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Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance

Behavioral and physiological evidence suggests that developmental changes lead to enhanced cortical differentiation and integration through maturation and learning, and that senescent changes during aging result in dedifferentiation and reduced cortical specialization of neural cell assemblies. We u...

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Autores principales: Müller, Viktor, Jirsa, Viktor, Perdikis, Dionysios, Sleimen-Malkoun, Rita, von Oertzen, Timo, Lindenberger, Ulman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580332/
https://www.ncbi.nlm.nih.gov/pubmed/31244648
http://dx.doi.org/10.3389/fnagi.2019.00138
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author Müller, Viktor
Jirsa, Viktor
Perdikis, Dionysios
Sleimen-Malkoun, Rita
von Oertzen, Timo
Lindenberger, Ulman
author_facet Müller, Viktor
Jirsa, Viktor
Perdikis, Dionysios
Sleimen-Malkoun, Rita
von Oertzen, Timo
Lindenberger, Ulman
author_sort Müller, Viktor
collection PubMed
description Behavioral and physiological evidence suggests that developmental changes lead to enhanced cortical differentiation and integration through maturation and learning, and that senescent changes during aging result in dedifferentiation and reduced cortical specialization of neural cell assemblies. We used electroencephalographic (EEG) recordings to evaluate network structure and network topology dynamics during rest with eyes closed and open, and during auditory oddball task across the lifespan. For this evaluation, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that WFC increased monotonously across the lifespan, whereas CFC showed a U-shaped relationship. These changes in WFC and CFC strengths coevolve with changes in network structure and network topology dynamics, namely the magnitude of graph-theoretical topology measures increased linearly with age (except for characteristic path length, which is going shorter), while their standard deviation showed an inverse U-shaped relationship with a peak in young adults. Temporal as well as structural or nodal similarity of network topology (with some exceptions) seems to coincide with variability changes, i.e., stronger variability is related to higher similarity between consecutive time windows or nodes. Furthermore, network complexity measures showed different lifespan-related patterns, which depended on the balance of WFC and CFC strengths. Both variability and complexity of HFNs were strongly related to the perceptual speed scores. Finally, investigation of the modular organization of the networks revealed higher number of modules and stronger similarity of community structures across time in young adults as compared with children and older adults. We conclude that network variability and complexity measures reflect temporal and structural topology changes in the functional organization and reorganization of neuronal cell assemblies across the lifespan.
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spelling pubmed-65803322019-06-26 Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance Müller, Viktor Jirsa, Viktor Perdikis, Dionysios Sleimen-Malkoun, Rita von Oertzen, Timo Lindenberger, Ulman Front Aging Neurosci Neuroscience Behavioral and physiological evidence suggests that developmental changes lead to enhanced cortical differentiation and integration through maturation and learning, and that senescent changes during aging result in dedifferentiation and reduced cortical specialization of neural cell assemblies. We used electroencephalographic (EEG) recordings to evaluate network structure and network topology dynamics during rest with eyes closed and open, and during auditory oddball task across the lifespan. For this evaluation, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that WFC increased monotonously across the lifespan, whereas CFC showed a U-shaped relationship. These changes in WFC and CFC strengths coevolve with changes in network structure and network topology dynamics, namely the magnitude of graph-theoretical topology measures increased linearly with age (except for characteristic path length, which is going shorter), while their standard deviation showed an inverse U-shaped relationship with a peak in young adults. Temporal as well as structural or nodal similarity of network topology (with some exceptions) seems to coincide with variability changes, i.e., stronger variability is related to higher similarity between consecutive time windows or nodes. Furthermore, network complexity measures showed different lifespan-related patterns, which depended on the balance of WFC and CFC strengths. Both variability and complexity of HFNs were strongly related to the perceptual speed scores. Finally, investigation of the modular organization of the networks revealed higher number of modules and stronger similarity of community structures across time in young adults as compared with children and older adults. We conclude that network variability and complexity measures reflect temporal and structural topology changes in the functional organization and reorganization of neuronal cell assemblies across the lifespan. Frontiers Media S.A. 2019-06-11 /pmc/articles/PMC6580332/ /pubmed/31244648 http://dx.doi.org/10.3389/fnagi.2019.00138 Text en Copyright © 2019 Müller, Jirsa, Perdikis, Sleimen-Malkoun, von Oertzen and Lindenberger. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Müller, Viktor
Jirsa, Viktor
Perdikis, Dionysios
Sleimen-Malkoun, Rita
von Oertzen, Timo
Lindenberger, Ulman
Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
title Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
title_full Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
title_fullStr Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
title_full_unstemmed Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
title_short Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
title_sort lifespan changes in network structure and network topology dynamics during rest and auditory oddball performance
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580332/
https://www.ncbi.nlm.nih.gov/pubmed/31244648
http://dx.doi.org/10.3389/fnagi.2019.00138
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