DocumentCode
663003
Title
Which method should be used for brain connectivity analysis?
Author
Bucolo, M. ; Rance, Mariela ; Muscarello, Antonella ; Spampinato, Alfio ; Baeuchl, Christian ; Flor, Herta
Author_Institution
Dept. of Electr. Electron. & Comput. Sci. Eng., Univ. of Catania, Catania, Italy
fYear
2013
fDate
6-8 Nov. 2013
Firstpage
541
Lastpage
544
Abstract
One possible way to examine brain connectivity is to study correlations between signals recorded from different areas. The recent trends couple the signal processing based on data-driven mathematical methods with graph analysis performed on the connectivity matrix. The connectivity matrices can be evaluated by using several methods, and different toolboxes are available. The aim of the proposed platform is to create an embedded environment where it is possible to study brain connectivity through different methods and at the same time to compare the results. For this purpose different procedures are developed: from frequency and lag selection in the case of time or frequency varying analyses, to binary graph creation and binary and weighted graph comparisons. This software is realized with a high level of modularity, making it possible to integrate new analysis methods and clustering approaches.
Keywords
brain; graph theory; matrix algebra; medical signal processing; pattern clustering; binary graph comparisons; binary graph creation; brain connectivity analysis; clustering approach; connectivity matrix; data-driven mathematical methods; frequency varying analysis; graph analysis; signal processing; time varying analysis; weighted graph comparisons; Coherence; Computational modeling; Correlation; Histograms; Market research; Software; Time-frequency analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on
Conference_Location
San Diego, CA
ISSN
1948-3546
Type
conf
DOI
10.1109/NER.2013.6695991
Filename
6695991
Link To Document