Functional connectivity: spatial patterns and covariance models of spontaneous activity

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.

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