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26/01/2017

ISCB has featured a new research published by two researchers Inria

© Fabrizio De Vico Fallani

The International Society for Computational Biology has featured its "research highlights" a new research published last november by two researchers of the team-project Inria ARAMIS  and the Institut du Cerveau et de la Moelle. The paper deals with filtering information in brain networks.

In collaboration with the Queen Mary University of London, Fabrizio De Vico Fallani and Mario Chavez of the ARAMIS team have developed a novel analytical tool for facilitating the analysis of the intricate web of connections in the brain.

Complex brain networks are mainly estimated from empirical measurements. As a result, filtering procedures are typically adopted to prune the weakest connections. The structural properties of the thresholded networks depend on the number of remaining links and how to objectively fix such threshold is still an open issue. The two scientists propose a possible criterion to filter connectivity based on the optimization of fundamental properties in complex systems, such as efficiency and economy, and show that a general law can be derived. Given its generality, ECO can advance the ability to analyze biological networks inferred from experimentally obtained data.

Given its generality, the authors anticipate that ECO can advance the ability to analyze biological networks inferred from experimentally obtained data and extract network biomarkers underlying neural diseases. Based on the optimization of fundamental properties in complex systems, such as efficiency and economy, this method allows to effectively quantify the effects of mental disorders and neurological diseases on the structural and functional organization of the brain.

Keywords: Brain’s Activity Complex signals Brain image analysis ECO ISCB Aramis

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