Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/2546
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dc.contributor.authorYang, Kanyanen
dc.date.accessioned2008-09-17T09:05:07Zen
dc.date.available2008-09-17T09:05:07Zen
dc.date.copyright2005en
dc.date.issued2005en
dc.identifier.citationYang, K. (2005). Brain connectivity analysis with ICA. Master’s thesis, Nanyang Technological University, Singapore.en
dc.identifier.urihttps://hdl.handle.net/10356/2546en
dc.description.abstractFunctional Magnetic Resonance Imaging (fMRI) is increasingly utilized to explore brain networks and neuronal interactions underlying brain functions. Although the concept of functional connectivity has been introduced to analyze brain connections for many years, this is a measure relying on the pattern of temporal correlations that exist between distinct neuronal units. In this research, we are going to extend the definition of brain connectivity into a higher-order statistical sense. Apart from this, two more contributions are made including a novel restoration model and a fully exploratory approach to investigating effective connectivity.en
dc.rightsNanyang Technological Universityen
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognitionen
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer visionen
dc.subjectDRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciencesen
dc.titleBrain connectivity analysis with ICAen
dc.typeThesisen
dc.contributor.supervisorRajapakse, Jagath Chandanaen
dc.contributor.schoolSchool of Computer Engineeringen
dc.description.degreeMASTER OF ENGINEERING (SCE)en
dc.identifier.doi10.32657/10356/2546en
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