was 70-78%, features the posterior probability for each individual as a method of determining the likelihood of progression to AD. Empirically obtained prediction accuracies rose to 94% when the computed posterior probabilities for individuals were 0.90 or higher (which was found for 40% of our MCI sample).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurobiology of Aging - Volume 32, Issue 10, October 2011, Pages 1742-1755
Journal: Neurobiology of Aging - Volume 32, Issue 10, October 2011, Pages 1742-1755
نویسندگان
Robert M. Chapman, John W. McCrary, Margaret N. Gardner, Tiffany C. Sandoval, Maria D. Guillily, Lindsey A. Reilly, Elizabeth DeGrush,