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ICA-based sparse feature recovery from fMRI datasets

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Academic year: 2021

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Fig. 1. Scatter plot of samples projected in the subspace spanned by the two first ICs identified
Fig. 4. ROC plot: sensitivity as a function of false posi- posi-tive rate for synthetic data using Gaussian and super-Gaussian (kurtosis = 4) noise of varying σ, as well as for fMRI data.
Fig. 3. ICs estimated from fMRI data and thresholded using MELODIC’s mixture model, and our multivariate thresholding procedure

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