Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 10, 422
eCollection

Functional Re-organization of Cortical Networks of Senior Citizens After a 24-Week Traditional Dance Program

Affiliations

Functional Re-organization of Cortical Networks of Senior Citizens After a 24-Week Traditional Dance Program

Vasiliki I Zilidou et al. Front Aging Neurosci.

Abstract

Neuroscience is developing rapidly by providing a variety of modern tools for analyzing the functional interactions of the brain and detection of pathological deviations due to neurodegeneration. The present study argues that the induction of neuroplasticity of the mature human brain leads to the prevention of dementia. Promising solution seems to be the dance programs because they combine cognitive and physical activity in a pleasant way. So, we investigated whether the traditional Greek dances can improve the cognitive, physical and functional status of the elderly always aiming at promoting active and healthy aging. Forty-four participants were randomly assigned equally to the training group and an active control group. The duration of the program was 6 months. Also, the participants were evaluated for their physical status and through an electroencephalographic (EEG) examination at rest (eyes-closed condition). The EEG testing was performed 1-14 days before (pre) and after (post) the training. Cortical network analysis was applied by modeling the cortex through a generic anatomical model of 20,000 fixed dipoles. These were grouped into 512 cortical regions of interest (ROIs). High quality, artifact-free data resulting from an elaborate pre-processing pipeline were segmented into multiple, 30 s of continuous epochs. Then, functional connectivity among those ROIs was performed for each epoch through the relative wavelet entropy (RWE). Synchronization matrices were computed and then thresholded in order to provide binary, directed cortical networks of various density ranges. The results showed that the dance training improved optimal network performance as estimated by the small-world property. Further analysis demonstrated that there were also local network changes resulting in better information flow and functional re-organization of the network nodes. These results indicate the application of the dance training as a possible non-pharmacological intervention for promoting mental and physical well-being of senior citizens. Our results were also compared with a combination of computerized cognitive and physical training, which has already been demonstrated to induce neuroplasticity (LLM Care).

Keywords: active aging; brain networks; dancing; dementia; electroencephalography; functional connectivity; neurodegeneration; neuroplasticity.

Figures

Figure 1
Figure 1
Visualization of the electroencephalographic (EEG) methodology from transforming the raw EEG data (1) to the cortical activity (2), estimation of regions of interest (ROIs) cortical activity (3), quantification of functional connectivity matrix (4) and finally cortical brain network analysis (5) through graph theory (6).
Figure 2
Figure 2
Visualization of the analysis performed for estimating the proper sample size for the proposed statistical analysis. The power analysis indicated that the proper sample size was 48 (24 participants per group), whereas we have included 44 senior citizens (22 participant per group).
Figure 3
Figure 3
Visualization of the hub significance of each node in terms of betweenness centrality (BC). The first column (from the left) displays a sagittal view of the cortex, the middle one an axial view and the right one a coronal view. Rows 1–2 are for the active control group for pre and post conditions respectively. Rows 3–4 are for the Dance group. The right plot denotes the pre-post differences in the hub strength for the active (upper plot) and for the dance (lower plot).
Figure 4
Figure 4
Visualization of the functional cartography in terms of participation coefficient (PC; horizontal axis) and within-module z-score (vertical axis). The DANCE group is denoted with asterisk and the ACTIVE group with circle. The pre-intervention is denoted with blue color and the post condition with red color.
Figure 5
Figure 5
Visualization of the Pearson correlation among nodes’ roles. Positive correlations are denoted with blue color and negative correlations with red color. The circle’s size is proportional to the strength of the statistical significance.

Similar articles

See all similar articles

Cited by 2 PubMed Central articles

References

    1. Balkus P. L. (1989). “Municipal dance for delayed individuals,” in Proceedings of the 3rd International Congress, Popular Dance and Education (Athens: D.O.L.T.), 13–17.
    1. Bamidis P. D., Fissler P., Papageorgiou S. G., Zilidou V., Konstantinidis E. I., Billis A. S., et al. . (2015). Gains in cognition through combined cognitive and physical training: the role of training dosage and severity of neurocognitive disorder. Front. Aging Neurosci. 7:152. 10.3389/fnagi.2015.00152 - DOI - PMC - PubMed
    1. Bamidis P. D., Vivas A. B., Styliadis C., Frantzidis C., Klados M., Schlee W., et al. . (2014). A review of physical and cognitive interventions in aging. Neurosci. Biobehav. Rev. 44, 206–220. 10.1016/j.neubiorev.2014.03.019 - DOI - PubMed
    1. Berg K., Wood-Dauphine S., Williams J. I., Gayton D. (2009). Measuring balance in the elderly: preliminary development of an instrument. Physiother. Can. 41, 304–311. 10.3138/ptc.41.6.304 - DOI
    1. Bherer L., Erickson K. I., Liu-Ambrose T. (2013). A review of the effects of physical activity and exercise on cognitive and brain functions in older adults. J. Aging Res. 2013:657508. 10.1155/2013/657508 - DOI - PMC - PubMed
Feedback