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


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.


Diffusion tensor imaging Connectome Cognitive fatigue Physical fatigue Principal component analysis 



cognitive fatigue


diffusion tensor imaging


fractional anisotropy


mean diffusivity


principal component


physical fatigue


region of interest


rating of perceived exertion


tensor network principal component analysis



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)


  1. Avlund, K., Damsgaard, M. T., Sakari-Rantala, R., Laukkanen, P., & Schroll, M. (2002). Tiredness in daily activities among nondisabled old people as determinant of onset of disability. Journal of Clinical Epidemiology, 55, 965–973.CrossRefGoogle Scholar
  2. Avlund, K., Pedersen, A. N., & Schroll, M. (2003). Functional decline from age 80 to 85: Influence of preceding changes in tiredness in daily activities. Psychosomatic Medicine, 65(5), 771–777.CrossRefGoogle Scholar
  3. Bailey, A., Channon, S., & Beaumont, J. G. (2007). The relationship between subjective fatigue and cognitive fatigue in advanced multiple sclerosis. Multiple Sclerosis, 13, 73–80.CrossRefGoogle Scholar
  4. Bernitsas, E., Yarraguntla, K., Bao, F., Sood, R., Santiago-Martinez, C., Govindan, R., Khan, O., & Seraji-Bozorgzad, N. (2017). Structural and neuronal integrity measures of fatigue severity in multiple sclerosis. Brain Sciences, 7(8), 102.CrossRefGoogle Scholar
  5. Bester, M., Lazar, M., Petracca, M., Babb, J. S., Herbert, J., Grossman, R. I., & Inglese, M. (2013). Tract-specific white matter correlates of fatigue and cognitive impairment in benign multiple sclerosis. Journal of the Neurological Sciences, 330(1–2), 61–66.CrossRefGoogle Scholar
  6. Boksem, M. A., Meijman, T. F., & Lorist, M. M. (2005). Effects of mental fatigue on attention: An ERP study. Brain Research. Cognitive Brain Research, 25(1), 107–116.CrossRefGoogle Scholar
  7. Borg, G. A. V. (1982). Psychological bases of perceived exertion. Medicine and Science in Sports and Exercise, 14, 377–381.Google Scholar
  8. Calabrese, M., Rinaldi, F., Grossi, P., Mattisi, I., Bernardi, V., Favaretto, A., Perini, P., & Gallo, P. (2010). Basal ganglia and frontal/parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis. Multiple Sclerosis, 16(10), 1220–1228.CrossRefGoogle Scholar
  9. Clark, A. L., Delano-Wood, L., Sorg, S. F., Werhane, M. L., Hanson, K. L., & Schiehser, D. M. (2017). Cognitive fatigue is associated with reduced anterior internal capsule integrity in veterans with history of mild to moderate traumatic brain injury. Brain Imaging and Behavior, 11(5), 1548–1554.CrossRefGoogle Scholar
  10. Cockshell, S. J., & Mathias, J. L. (2014). Cognitive functioning in people with chronic fatigue syndrome: A comparison between subjective and objective measures. Neuropsychology, 28, 394–405.CrossRefGoogle Scholar
  11. Cook, D. B., O'Connor, P. J., Lange, G., & Steffener, J. (2007). Functional neuroimaging correlates of mental fatigue induced by cognition among chronic fatigue syndrome patients and controls. Neuroimage, 36(1), 108–122.CrossRefGoogle Scholar
  12. Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., Albert, M. S., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31, 968–980.CrossRefGoogle Scholar
