Optimizing Within-Subject Experimental Designs for jICA of Multi-Channel ERP and fMRI.

ABSTRACT: Joint independent component analysis (jICA) can be applied within subject for fusion of multi-channel event-related potentials (ERP) and functional magnetic resonance imaging (fMRI), to measure brain function at high spatiotemporal resolution (Mangalathu-Arumana et al., 2012). However, the impact of experimental design choices on jICA performance has not been systematically studied. Here, the sensitivity of jICA for recovering neural sources in individual data was evaluated as a function of imaging SNR, number of independent representations of the ERP/fMRI data, relationship between instantiations of the joint ERP/fMRI activity (linear, non-linear, uncoupled), and type of sources (varying parametrically and non-parametrically across representations of the data), using computer simulations.

SUBMITTER: Mangalathu-Arumana J 

PROVIDER: S-EPMC5787094 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature