… information across the whole brain, and might improve the prediction performance. To learn
… for the age prediction, we adopt deep CNNs to learn hierarchical FC patterns from the dense …

… Importantly, since we hypothesized that model predictions of brain age should have increased
error in the preclinical and symptomatic AD samples, these samples were used only for …

… age of a subject using only brain imaging data, is an exciting avenue of research. In this work
we seek to build models of brain age based on functional connectivity … of brain age as well …

… In the present study, we employed resting-state functional MRI data to construct functional
network models. Principal component analysis was performed on the FC matrices across all …

… is significantly linked with the functional maturity of the brain. Our … functional connections
changes with age likely reflects developmental trends of functional organization in distinct brain …

… Predictability of individual working memory capacity (WMC) based on functional connectivity
patterns in nine brain networks. Scatter plots show real against mean predicted WMC …

… Therefore, in this work we directly used the functional connectivity to initialize the adjacency
… the reliable relationship between structural and functional connectivity, using the original FC …

… vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that
… whole-brain functional connectivity pattern was used as the feature for age prediction. Our …

… functional connectivity (SFC) and more recently proposed dynamic functional connectivity
(… ), data-driven spatial network and functional network connectivity (FNC) are often computed …

… brain age prediction models. Instead of characterizing functional connectivity pattern at one
single spatial scale, we computed functional connectivity measures between personalized …