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

  • Timothy M. BaranEmail author
  • Zhengwu Zhang
  • Andrew James Anderson
  • Kelsey McDermott
  • Feng Lin
Original Research

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

Diffusion tensor imaging Connectome Cognitive fatigue Physical fatigue Principal component analysis 

Abbreviations

CF

cognitive fatigue

DTI

diffusion tensor imaging

FA

fractional anisotropy

MD

mean diffusivity

PC

principal component

PF

physical fatigue

ROI

region of interest

RPE

rating of perceived exertion

TN-PCA

tensor network principal component analysis

Notes

Acknowledgments

This work was supported by the National Institute on Aging at the National Institutes of Health (R21 AG053193).

Compliance with ethical standards

The study and all procedures were approved by the local Institutional Review Board. All participants provided written consent.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (University of Rochester Research Subjects Review Board) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11682_2019_201_MOESM1_ESM.pdf (26 kb)
ESM 1 (PDF 26 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Imaging SciencesUniversity of Rochester Medical CenterRochesterUSA
  2. 2.Department of Biomedical EngineeringUniversity of RochesterRochesterUSA
  3. 3.Department of Biostatistics and Computational BiologyUniversity of Rochester Medical CenterRochesterUSA
  4. 4.Department of NeuroscienceUniversity of Rochester Medical CenterRochesterUSA
  5. 5.School of NursingUniversity of Rochester Medical CenterRochesterUSA
  6. 6.Department of PsychiatryUniversity of Rochester Medical CenterRochesterUSA
  7. 7.Department of NeurologyUniversity of Rochester Medical CenterRochesterUSA
  8. 8.Department of Brain and Cognitive SciencesUniversity of RochesterRochesterUSA

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