Testing different ICA algorithms and connectivity analyses on MS patients

  • Multiple sclerosis (MS) is a progressive neurological disorder that affects the central nervous system. Functional magnetic resonance imaging (fMRI) has been employed to track the course and disease progression in patients with MS. The two main aims of this study were to apply in a data-driven approach the independent component analysis (ICA) in the spatial domain to depict the active sources and to look at the effective connectivity between the identified spatial sources. Several ICA algorithms have been proposed for fMRI data analysis. In this study, we aimed to test two well characterized algorithms, namely, the fast ICA and the complex infomax algorithms, followed by two effective connectivity algorithms, namely, Granger causality (GC) and generalized partial directed coherence (GPDC), to illustrate the connections between the spatial sources in patients with MS. The results obtained from the ICA analyses showed the involvement of the default mode network sources. The connectivityMultiple sclerosis (MS) is a progressive neurological disorder that affects the central nervous system. Functional magnetic resonance imaging (fMRI) has been employed to track the course and disease progression in patients with MS. The two main aims of this study were to apply in a data-driven approach the independent component analysis (ICA) in the spatial domain to depict the active sources and to look at the effective connectivity between the identified spatial sources. Several ICA algorithms have been proposed for fMRI data analysis. In this study, we aimed to test two well characterized algorithms, namely, the fast ICA and the complex infomax algorithms, followed by two effective connectivity algorithms, namely, Granger causality (GC) and generalized partial directed coherence (GPDC), to illustrate the connections between the spatial sources in patients with MS. The results obtained from the ICA analyses showed the involvement of the default mode network sources. The connectivity analyses depicted significant changes between the two applied algorithms. The significance of this study was to demonstrate the robustness of the analyzed algorithms in patients with MS and to validate them before applying them on larger datasets of patients with MS.show moreshow less

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Metadaten
Author:Muthuraman MuthuramanORCiDGND, T. Anjum, Amgad Droby, Vinzenz Fleischer, Sarah Christina Reitz, Kidist Gebremariam Mideksa, Gerhard Schmidt, F. Zipp, Sergiu Groppa
URN:urn:nbn:de:bvb:384-opus4-1102772
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/110277
ISBN:978-1-4244-9271-8OPAC
Parent Title (English):2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 25-29 August 2015, Milan, Italy
Publisher:IEEE
Place of publication:Piscataway, NJ
Editor:Sergio Cerutti, Paolo Bonato, Colin J. H. Brenan, Anna Maria Bianchi, Silvestro Micera
Type:Conference Proceeding
Language:English
Year of first Publication:2015
Publishing Institution:Universität Augsburg
Release Date:2023/12/20
First Page:4314
Last Page:4317
DOI:https://doi.org/10.1109/embc.2015.7319349
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Professur für Informatik in der Medizintechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht