Brain signal variability during rest as a neural mechanism underlying cognitive reserve

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Authors: Annabell Coors, Yaakov Stern, Christian Georg Habeck
Cited by: 0
References: 47

Abstract

BACKGROUND: Resting-state brain signal variability has been found to vary with age and cognitive function. Neural flexibility has been suggested as a neural mechanism underlying cognitive reserve (CR), a construct that describes better than expected cognition given brain status. We examined the associations between age, resting-state brain signal variability, and CR. METHOD: Analysis was based on resting-state functional neuroimaging data from 470 participants (ages 20-80) from the Reference Ability Neural Network and the CR studies. Brain signal variability was quantified as the log-transformed standard deviation of the time-varying blood-oxygen-level-dependent signal per region. We then derived variability pattern scores related to age, perceptual speed, episodic memory, fluid reasoning, and vocabulary using Scaled Subprofile Modelling principal component analysis. To formally test whether the cognition-related patterns fulfill the requirements for CR, we examined whether each pattern explained additional variance in cognition beyond brain structural measures, age, sex, education. We checked the robustness of our findings using permutation tests. Finally, we determined which brain regions significantly contributed to each pattern. RESULTS: Brain variability patterns emerged across all four cognitive domains and showed robust associations with CR in the domains of episodic memory, fluid reasoning and vocabulary, explaining between 10.5%-18.3% of variance in cognitive performance. The cognition-related variability patterns inversely mirrored age-related variability patterns in some brain regions. CONCLUSIONS: BOLD signal variability plays a role in aging and underlies CR in the domains of episodic memory, fluid reasoning, and vocabulary.

Fields of Study & Subjects

Technology and Human Factors in Education and Health

Publication details

Journal / source
NeuroImage
Publisher
Elsevier BV
Volume
339
Pages
122150–122150
Publication date
29 July 2026
Language
EN