A quantitative neural network approach to understanding aging phenotypes

Highlights • We review literature on neural network integrity in healthy and pathological aging. • Imaging analysis approaches that better differentiate cognitive outcomes are needed. • We propose new strategies for predicting cognitive trajectories using graph theory.

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Published in:Ageing research reviews 2014-05, Vol.15, p.44-50
Main Authors: Ash, Jessica A, Rapp, Peter R
Format: Article
Language:English
Subjects:
Adult
Aged
Aging - physiology
Biological and medical sciences
Development. Metamorphosis. Moult. Ageing
Fundamental and applied biological sciences. Psychology
General aspects
Graph theory
Humans
Internal Medicine
Medical sciences
Middle Aged
Models, Neurological
Nerve Net - growth & development
Nerve Net - physiology
Neural networks
Neurocognitive aging
Neurology
Phenotype
Vertebrates: anatomy and physiology, studies on body, several organs or systems
Young Adult
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cites cdi_FETCH-LOGICAL-c536t-118b18b07c081c4c99b47f14366053b714f0a4e9bd4bfe48cdc42101936aa78c3
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container_title Ageing research reviews
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creator Ash, Jessica A
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description Highlights • We review literature on neural network integrity in healthy and pathological aging. • Imaging analysis approaches that better differentiate cognitive outcomes are needed. • We propose new strategies for predicting cognitive trajectories using graph theory.
doi_str_mv 10.1016/j.arr.2014.02.001
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source ScienceDirect Freedom Collection
subjects Adult
Aged
Aging - physiology
Biological and medical sciences
Development. Metamorphosis. Moult. Ageing
Fundamental and applied biological sciences. Psychology
General aspects
Graph theory
Humans
Internal Medicine
Medical sciences
Middle Aged
Models, Neurological
Nerve Net - growth & development
Nerve Net - physiology
Neural networks
Neurocognitive aging
Neurology
Phenotype
Vertebrates: anatomy and physiology, studies on body, several organs or systems
Young Adult
title A quantitative neural network approach to understanding aging phenotypes
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