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Evaluation of the Brain Network Organization From EEG Signals: A Preliminary Evidence in Stroke Patient
Author(s) -
De Vico Fallani Fabrizio,
Astolfi Laura,
Cincotti Febo,
Mattia Donatella,
la Rocca Daria,
Maksuti Elira,
Salinari Serenella,
Babiloni Fabio,
Vegso Balazs,
Kozmann Gyorgy,
Nagy Zoltan
Publication year - 2009
Publication title -
the anatomical record: advances in integrative anatomy and evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.678
H-Index - 62
eISSN - 1932-8494
pISSN - 1932-8486
DOI - 10.1002/ar.20965
Subject(s) - electroencephalography , stroke (engine) , psychology , neuroscience , medicine , physical medicine and rehabilitation , mechanical engineering , engineering
Abstract Synchronous brain activity in motor cortex in perception or in complex cognitive processing has been the subject of several studies. The advanced analysis of cerebral electro‐physiological activity during the course of planning (PRE) or execution of movement (EXE) in a high temporal resolution could reveal interesting information about the brain functional organization in patients following stroke damage. High‐power (128 channels) electroencephalography registration was carried out on 8 healthy subjects and on a patient with stroke with capsular lacuna in the right hemisphere. For activation of motor cortex, the finger tapping paradigm was used. In this preliminary study, we tested a theoretical graph approach to characterize the task‐related spectral coherence. All of the obtained brain functional networks were analyzed by the connectivity degree, the degree distribution, and efficiency parameters in the Theta, Alpha, Beta, and Gamma bands during the PRE and EXE intervals. All the brain networks were found to hold a regular and ordered topology. However, significant differences ( P < 0.01) emerged between the patient with stroke and the control subjects, independently of the neural processes related to the PRE or EXE periods. In the Beta (13–29 Hz) and Gamma (30–40 Hz) bands, the significant ( P < 0.01) decrease in global‐ and local‐efficiency in the patient's networks, reflected a lower capacity to integrate communication between distant brain regions and a lower tendency to be modular. This weak organization is principally due to the significant ( P < 0.01 Bonferroni corrected) increase in disconnected nodes together with the significant increase in the links in some other crucial vertices. Anat Rec, 292:2023–2031, 2009. © 2009 Wiley‐Liss, Inc.