Recurrence quantification analysis provides the link between age-related decline in motor brain response and complexity of the baseline EEG

The goal of the present study is to investigate the effect of healthy aging on the neuronal mechanisms supporting human brain activity during motor task performance. Such biomarkers of the age-related changes can be detected using mathematical methods of time-series analysis and complexity analysis. Methods. In the present paper, recurrence quantification analysis (RQA) measures are employed to explore the complexity of the pre-movement EEG in young and elderly adult groups. To evaluate the neural brain response during motor execution, we applied the traditional methods of time-frequency analysis. Results. The proposed approach demonstrated that (i) the RQA measures show a significant increase of complexity in elderly adults; (ii) increased pre-movement EEG complexity comes with the reduced motor-related brain response in the $\alpha/\mu$-band ($p< 0.01$), estimated via the traditional methods of time-frequency analysis. It allows to conclude that the increased pre-movement EEG complexity indicates the weak neuronal plasticity degenerated under the factor of age. Conclusion. The complexity of the pre-movement $\alpha/\mu$-band neuronal oscillations could be considered as a relevant measure for the detection of age-related cognitive or motor impairments. Besides, applied RQA method demonstrated a good ability to assess the complexity features of pre-stimulus EEG and provided a clear interpretation of age-related changes in electrical activity of the brain cortex.