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Small-world networks and neuropsychiatric disorders

Recall that a network is said to exhibit small-world property when it is characterized by a high degree of local interaction (presence of cliques) and few short cuts between the nodes. Mathematically, this is represented by what is known as a small-world coefficient, which is simply the ratio of the (normalized) clustering coefficient of a network to the (normalized) average path length.  
Several studies have shown that small-world configuration is essential for healthy brain function and a deviation from this may result in disorders. For instance , using EEG (see Figure  below) it was shown that in Alzheimer’s disease (AD), the clustering coefficient decreased in the lower alpha and beta bands, while the mean path length reduced in the lower alpha and gamma band, compared to controls [1]. However in case of frontotemporal lobe degeneration (FTLD), no significant difference with the controls was found. In this work, the authors used synchronization likelihood as a measure of functional connectivity between pairs of EEG electrodes. Overall, the authors reported that their results supported the disconnection hypothesis in AD, by demonstrating that deviation from SW networks towards a more random network results in less efficient information exchange between the brain areas.
In another study, again using EEG it was shown that , during a working memory task the control group exhibited small-world property, which was not seen in the schizophrenia group [2]. Similarly, deviation from small world networks have been implicated in Autism as well [3].
توضیحات و مطالب مرتبط با شبکه دنیای کوچک small world network
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فصل 18 اش هم عنوانش همزمانی EEG-fMRI

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10.1007@978-981-13-9113-2.pdf
13.9 MB
10.1007@978-981-13-9113-2.pdf