  13. Dobryakova, E., DeLuca, J., Genova, H. M., & Wylie, G. R. (2013). Neural correlates of cognitive fatigue: Cortico-striatal circuitry and effort-reward imbalance. Journal of the International Neuropsychological Society, 19, 849–583.CrossRefGoogle Scholar
  14. Eldadah, B. A. (2010). Fatigue and fatigability in older adults. PM & R : The Journal of Injury, Function, and Rehabilitation, 2, 406–413.CrossRefGoogle Scholar
  15. Fatigue and Multiple Sclerosis: Evidence-Based Management Strategies for Fatigue in Multiple Sclerosis. (1998). Washintong, D.C.: Paralyzed Veterans of America.Google Scholar
  16. Finke, C., Schlichting, J., Papazoglou, S., Scheel, M., Greing, A., Soemmer, C., et al. (2015). Altered basal ganglia functional connectivity in multiple sclerosis patients with fatigue. Multiple Sclerosis Journal, 21, 925–934.CrossRefGoogle Scholar
  17. Fjell, A. M., Westlye, L. T., Greve, D. N., Fischl, B., Benner, T., van der Kouwe, A. J., et al. (2008). The relationship between diffusion tensor imaging and volumetry as measures of white matter properties. NeuroImage, 42(4), 1654–1668.CrossRefGoogle Scholar
  18. Genova, H. M., Rajagopalan, V., Deluca, J., Das, A., Binder, A., Arjunan, A., et al. (2013). Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging. PLoS One, 8(11), e78811.CrossRefGoogle Scholar
  19. Gill, T. M., Desai, M. M., Gahbauer, E. A., Holford, T. R., & Williams, C. S. (2001). Restricted activity among community-living older persons: Incidence, precipitants, and health care utilization. Annals of Internal Medicine, 135(5), 313–321.CrossRefGoogle Scholar
  20. Glynn, N. W., Santanasto, A. J., Simonsick, E. M., Boudreau, R. M., Beach, S. R., Schulz, R., & Newman, A. B. (2015). The Pittsburgh fatigability scale for older adults: Development and validation. Journal of the American Geriatrics Society, 63, 130–135.CrossRefGoogle Scholar
  21. Goni, M., Basu, N., Murray, A. D., & Waiter, G. D. (2018). Neural indicators of fatigue in chronic diseases: A systematic review of MRI studies. Diagnostics (Basel), 8(3), 42.CrossRefGoogle Scholar
  22. Gretton, A., Borgwardt, K. M., Rasch, M. J., Schölkopf, B., & Smola, A. (2012). A kernel two-sample test. Journal of Machine Learning Research, 13, 723–773.Google Scholar
  23. Jarad, N. A., Sequeiros, I. M., Patel, P., Bristow, K., & Sund, Z. (2012). Fatigue in cystic fibrosis: A novel prospective study investigating subjective and objective factors associated with fatigue. Chronic Respiratory Disease, 9, 241–249.CrossRefGoogle Scholar
  24. Juengst, S., Skidmore, E., Arenth, P. M., Niyonkuru, C., & Raina, K. D. (2013). The unique contribution of fatigue to disability in community dwelling adults with traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 94, 74–79.CrossRefGoogle Scholar
  25. Klaassen, E. B., Plukaard, S., Evers, E. A., de Groot, R. H., Backes, W. H., Veltman, D. J., & Jolles, J. (2016). Young and middle-aged schoolteachers differ in the neural correlates of memory encoding and cognitive fatigue: A functional MRI study. Frontiers in Human Neuroscience, 10, 148.CrossRefGoogle Scholar
  26. Kluger, B. M., Krupp, L. B., & Enoka, R. M. (2013). Fatigue and fatigability in neurologic illnesses: Proposal for a unified taxonomy. Neurology, 80(4), 409–416.CrossRefGoogle Scholar
