Predicting dysfunctional age-related task activations from resting-state network alterations.

NeuroImage
R. D. MillMichael W Cole

Abstract

Alzheimer's disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the illness timecourse. These fMRI correlates of unhealthy aging have been studied in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC alterations associated with AD disrupt the flow of activations between brain regions, leading to aberrant task activations. We apply this activity flow model in a large sample of clinically normal older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) AD risk factors. Modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy (at-risk) aged activations. This enabled reliable prediction of at-risk AD task activations, and these predicted activations were related to individual differences in task behavior. These results support activity flow over altered intrinsic functional connections as a mechanism underlying Alzheimer's-related dysfunction, even in very early stages o...Continue Reading

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Citations

Nov 17, 2020·Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences·Kamen A TsvetanovJames B Rowe
Apr 21, 2021·NeuroImage·Brian P KeaneMichael W Cole
Jun 30, 2021·Brain Connectivity·Tanja VeselinovićIrene Neuner

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Methods Mentioned

BETA
PCA
PCAs

Software Mentioned

SPM
FEAT
Freesurfer
Matlab
FSL

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