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The Influence of Ageing on Complex Brain Networks : A Graph Theoretical Analysis

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TLDR
To determine the functional connectivity of different EEG bands at the “baseline” situation (rest) and during mathematical thinking in children and young adults to study the maturation effect on brain networks at rest and during a cognitive task.
Abstract
Objective: To determine the functional connectivity of different EEG bands at the “baseline” situation (rest) and during mathematical thinking in children and young adults to study the maturation effect on brain networks at rest and during a cognitive task. Methods: Twenty children (8–12 years) and twenty students (21–26 years) were studied. The synchronization likelihood was used to evaluate the interregional synchronization of different EEG frequency bands in children and adults, at rest and during math. Then, graphs were constructed and characterized in terms of local structure (clustering coefficient) and overall integration (path length) and the “optimal” organization of the connectivity i.e., the small world network (SWN). Results: The main findings were: (i) Enhanced synchronization for theta band during math more prominent in adults. (ii) Decrease of the optimal SWN organization of the alpha2 band during math. (iii) The beta and especially gamma bands showed lower synchronization and signs of lower SWN organization in both situations in adults. Conclusion: There are interesting findings related to the two age groups and the two situations. The theta band showed higher synchronization during math in adults as a result of higher capacity of the working memory in this age group. The alpha2 band showed some SWN disorganization during math, a process analog to the known desynchronization. In adults, a dramatic reduction of the connections in gray matter occurs. Although this maturation process is probably related to higher efficiency, reduced connectivity is expressed by lower synchronization and lower mean values of the graph parameters in adults. Hum Brain Mapp 2009. © 2007 Wiley-Liss, Inc.

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Complex brain networks: graph theoretical analysis of structural and functional systems

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TL;DR: Graph theoretical analysis of neuroimaging data is growing rapidly and could potentially provide a relatively simple but powerful quantitative framework to describe and compare whole human brain structural and functional networks under diverse experimental and clinical conditions.
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Graph theoretical modeling of brain connectivity.

TL;DR: This review will focus mainly on recent findings concerning graph theoretical analysis of human brain networks with a variety of imaging modalities, exploring whether graph-based brain network analysis could yield reliable biomarkers for disease diagnosis and treatment.
References
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Journal ArticleDOI

EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis

TL;DR: In this article, it is suggested to adjust the frequency windows of alpha and theta for each subject by using individual alpha frequency as an anchor point, based on this procedure, a consistent interpretation of a variety of findings is made possible.
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The brainweb: phase synchronization and large-scale integration.

TL;DR: It is argued that the most plausible candidate is the formation of dynamic links mediated by synchrony over multiple frequency bands.
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Efficient Behavior of Small-World Networks

TL;DR: It is shown that the underlying general principle of their construction is in fact a small-world principle of high efficiency, which gives a clear physical meaning to the concept of "small world," and also a precise quantitative analysis of both weighted and unweighted networks.
Journal ArticleDOI

High gamma power is phase-locked to theta oscillations in human neocortex.

TL;DR: The results indicate that transient coupling between low- and high-frequency brain rhythms coordinates activity in distributed cortical areas, providing a mechanism for effective communication during cognitive processing in humans.
Journal ArticleDOI

A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs

TL;DR: It is concluded that correlated, low-frequency oscillations in human fMRI data have a small-world architecture that probably reflects underlying anatomical connectivity of the cortex, and could provide a physiological substrate for segregated and distributed information processing.
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