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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _update_individual(X, W, R, gamma):
 """Update the individual components `S_i`. Parameters X : list of 2D arrays, element i has shape=[voxels_i, timepoints] Each element in the list contains the fMRI data for alignment of one subject. W : list of array, element i has shape=[voxels_i, features] The orthogonal transforms (mappings) :math:`W_i` for each subject. R : array, shape=[features, timepoints] The shared response. gamma : float, default: 1.0 Regularization parameter for the sparseness of the individual components. Returns ------- S : list of array, element i has shape=[voxels_i, timepoints] The individual component :math:`S_i` for each subject. """

        subjs = len(X)
        S = []
        for i in range(subjs):
            S.append(RSRM._shrink(X[i] - W[i].dot(R), gamma))
        return S