Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder

Predicting future brain topography can give insight into neural correlates of aging and neurodegeneration. Due to variability in the aging process, it has been challenging to precisely estimate brain topographical change according to aging. Here, we predict age-related brain metabolic change by gene...

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Veröffentlicht in:	Frontiers in aging neuroscience Jg. 10; S. 212
Hauptverfasser:	Choi, Hongyoon, Kang, Hyejin, Lee, Dong Soo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Research Foundation 12.07.2018 Frontiers Media S.A
Schlagworte:	Age Aging Alzheimer's disease Amygdala APOE4 Apolipoprotein E4 Brain architecture brain metabolism Cognitive ability deep generative model FDG PET Geriatrics Medical imaging Metabolism Neurodegeneration Neuroscience Population Population distribution Positron emission tomography Prediction models Teaching methods Topography variational autoencoder South Korea brain metabolism variational autoencoder APOE4 FDG PET deep generative model
ISSN:	1663-4365, 1663-4365
Online-Zugang:	Volltext
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