Validation of Shared and Specific Independent Component Analysis (SSICA) for Between-Group Comparisons in fMRI.

ABSTRACT: Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named "shared and specific independent component analysis" (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i.e., components that could be considered "specific" for a group or condition. Here, we investigated the performance of SSICA on realistic simulations, and task fMRI data and compared the results with one of the state-of-the-art group ICA approaches to infer between-group differences

SUBMITTER: Maneshi M 

PROVIDER: S-EPMC5037228 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature