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- W2766788618 abstract "Brain structural and functional changes due to aging are complex and heterogeneous, potentially reflected by multiple co-occurring pathologic processes and individuals' resilience to them. We sought to investigate the structural and functional heterogeneity of brain aging in cognitively normal aging cohort. We uncovered heterogeneous functional and structural magnetic resonance patterns of brain aging in a large sample (n=400, aged 50 to 96 years) from the Baltimore Longitudinal Study of Aging (BLSA) cohort, USA. Using machine-learning methods, we calculated normative cross-sectional aging curves for brain structure as well as brain functional connectivity. We identified resilient and advanced brain aging as deviation from those curves and demonstrated five distinct imaging phenotypes for advanced brain agers leveraging a semi-supervised machine-learning approach. We associated those phenotypes with the rich cognitive battery of BLSA. In contrast to resilient brain agers, an advanced brain aging phenotype included individuals who demonstrated AD-like structural and functional brain changes including hippocampal, para-hippocampal and amygdalae atrophy, lower functional coherence in the hippocampus, thalamus and anterior insula and overall decrease in default mode network connectivity, more white matter hyperintensities and lower cognitive performance. A second phenotype included individuals with brain changes in line with early stages of AD, including bilateral hippocampal and superior temporal gyrus atrophy, lower precuneus and hippocampus functional coherence in addition to higher functional connectivity in the medial temporal lobe, no difference in white matter hyperintensities burden and higher cognitive performance, which might reflect cognitive reserve. Another phenotype involved primarily sensory-motor-cerebellar networks." @default.
- W2766788618 created "2017-11-10" @default.
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- W2766788618 date "2017-07-01" @default.
- W2766788618 modified "2023-10-16" @default.
- W2766788618 title "MAPPING THE HETEROGENEITY OF NEUROANATOMY AND FUNCTIONAL CONNECTIVITY DEVIATION FROM TYPICAL BRAIN AGING: A PATTERN ANALYSIS AND MACHINE LEARNING STUDY" @default.
- W2766788618 doi "https://doi.org/10.1016/j.jalz.2017.07.533" @default.
- W2766788618 hasPublicationYear "2017" @default.
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