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
A. Staffaroni, Jesse A. Brown, K. Casaletto, F. Elahi, Jersey Deng, J. Neuhaus, Y. Cobigo, Paige S. Mumford, Samantha M. Walters, R. Saloner, A. Karydas, G. Coppola, H. Rosen, B. Miller, W. Seeley, J. Kramer
Journal of Neuroscience February 13, 2018 DOI: 10.1523/jneurosci.3067-17.2018 (opens in new tab) via Semantic Scholar
Summary
AI-generated from the abstractThe default mode network (DMN) and whole-brain functional connectivity change nonlinearly with age in cognitively normal older adults. Among 111 adults aged 49–87, connectivity tended to increase between ages 50–66 and then declined significantly after age 74. Changes in within-DMN connectivity were specifically linked to changes in episodic memory and processing speed, but not working memory or executive functions. The memory association remained even after accounting for white matter hyperintensities and whole-brain connectivity, suggesting that DMN connectivity is a marker of memory performance in healthy aging. APOE status did not predict connectivity or its change over time.
Study at a glance
| Characteristics | Observational cohort Longitudinal Peer reviewed |
|---|---|
| Sample size | 111 |
| Population | Cognitively normal older human adults (ages 49–87) |
| Duration | Longitudinal (at least three task-free fMRI scans; 353 total scans) |
| Keywords | Psychology Medicine |
| Key finding | Default mode network and whole-brain functional connectivity follow a nonlinear trajectory with age, showing early increases and accelerating declines after age 74, and within-DMN connectivity changes are associated with episodic memory performance. |
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 (n = 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. APOE 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. SIGNIFICANCE STATEMENT 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.