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Entropy modulation of electroencephalographic signals in physiological aging
Francesca Alù1, Alessandro Orticoni1, Elda Judica2
1Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy.
Mechanisms of Ageing and Development
|March 26, 2021
Summary
Aging alters brain dynamics, increasing neural network disorder in older adults. This study used electroencephalography (EEG) and Approximate Entropy (ApEn) to reveal age-related changes in brain activity across different regions.
Area of Science:
- Neuroscience
- Gerontology
- Computational Biology
Background:
- Aging is a complex process affecting cognitive functions and brain networks.
- Electroencephalography (EEG) is crucial for studying brain electrical activity.
- Non-linear methods, like entropy, help analyze complex brain dynamics.
Purpose of the Study:
- To investigate the influence of aging on brain dynamics using Approximate Entropy (ApEn).
- To analyze resting-state EEG data from healthy adults across different age groups.
- To identify age-related changes in specific brain regions.
Main Methods:
- Utilized Approximate Entropy (ApEn) to quantify brain signal complexity.
- Analyzed resting-state electroencephalogram (EEG) data from 68 healthy adults.
- Compared ApEn values between younger and elderly participant groups in central, parietal, and occipital regions.
Main Results:
- Elderly participants exhibited significantly higher ApEn values than younger participants.
- Increased ApEn was observed in the central, parietal, and occipital brain areas of older adults.
- These findings suggest a shift in brain dynamics with aging.
Conclusions:
- Aging is associated with increased disorder or complexity in brain dynamics.
- Reduced neural network synchronization may underlie observed changes in aging.
- Entropy analysis of EEG offers insights into brain network evolution and potential applications in neurodegenerative disease research and rehabilitation.
