TY - JOUR
T1 - Entropy modulation of electroencephalographic signals in physiological aging
AU - Alù, Francesca
AU - Orticoni, Alessandro
AU - Judica, Elda
AU - Cotelli, Maria
AU - Rossini, Paolo Maria
AU - Miraglia, Francesca
AU - Vecchio, Fabrizio
N1 - Funding Information:
This work was partially supported by the Italian Ministry of Health for Institutional Research (Ricerca corrente).
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/6
Y1 - 2021/6
N2 - Aging is a multifactorial physiological process characterized by the accumulation of degenerative processes impacting on different brain functions, including the cognitive one. A tool largely employed in the investigation of brain networks is the electroencephalogram (EEG). Given the cerebral complexity and dynamism, many non-linear approaches have been applied to explore age-related brain electrical activity modulation detected by the EEG: one of them is the entropy, which measures the disorder of a system. The present study had the aim to investigate aging influence on brain dynamics applying Approximate Entropy (ApEn) parameter to resting state EEG data of 68 healthy adult participants, divided with respect to their age in two groups, focusing on several specialized brain regions. Results showed that elderly participants present higher ApEn values than younger participants in the central, parietal and occipital areas, confirming the hypothesis that aging is characterized by an evolution of brain dynamics. Such findings may reflect a reduced synchronization of the neural networks cyclic activity, due to the reduction of cerebral connections typically found in aging process. Understanding the dynamics of brain networks by applying the entropy parameter could be useful for developing appropriate and personalized rehabilitation programs and for future studies on neurodegenerative diseases.
AB - Aging is a multifactorial physiological process characterized by the accumulation of degenerative processes impacting on different brain functions, including the cognitive one. A tool largely employed in the investigation of brain networks is the electroencephalogram (EEG). Given the cerebral complexity and dynamism, many non-linear approaches have been applied to explore age-related brain electrical activity modulation detected by the EEG: one of them is the entropy, which measures the disorder of a system. The present study had the aim to investigate aging influence on brain dynamics applying Approximate Entropy (ApEn) parameter to resting state EEG data of 68 healthy adult participants, divided with respect to their age in two groups, focusing on several specialized brain regions. Results showed that elderly participants present higher ApEn values than younger participants in the central, parietal and occipital areas, confirming the hypothesis that aging is characterized by an evolution of brain dynamics. Such findings may reflect a reduced synchronization of the neural networks cyclic activity, due to the reduction of cerebral connections typically found in aging process. Understanding the dynamics of brain networks by applying the entropy parameter could be useful for developing appropriate and personalized rehabilitation programs and for future studies on neurodegenerative diseases.
KW - Age
KW - Brain network
KW - EEG
KW - Nonlinearity
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U2 - 10.1016/j.mad.2021.111472
DO - 10.1016/j.mad.2021.111472
M3 - Article
C2 - 33766746
AN - SCOPUS:85103332099
VL - 196
JO - Mechanisms of Ageing and Development
JF - Mechanisms of Ageing and Development
SN - 0047-6374
M1 - 111472
ER -