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Brain functional networks become more connected as amyotrophic lateral sclerosis progresses: a source level magnetoencephalographic study.


ABSTRACT: This study hypothesizes that the brain shows hyper connectedness as amyotrophic lateral sclerosis (ALS) progresses. 54 patients (classified as "early stage" or "advanced stage") and 25 controls underwent magnetoencephalography and MRI recordings. The activity of the brain areas was reconstructed, and the synchronization between them was estimated in the classical frequency bands using the phase lag index. Brain topological metrics such as the leaf fraction (number of nodes with degree of 1), the degree divergence (a measure of the scale-freeness) and the degree correlation (a measure of disassortativity) were estimated. Betweenness centrality was used to estimate the centrality of the brain areas. In all frequency bands, it was evident that, the more advanced the disease, the more connected, scale-free and disassortative the brain networks. No differences were evident in specific brain areas. Such modified brain topology is sub-optimal as compared to controls. Within this framework, our study shows that brain networks become more connected according to disease staging in ALS patients.

SUBMITTER: Sorrentino P 

PROVIDER: S-EPMC6120607 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Brain functional networks become more connected as amyotrophic lateral sclerosis progresses: a source level magnetoencephalographic study.

Sorrentino Pierpaolo P   Rucco Rosaria R   Jacini Francesca F   Trojsi Francesca F   Lardone Anna A   Baselice Fabio F   Femiano Cinzia C   Santangelo Gabriella G   Granata Carmine C   Vettoliere Antonio A   Monsurrò Maria Rosaria MR   Tedeschi Gioacchino G   Sorrentino Giuseppe G  

NeuroImage. Clinical 20180804


This study hypothesizes that the brain shows hyper connectedness as amyotrophic lateral sclerosis (ALS) progresses. 54 patients (classified as "early stage" or "advanced stage") and 25 controls underwent magnetoencephalography and MRI recordings. The activity of the brain areas was reconstructed, and the synchronization between them was estimated in the classical frequency bands using the phase lag index. Brain topological metrics such as the leaf fraction (number of nodes with degree of 1), the  ...[more]

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