  27. Kluger, B. M., Zhao, Q., Tanner, J. J., Schwab, N. A., Levy, S.-A., Burke, S. E., Huang, H., Ding, M., & Price, C. (2019). Structural brain correlates of fatigue in older adults with and without Parkinson disease. NeuroImage: Clinical, 22, 101730.CrossRefGoogle Scholar
  28. Kohl, A. D., Wylie, G. R., Genova, H. M., Hillary, F. G., & Deluca, J. (2009). The neural correlates of cognitive fatigue in traumatic brain injury using functional MRI. Brain Injury, 23, 420–432.CrossRefGoogle Scholar
  29. Lee, K. A., Hicks, G., & Nino-Murcia, G. (1991). Validity and reliability of a scale to assess fatigue. Psychiatry Research, 36, 291–298.CrossRefGoogle Scholar
  30. Lin, F., Roiland, R., Polesskaya, O., Chapman, B., Johnson, M., Brasch, J., et al. (2013). Fatigability disrupts cognitive Processes' regulation of inflammatory reactivity in old age. The American Journal of Geriatric Psychiatry, 22, 1544–1554.CrossRefGoogle Scholar
  31. Lin, F., Ren, P., Cotton, K., Porsteinsson, A., Mapstone, M., & Heffner, K. L. (2016). Mental fatigability and heart rate variability in mild cognitive impairment. The American Journal of Geriatric Psychiatry, 24(5), 374–378.CrossRefGoogle Scholar
  32. Lutz, J., Jager, L., de Quervain, D., Krauseneck, T., Padberg, F., Wichnalek, M., et al. (2008). White and gray matter abnormalities in the brain of patients with fibromyalgia: A diffusion-tensor and volumetric imaging study. Arthritis and Rheumatism, 58(12), 3960–3969.CrossRefGoogle Scholar
  33. Mackworth, J. F. (1964). Performance decrement in vigilance, threshold, and high-speed perceptual motor tasks. Canadian Journal of Psychology, 18, 209–223.CrossRefGoogle Scholar
  34. Marcora, S. M., Staiano, W., & Manning, V. (2009). Mental fatigue impairs physical performance in humans. Journal of Applied Physiology (Bethesda, MD: 1985), 106(3), 857–864.CrossRefGoogle Scholar
  35. Miller, A. H., Jones, J. F., Drake, D. F., Tian, H., Unger, E. R., & Pagnoni, G. (2014). Decreased basal ganglia activation in subjects with chronic fatigue syndrome: Association with symptoms of fatigue. PLoS One, 9, e98156.CrossRefGoogle Scholar
  36. Monje, M. (2018). Myelin plasticity and nervous system function. Annual Review of Neuroscience, 41, 61–76.CrossRefGoogle Scholar
  37. Muller, T., & Apps, M. A. J. (2018). Motivational fatigue: A neurocognitive framework for the impact of effortful exertion on subsequent motivation. Neuropsychologia, 123, 141–151.CrossRefGoogle Scholar
  38. Nazeri, A., Chakravarty, M. M., Rajji, T. K., Felsky, D., Rotenberg, D. J., Mason, M., Xu, L. N., Lobaugh, N. J., Mulsant, B. H., & Voineskos, A. N. (2015). Superficial white matter as a novel substrate of age-related cognitive decline. Neurobiology of Aging, 36(6), 2094–2106.CrossRefGoogle Scholar
  39. Phillips, O. R., Clark, K. A., Luders, E., Azhir, R., Joshi, S. H., Woods, R. P., Mazziotta, J. C., Toga, A. W., & Narr, K. L. (2013). Superficial white matter: Effects of age, sex, and hemisphere. Brain Connectivity, 3(2), 146–159.CrossRefGoogle Scholar
  40. Puri, B. K., Jakeman, P. M., Agour, M., Gunatilake, K. D., Fernando, K. A., Gurusinghe, A. I., … Gishen, P. (2012). Regional grey and white matter volumetric changes in myalgic encephalomyelitis (chronic fatigue syndrome): A voxel-based morphometry 3 T MRI study. The British Journal of Radiology, 85(1015), e270–e273.Google Scholar
