Brain structural connectomes indicate shared neural circuitry involved in subjective experience of cognitive and physical fatigue in older adults

• Published in: Brain imaging and behavior Vol. 14; no. 6; pp. 2488 - 2499
• Main Authors: Baran, Timothy M., Zhang, Zhengwu, Anderson, Andrew James, McDermott, Kelsey, Lin, Feng
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2020; Springer Nature B.V
• Subjects: Adults; Aged; Biomedical and Life Sciences; Biomedicine; Brain; Brain - diagnostic imaging; Circuits; Cognition; Cognitive ability; Connectome; Diffusion Tensor Imaging; Editorials; Fatigue; Female; Gambling; Humans; Magnetic Resonance Imaging; Male; Mathematical analysis; Neostriatum; Networks; Neural networks; Neuroimaging; Neuropsychology; Neuroradiology; Neurosciences; Older people; Original Research; Principal components analysis; Psychiatry; Surface area; Tensors; Physical fatigue; Connectome; Cognitive fatigue; Diffusion tensor imaging; Principal component analysis
• ISSN: 1931-7557; 1931-7565; 1931-7565
• DOI: 10.1007/s11682-019-00201-9

Cumulative evidence suggests the existence of common processes underlying subjective experience of cognitive and physical fatigue. However, mechanistic understanding of the brain structural connections underlying the experience of fatigue in general, without the influence of clinical conditions, is limited. The purpose of the study was to examine the relationship between structural connectivity and perceived state fatigue in older adults. We enrolled cognitively and physically healthy older individuals ( n  = 52) and categorized them into three groups (low cognitive/low physical fatigue; low cognitive/high physical fatigue; high cognitive/low physical fatigue; no subjects had high cognitive/high physical fatigue) based on perceived fatigue from cognitive and physical fatigue manipulation tasks. Using sophisticated diffusion tensor imaging processing techniques, we extracted connectome matrices for six different characteristics of whole-brain structural connections for each subject. Tensor network principal component analysis was used to examine group differences in these connectome matrices, and extract principal brain networks for each group. Connected surface area of principal brain networks differentiated the two high fatigue groups from the low cognitive/physical fatigue group (high vs. low physical fatigue, p  = 0.046; high vs. low cognitive fatigue, p  = 0.036). Greater connected surface area within striatal-frontal-parietal networks was correlated with lower cognitive and physical fatigue, and was predictive of perceived physical and cognitive fatigue measures not used for group categorization (Pittsburgh fatigability physical subscale, R 2  = 0.70, p  < 0.0001; difference in self-report fatigue before and after gambling tasks, R 2  = 0.54, p < 0.0001). There are potentially structural connectomes resilient to both cognitive and physical fatigue in older adults.