| Literature DB >> 17315225 |
Fabrizio De Vico Fallani1, Laura Astolfi, Febo Cincotti, Donatella Mattia, Maria Grazia Marciani, Serenella Salinari, Jurgen Kurths, Shangkai Gao, Andrzej Cichocki, Alfredo Colosimo, Fabio Babiloni.
Abstract
The present work aims at analyzing the structure of cortical connectivity during the attempt to move a paralyzed limb by a group of spinal cord injured (SCI) patients. Connectivity patterns were obtained by means of the Directed Transfer Function applied to the cortical signals estimated from high resolution EEG recordings. Electrical activity were estimated in normals (Healthy) and SCI patients on twelve regions of interest (ROIs) coincident with Brodmann areas. Degree distributions showed the presence of few cortical regions with a lot of outgoing connections in all the cortical networks estimated irrespectively of the frequency band investigated. For both of the groups (SCI and Healthy), bilateral cingulate motor area (CMA) acts as hub transmitting information flows. The efficiency index, allowed to assert the ordered properties of such estimated cortical networks in both populations. The comparison of such estimated networks with those obtained from random networks, elicited significant differences (P < 0.05, Bonferroni-corrected for multiple comparisons). A statistical comparison (ANOVA) between SCI patients and healthy subjects showed a significant difference (P < 0.05) between the local efficiency of their respective networks. For three frequency bands (theta 4-7 Hz, alpha 8-12 Hz, and beta 13-29 Hz) the higher value observed in the spinal cord injured population entails a larger level of internal organization and fault tolerance. This fact suggests a sort of compensative mechanism as local response to the alteration in their MIF areas, which is probably due to the indirect effects of the spinal injury. (copyright) 2007 Wiley-Liss, Inc.Entities:
Mesh:
Year: 2007 PMID: 17315225 PMCID: PMC6871447 DOI: 10.1002/hbm.20353
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.038