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01-03-2008 | Original Article

Cortical Network Dynamics during Foot Movements

Authors: Fabrizio De Vico Fallani, Laura Astolfi, Febo Cincotti, Donatella Mattia, Maria Grazia Marciani, Andrea Tocci, Serenella Salinari, Herbert Witte, Wolfram Hesse, Shangkai Gao, Alfredo Colosimo, Fabio Babiloni

Published in: Neuroinformatics | Issue 1/2008

Abstract

The present work intends to evaluate the dynamics of the cerebral networks during the preparation and the execution of the foot movement. In order to achieve this objective, we have used mathematical tools capable of estimating the cortical activity via high-resolution EEG techniques. Afterwards we estimated, the instantaneous relationships occurring among the time-series of sixteen regions of interest (ROIs) in the Alpha (7–12 Hz) and Beta (13–29 Hz) band through the adaptive multivariate autoregressive models. Eventually, we evaluated the weighted-topology of the cerebral networks by calculating some theoretical graph indexes. The results show that the main structural changes are encoded in the highest spectral contents (Beta band). In particular, during the execution of the foot movement the cingulate motor areas (CM) work as network “hubs” presenting a large amount of outgoing links to the other ROIs. Moreover, the connectivity pattern changes its structure according to the different temporal stages of the task. In particular, the communication between the ROIs reaches its highest level of efficiency during the preparation of the foot movement, as revealed by the “small-world” property of the network, which is characterized by the presence of abundant clustering connections combined with short average distances between the cortical areas.

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Title: Cortical Network Dynamics during Foot Movements
Authors: Fabrizio De Vico Fallani
Laura Astolfi
Febo Cincotti
Donatella Mattia
Maria Grazia Marciani
Andrea Tocci
Serenella Salinari
Herbert Witte
Wolfram Hesse
Shangkai Gao
Alfredo Colosimo
Fabio Babiloni
Publication date: 01-03-2008
Publisher: Humana Press Inc
Published in: Neuroinformatics / Issue 1/2008
Print ISSN: 1539-2791
Electronic ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-007-9006-6

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