Before revision:  Subsequently, we construct a statistical framework to highlight brain connections that are selected with probability well above chanceand we estimate their sCCA loadings based on a de-noising approach  .
After revision:  Randomised lasso is used to alleviate the dependency of the sCCA on the lasso parameters and control the false positive rate. Subsequently, the binomial distribution is exploited to set a threshold statistic that reflects whether a connection is selected or rejected by chance. Finally, we estimate the sCCA loadings based on a de-noising approach .