Does functional system segregation mediate the effects of lifestyle on cognition in older adults?
Poster No:
1131
Submission Type:
Abstract Submission
Authors:
Petar Raykov1, Ethan Knights1, Richard Henson1
Institutions:
1MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom
First Author:
Co-Author(s):
Introduction:
Healthy aging is typically accompanied by cognitive decline (Nyberg et al., 2003). Previous work has shown that engaging in multiple, non-work activities during midlife can have a protective effect on cognition several decades later, rendering it less dependent on brain structural health; the definition of "cognitive reserve" (D. Chan et al., 2018; Gow et al., 2017). Other work has shown that increasing age is associated with reduced segregation of large-scale brain functional networks (M. Chan et al., 2021; Wig, 2017). Here we tested the hypothesis that functional segregation mediates this effect of middle-aged lifestyle on late-life cognition.
Methods:
We used fMRI data acquired during three different brain states (tasks) in the CamCAN dataset (www.cam-can.org), together with cognitive data on fluid intelligence and episodic memory and retrospective lifestyle data from the Lifetime of Experiences Questionnaire (LEQ). We computed functional system segregation (SyS) as the difference between within network connectivity compared to between network connectivity. We ran regression models to examine whether SyS measures predict cognition after adjusting for linear and non-linear age and sex effects. We additionally ran mediation models examining how previous midlife activities (during ages of 30-64 years) affected SyS and cognition in late-life (65+ years old).
Results:
In all three tasks, we replicated the negative association between adult age and functional segregation, and showed that functional segregation related to fluid intelligence even after adjusting for the (nonlinear) age effects. However, we found no evidence that functional segregation in late-life mediated the relationship between non-specific (non-occupation) midlife activities from the LEQ and either measure of cognition in late-life. In exploratory analyses, we also failed to find evidence that functional segregation in late-life related to youth-specific LEQ activities (i.e., education), or that functional segregation in mid-life related to current non-specific LEQ activities. These results were largely robust to use of different brain parcellations and pre-processing strategies. We tested how different pre-processing strategies affect measures of functional system segregation and its relation to fluid intelligence.
Conclusions:
Our results confirm that measures of functional system segregation may be indicative of cognition. We did not find evidence that functional segregation mediated the effects non-specific midlife activities have on late life cognition. Thus, the brain correlates of cognitive reserve arising from mid-life activities remain to be discovered.
Higher Cognitive Functions:
Higher Cognitive Functions Other
Learning and Memory:
Long-Term Memory (Episodic and Semantic)
Lifespan Development:
Aging 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Aging
Cognition
FUNCTIONAL MRI
Other - Cognitive Reserve, Functional Connectivity, Graph Theory
1|2Indicates the priority used for review
·Predicting Fluid Intelligence from SyS (N=627). Fluid intelligence was positively related to SyS in each of the three brain states, after adjusting for second-order effects of age, and sex.
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Chan, M. Y., Han, L., Carreno, C. A., Zhang, Z., Rodriguez, R. M., LaRose, M., Hassenstab, J., & Wig, G. S. (2021). Long-term prognosis and educational determinants of brain network decline in older adult individuals. Nature Aging, 1(11), 1053–1067
Gow, A. J., Pattie, A., & Deary, I. J. (2017). Lifecourse Activity Participation From Early, Mid, and Later Adulthood as Determinants of Cognitive Aging: The Lothian Birth Cohort 1921. The Journals of Gerontology: Series B, 72(1), 25–37. https://doi.org/10.1093/geronb/gbw124
Nyberg, L., Maitland, S. B., Rönnlund, M., Bäckman, L., Dixon, R. A., Wahlin, Å., & Nilsson, L.-G. (2003). Selective adult age differences in an age-invariant multifactor model of declarative memory. Psychology and Aging, 18(1), 149.
Wig, G. S. (2017). Segregated systems of human brain networks. Trends in Cognitive Sciences, 21(12), 981–996.