Brain connectivity analysis with ICA

• Main Author: Yang, Kanyan
• Other Authors: Rajapakse, Jagath Chandana
• Format: Theses and Dissertations
• Published: 2008
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision; DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
• Online Access: https://hdl.handle.net/10356/2546
• Institution: Nanyang Technological University

Functional 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.