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. 2023 Jul-Aug;37(4):1649-1657.
doi: 10.21873/invivo.13250.

The Decline of Cortical Beta Oscillation on the Function of Eye-hand Coordination in the Healthy Elderly

Rodiya Manor  1   2 , Dania Cheaha  2   3 , Enoch Perimal  4   5 , Pornchai Sathirapanya  6 , Ekkasit Kumarnsit  1   2 , Nifareeda Samerphob  7   2
Affiliations

The Decline of Cortical Beta Oscillation on the Function of Eye-hand Coordination in the Healthy Elderly

Rodiya Manor et al. In Vivo. 2023 Jul-Aug.

Abstract

Background/aim: There seems to be a correlation between changes in movement patterns with aging and brain activation. In the preparation and execution of movements, neural oscillations play an important role. In this study, cortical high frequency brain oscillations were analyzed in 15 healthy young adults and 15 elderly adults who participated in eye-hand coordination tasks.

Patients and methods: The brain activities of healthy young and older adults were recorded using electroencephalography (EEG).

Results: Elderly participants spent significantly more time completing the task than young participants. During eye-hand coordination in elderly groups, beta power decreased significantly in the central midline and parietal brain regions. The data suggest that healthy elderly subjects had intact cognitive performance, but relatively poor eye-hand coordination associated with loss of beta brain oscillation in the central midline and parietal cortex and reduced ability to attentional movement.

Conclusion: Beta frequency in the parietal brain sites may contribute to attentional movement. This could be an important method for monitoring cognitive brain function changes as the brain ages.

Keywords: Parietal cortex; attentional movement task; beta; gamma; healthy elderly adult.

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Conflict of interest statement

There are no conflicts of interest related to this study.

Figures

Figure 1
Figure 1. A diagram of the experimental protocol. (A) Experimental timeline, (B) electroencephalography (EEG) recording and EEG electrode placement according to 10-20 international system, and (C) Data processing and data analysis.
Figure 2
Figure 2. Cognitive score and Modified 25-holepeg board test. (A) Violin plot of Thai- Mini-Mental State Examination (MMSE) score of young and elderly participants, (B) simple linear regression graph with age (x-axis) as the predictor variable and the Thai-MMSE score (Y-axis) as the dependent variable, (C) Box plot of the modified 25-holepeg board test completion time score, and (D) simple linear regression graph with age (xaxis) as the predictor variable and the time of completion (Y-axis) as the dependent variable. Data are expressed in mean±S.E.M, and unpaired ttest was used for statistical analysis (p<0.0001).
Figure 3
Figure 3. Percentage of total power of the electroencephalography (EEG) signal from the central midline during resting states and during task performance in young and elderly participants. Brain activities from the regions of Fz (A and E), Cz (B and F), Pz (C and G), and Oz (D and H) were recorded and analyzed. Data are expressed in mean±S.E.M.
Figure 4
Figure 4. Percentage of total power of the electroencephalography (EEG) signal in the left and right hemispheres during resting states and during task performance in young and elderly participants. Brain activities from the regions of P3 (A and E), P4 (B and F), T5 (C and G), and T6 (D and H) were recorded and analyzed. Data are expressed in mean±S.E.M.
Figure 5
Figure 5. Beta and gamma band activities during the resting state and motor performance test in healthy young and aging participants. The data are shown for the following regions: Fz (A), Cz (B), Pz (C), Oz (D), P3 (E), P4 (F), T5 (G), and T6 (H). Data are expressed in mean±S.E.M, Twoway repeated ANOVA was used for statistical analysis followed by Tukey’s post hoc test (*p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001).
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