A group model for stable multi-subject ICA on fMRI datasets

@article{Varoquaux2010AGM,
  title={A group model for stable multi-subject ICA on fMRI datasets},
  author={Ga{\"e}l Varoquaux and Sepideh Sadaghiani and Philippe Pinel and Andreas Kleinschmidt and J B Poline and Bertrand Thirion},
  journal={NeuroImage},
  year={2010},
  volume={51},
  pages={288-299}
}
Spatial Independent Component Analysis (ICA) is an increasingly used data-driven method to analyze functional Magnetic Resonance Imaging (fMRI) data. To date, it has been used to extract sets of mutually correlated brain regions without prior information on the time course of these regions. Some of these sets of regions, interpreted as functional networks, have recently been used to provide markers of brain diseases and open the road to paradigm-free population comparisons. Such group studies… Expand
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