Algorithms and models for extracting salient and reproducible spatial features from the correlation structure of functional MRI images without using a paradigm, such as in resting-state studies
We have introduced a multivariate random effects group model to conduct multi-subject ICA with good reproducibility.
We formulate ICA as a sparse-recovery problem to give statistical control on the extracted brain maps base on a probabilistic model of the noise based on sole assumption that the interesting latent factors are sparsely-activated.
