Most of what is known about the reorganization of functional brain networks that accompanies normal aging is based on neuroimaging studies in which participants perform specific tasks. In these studies, reorganization is defined by the differences in task activation between young and old adults. However, task activation differences could be the result of differences in task performance, strategy, or motivation, and not necessarily reflect reorganization. Resting-state fMRI provides a method of investigating functional brain networks without such confounds. Here, a support vector machine (SVM) classifier was used in an attempt to differentiate older adults from younger adults based on their resting-state functional connectivity. In addition, the information used by the SVM was investigated to see what functional connections best differentiated younger adult brains from older adult brains. Three separate resting-state scans from 26 younger adults (18-35 yrs) and 26 older adults (55-85) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available in the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 100 seed-regions from four functional networks with 5 mm3 radius were defined based on a recent study using machine learning classifiers on adolescent brains. Time-series for every seed-region were averaged and three matrices of z-transformed correlation coefficients were created for each subject corresponding to each individual’s three resting-state scans. SVM was then applied using leave-one-out cross-validation. The SVM classifier was 84% accurate in classifying older and younger adult brains. The majority of the connections used by the classifier to distinguish subjects by age came from seed-regions belonging to the sensorimotor and cingulo-opercular networks. These results suggest that age-related decreases in positive correlations within the cingulo-opercular and default networks, and decreases in negative correlations between the default and sensorimotor networks, are the distinguishing characteristics of age-related reorganization.

Resting-state functional MRI (rs-fMRI) has emerged as a powerful tool for investigating brain functional connectivity (FC). Research in recent years has focused on assessing the reliability of FC across younger subjects within and between scan-sessions. Test-retest reliability in resting-state functional connectivity (RSFC) has not yet been examined in older adults. In this study, we investigated age-related differences in reliability and stability of RSFC across scans. In addition, we examined how global signal regression (GSR) affects RSFC reliability and stability. Three separate resting-state scans from 29 younger adults (18–35 yrs) and 26 older adults (55–85 yrs) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available as part of the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 92 regions of interest (ROIs) with 5 cubic mm radius, derived from the default, cingulo-opercular, fronto-parietal and sensorimotor networks, were previously defined based on a recent study. Mean time series were extracted from each of the 92 ROIs from each scan and three matrices of z-transformed correlation coefficients were created for each subject, which were then used for evaluation of multi-scan reliability and stability. The young group showed higher reliability of RSFC than the old group with GSR (p-value = 0.028) and without GSR (p-value <0.001). Both groups showed a high degree of multi-scan stability of RSFC and no significant differences were found between groups. By comparing the test-retest reliability of RSFC with and without GSR across scans, we found significantly higher proportion of reliable connections in both groups without GSR, but decreased stability. Our results suggest that aging is associated with reduced reliability of RSFC which itself is highly stable within-subject across scans for both groups, and that GSR reduces the overall reliability but increases the stability in both age groups and could potentially alter group differences of RSFC.