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Brain Imaging Behav. 2019 Sep 6. doi: 10.1007/s11682-019-00201-9. [Epub ahead of print]

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

Author information

1
Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, 14642, USA. Timothy.Baran@Rochester.edu.
2
Department of Biomedical Engineering, University of Rochester, Rochester, NY, 14627, USA. Timothy.Baran@Rochester.edu.
3
Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, 14642, USA.
4
Department of Biomedical Engineering, University of Rochester, Rochester, NY, 14627, USA.
5
Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, 14642, USA.
6
School of Nursing, University of Rochester Medical Center, Rochester, NY, 14642, USA.
7
Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, 14642, USA.
8
Department of Neurology, University of Rochester Medical Center, Rochester, NY, 14642, USA.
9
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, 14627, USA.

Abstract

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, R2 = 0.70, p < 0.0001; difference in self-report fatigue before and after gambling tasks, R2 = 0.54, p < 0.0001). There are potentially structural connectomes resilient to both cognitive and physical fatigue in older adults.

KEYWORDS:

Cognitive fatigue; Connectome; Diffusion tensor imaging; Physical fatigue; Principal component analysis

PMID:
31493140
DOI:
10.1007/s11682-019-00201-9

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