Lifespan Changes in Network Structure and Network Topology Dynamics During Rest and Auditory Oddball Performance
Viktor Müller1, Viktor Jirsa2, Dionysios Perdikis1,2
1Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
Frontiers in Aging Neuroscience
|June 28, 2019
Summary
Brain network complexity and variability change across the lifespan, impacting cognitive function. These changes in hyper-frequency networks (HFNs) correlate with perceptual speed, offering insights into neural development and aging.
Area of Science:
- Neuroscience
- Cognitive Science
- Network Science
Background:
- Cortical differentiation and integration change throughout development and aging.
- Senescence is associated with dedifferentiation and reduced cortical specialization.
- Understanding lifespan changes in neural network dynamics is crucial.
Purpose of the Study:
- To evaluate network structure and topology dynamics across the lifespan using electroencephalography (EEG).
- To investigate changes in within- and cross-frequency coupling (WFC and CFC) in hyper-frequency networks (HFNs).
- To correlate network complexity and variability with cognitive performance, specifically perceptual speed.
Main Methods:
- EEG recordings during rest and auditory oddball task across different age groups.
- Construction of HFNs based on WFC and CFC at 10 oscillation frequencies (2-20 Hz).
- Analysis of graph-theoretical topology measures, network variability, complexity, and modular organization.
Main Results:
- WFC increased linearly with age, while CFC showed a U-shaped relationship.
- Network topology measures' magnitude increased with age, while their standard deviation peaked in young adults.
- Network complexity and variability were linked to perceptual speed, with distinct lifespan patterns.
- Young adults exhibited higher modularity and community structure similarity compared to children and older adults.
Conclusions:
- Network variability and complexity measures reflect lifespan-related changes in functional brain organization.
- These measures capture temporal and structural topology shifts in neuronal assemblies.
- Findings provide insights into neural development, maturation, and aging processes.
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