Regularity and randomness in ageing: Differences in resting-state EEG complexity measured by largest Lyapunov...

Area of Science:

• Neuroscience
• Dynamical Systems Theory
• Gerontology

Background:

• The loss of complexity in ageing hypothesis (LOCH) is supported by electroencephalography (EEG) studies using signal-domain complexity measures.
• Previous research primarily focused on signal-domain metrics, leaving dynamical systems perspectives less explored in aging brain complexity.

Purpose of the Study:

• To investigate age-related changes in brain complexity using the largest Lyapunov exponent (LLE) from a nonlinear dynamical systems viewpoint.
• To examine the regional specificity of age-related complexity differences and their relationship with other complexity measures.

Main Methods:

• Employed the largest Lyapunov exponent (LLE) to quantify brain complexity in 144 participants across young, young-old, and old-old age groups.
• Utilized both sensor-space and source-space analyses of EEG data.
• Correlated LLE with Lempel-Ziv complexity (LZC) and analyzed age-group differences across brain regions.

Main Results:

• Significantly lower LLE was observed in older adults compared to younger adults, indicating increased dynamical regularity.
• Age-related differences in LLE were most pronounced in frontal and temporal regions, with non-significant findings in the occipital region.
• Source-space analysis revealed reduced LLE in the posterior cingulate, and a negative correlation between LLE and LZC was found, suggesting simultaneous increases in regularity and signal-domain randomness.

Conclusions:

• The findings support the loss of complexity in ageing hypothesis (LOCH) by demonstrating age-related increases in brain signal regularity (lower LLE) and randomness (higher LZC).
• The study highlights the utility of nonlinear dynamical systems measures like LLE in understanding brain aging.
• Region-specific age-related complexity changes, particularly in frontal areas, warrant further investigation.