Cognitive Load of Exercise Influences Cognition and Neuroplasticity of Healthy Elderly: An Exploratory Investigation

Yi Ping Chao, Changwei W. Wu, Li Jung Lin, Cheng Hung Lai, Hong Yi Wu, Ai Ling Hsu, Chiao Nan Chen

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This study explored the effects of exercise with either high cognitive load or low cognitive load on cognitive performance and neuroplasticity in healthy elderly. Twenty-eight sedentary community-dwelling seniors participated in this study. Participants were assigned to one of three groups: the control group (C), low-cognitive load exercise group (LE), or high-cognitive load exercise group (HE). Individuals in both exercise groups engaged in moderate-intensity aerobic exercise for 4 months. Resting-state functional MRI and diffusion MRI were used to investigate the effects of intervention on functional and structural connectivity, respectively. Analysis of covariance with baseline, age and the education year as covariates was used to determine the effects of intervention. We found 4 months of exercise with high-cognitive load, but not exercise with low-cognitive load, improved the overall cognitive function of healthy elderly. Additionally, the HE group showed increased resting-state functional connectivity of superior frontal gyrus and anterior cingulate cortex and decreased functional connectivity of middle occipital gyrus and postcentral gyrus. The age-related alterations in local efficiency and betweenness were protected by exercise. Our findings might suggest that exercise with greater cognitive load likely results in greater training effects on cognition and brain connectivity than exercise requiring lower cognitive loads for healthy elderly.

Original languageEnglish
Pages (from-to)391-399
Number of pages9
JournalJournal of Medical and Biological Engineering
Issue number3
Publication statusPublished - Jun 1 2020


  • Dance
  • Diffusion tensor imaging
  • Functional connectivity
  • Plasticity

ASJC Scopus subject areas

  • Biomedical Engineering


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