The Longitudinal Trajectory of Default Mode Network Connectivity in Healthy Older Adults Varies As a Function of Age and Is Associated with Changes in Episodic Memory and Processing Speed

Abstract

The default mode network (DMN) supports memory functioning and may be sensitive to preclinical Alzheimer's pathology. Little is known, however, about the longitudinal trajectory of this network's intrinsic functional connectivity (FC). In this study, we evaluated longitudinal FC in 111 cognitively normal older human adults (ages 49-87, 46 women/65 men), 92 of whom had at least three task-free fMRI scans ( = 353 total scans). Whole-brain FC and three DMN subnetworks were assessed: (1) within-DMN, (2) between anterior and posterior DMN, and (3) between medial temporal lobe network and posterior DMN. Linear mixed-effects models demonstrated significant baseline age × time interactions, indicating a nonlinear trajectory. There was a trend toward increasing FC between ages 50-66 and significantly accelerating declines after age 74. A similar interaction was observed for whole-brain FC. status did not predict baseline connectivity or change in connectivity. After adjusting for network volume, changes in within-DMN connectivity were specifically associated with changes in episodic memory and processing speed but not working memory or executive functions. The relationship with processing speed was attenuated after covarying for white matter hyperintensities (WMH) and whole-brain FC, whereas within-DMN connectivity remained associated with memory above and beyond WMH and whole-brain FC. Whole-brain and DMN FC exhibit a nonlinear trajectory, with more rapid declines in older age and possibly increases in connectivity early in the aging process. Within-DMN connectivity is a marker of episodic memory performance even among cognitively healthy older adults. Default mode network and whole-brain connectivity, measured using task-free fMRI, changed nonlinearly as a function of age, with some suggestion of early increases in connectivity. For the first time, longitudinal changes in DMN connectivity were shown to correlate with changes in episodic memory, whereas volume changes in relevant brain regions did not. This relationship was not accounted for by white matter hyperintensities or mean whole-brain connectivity. Functional connectivity may be an early biomarker of changes in aging but should be used with caution given its nonmonotonic nature, which could complicate interpretation. Future studies investigating longitudinal network changes should consider whole-brain changes in connectivity.

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

“…However, EEG-RSN activities did not show any age dependences in DLB patients and healthy subjects. This result indicates that EEG-RSN activities reflect cortical functional differences rather than age differences which was suggested by fMRI studies [56, 57]. Third, the diagnoses were largely based on clinical features according to the third DLB consortium criteria, and no pathology was confirmed as this study was a clinical research.…”

“…In a previous study, we used 80 healthy subjects with a wide age range (44.2 ± 20.0 years) and revealed that there were 5 common EEG-RSNs across a wide age range, and their activities showed no age dependences [20]. This result indicates that age-related changes in EEG-RSN activities are better described by cognitive functions rather than age itself which was suggested by fMRI studies [56, 57]. Therefore, in this study, although there was a significant age difference between these 80 healthy subjects and 41 DLB patients, considering the normal MMSE and CDR results of the healthy subjects over 60 years old, we could compare EEG-RSN activities between healthy subjects and DLB patients.…”

A longitudinal characterization of perfusion in the aging brain and associations with cognition and neural structure

“…Processing speed was analyzed using a previously described computerized battery that is sensitive in an aging population and is associated with brain structure (Kerchner et al, 2012) and function (Staffaroni et al, 2018). Processing speed was analyzed using a previously described computerized battery that is sensitive in an aging population and is associated with brain structure (Kerchner et al, 2012) and function (Staffaroni et al, 2018).…”

“…Episodic memory tasks included the California Verbal Learning Test, 2nd edition (Delis, Kramer, Kaplan, & Ober, 2000), short delay free recall, long delay free recall, and recognition discriminability (d'), as well as the total score on Benson figure recall from the Uniform Data Set (Weintraub et al, 2018). Each test was converted to a Z-score and the resultant Z-scores were averaged for each participant to create executive function and episodic memory composites as previously described (Staffaroni et al, 2018). Each test was converted to a Z-score and the resultant Z-scores were averaged for each participant to create executive function and episodic memory composites as previously described (Staffaroni et al, 2018).…”

“…WMHs were quantified using a previously-described, automated algorithm (Staffaroni et al, 2018) based on a regression algorithm (Dadar et al, 2017) using Hidden Markov Random Field with Expectation Maximization software (Avants, Tustison, Wu, Cook, & Gee, 2011). Global WMH burden in mm 3 was log transformed to achieve a normal distribution.…”