  41. Rayhan, R. U., Stevens, B. W., Timbol, C. R., Adewuyi, O., Walitt, B., VanMeter, J. W., & Baraniuk, J. N. (2013). Increased brain white matter axial diffusivity associated with fatigue, pain and hyperalgesia in gulf war illness. PLoS One, 8(3), e58493.CrossRefGoogle Scholar
  42. Ren, P., Anderson, A. J., McDermott, K., Baran, T. M., & Lin, F. (2019). Cognitive fatigue and cortical-striatal network in old age. Aging, 11, 2312–2326.CrossRefGoogle Scholar
  43. Schaaf, M. E. v. d., Roelofs, K., Lange, F. P. d., Geurts, D. E. M., Meer, J. W. M. v. d., Knoop, H., & Toni, I. (2018). Fatigue is associated with altered monitoring and preparation of physical effort in patients with chronic fatigue syndrome. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3, 392–404.Google Scholar
  44. Schnelle, J. F., Buchowski, M. S., Ikizler, T. A., Durkin, D. W., Beuscher, L., & Simmons, S. F. (2012). Evaluation of two fatigability severity measures in elderly subjects. Journal of the American Geriatrics Society, 60, 1527–1533.CrossRefGoogle Scholar
  45. Simonsick, E. M., Glynn, N. W., Jerome, G. J., Shardell, M., Schrack, J. A., & Ferrucci, L. (2016). Fatigued, but not frail: Perceived fatigability as a marker of impending decline in mobility-intact older adults. Journal of the American Geriatrics Society, 64(6), 1287–1292.CrossRefGoogle Scholar
  46. Swain, M. G. (2000). Fatigue in chronic disease. Clinical Science, 99, 1–8.CrossRefGoogle Scholar
  47. Tanaka, M., & Watanabe, Y. (2012). Supraspinal regulation of physical fatigue. Neuroscience and Biobehavioral Reviews, 36(1), 727–734.CrossRefGoogle Scholar
  48. Tomporowski, P. D. (2003). Effects of acute bouts of exercise on cognition. Acta Psychologica, 112(3), 297–324.CrossRefGoogle Scholar
  49. Van Cutsem, J., Marcora, S., De Pauw, K., Bailey, S., Meeusen, R., & Roelands, B. (2017). The effects of mental fatigue on physical performance: A systematic review. Sports Medicine, 47(8), 1569–1588.CrossRefGoogle Scholar
  50. Yarraguntla, K., Seraji-Bozorgzad, N., Lichtman-Mikol, S., Razmjou, S., Bao, F., Sriwastava, S., Santiago-Martinez, C., Khan, O., & Bernitsas, E. (2018). Multiple sclerosis fatigue: A longitudinal structural MRI and diffusion tensor imaging study. Journal of Neuroimaging, 28, 650–655.CrossRefGoogle Scholar
  51. Zhang, S., Wang, Y., Deng, F., Zhong, S., Chen, L., Luo, X., Qiu, S., Chen, P., Chen, G., Hu, H., Lai, S., Huang, H., Jia, Y., Huang, L., & Huang, R. (2018a). Disruption of superficial white matter in the emotion regulation network in bipolar disorder. NeuroImage: Clinical, 20, 875–882.CrossRefGoogle Scholar
  52. Zhang, Z., Allen, G. I., Zhu, H., & Dunson, D. (2018b). Relationships between human brain structural connectomes and traits. bioRxiv, 256933.Google Scholar
  53. Zhang, Z., Descoteaux, M., Zhang, J., Girard, G., Chamberland, M., Dunson, D., Srivastava, A., & Zhu, H. (2018c). Mapping population-based structural connectomes. Neuroimage, 172, 130–145.CrossRefGoogle Scholar
  54. Zhu, Z., Johnson, N. F., Kim, C., & Gold, B. T. (2015). Reduced frontal cortex efficiency is associated with lower white matter integrity in aging. Cerebral Cortex, 25(1), 138–146.CrossRefGoogle Scholar

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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