envelope_correlation(data, combine='mean', orthogonalize='pairwise', verbose=None)¶
Compute the envelope correlation.
- dataarray_like, shape=(n_epochs, n_signals, n_times) | generator
The data from which to compute connectivity. The array-like object can also be a list/generator of array, each with shape (n_signals, n_times), or a
stc.datawill be used). If it’s float data, the Hilbert transform will be applied; if it’s complex data, it’s assumed the Hilbert has already been applied.
- combine‘mean’ |
How to combine correlation estimates across epochs. Default is ‘mean’. Can be None to return without combining. If callable, it must accept one positional input. For example:
combine = lambda data: np.median(data, axis=0)
- orthogonalize‘pairwise’ |
Whether to orthogonalize with the pairwise method or not. Defaults to ‘pairwise’. Note that when False, the correlation matrix will not be returned with absolute values.
New in version 0.19.
- corrndarray, shape ([n_epochs, ]n_nodes, n_nodes)
The pairwise orthogonal envelope correlations. This matrix is symmetric. If combine is None, the array with have three dimensions, the first of which is
Hipp JF, Hawellek DJ, Corbetta M, Siegel M, Engel AK (2012) Large-scale cortical correlation structure of spontaneous oscillatory activity. Nature Neuroscience 15:884–890
Khan S et al. (2018). Maturation trajectories of cortical resting-state networks depend on the mediating frequency band. Neuroimage 174:57–68