mne.minimum_norm.make_inverse_resolution_matrix#

mne.minimum_norm.make_inverse_resolution_matrix(forward, inverse_operator, method='dSPM', lambda2=0.1111111111111111, verbose=None)[source]#

Compute resolution matrix for linear inverse operator.

Parameters:

forwardinstance of Forward: Forward Operator.
inverse_operatorinstance of InverseOperator: Inverse operator.
method‘MNE’ | ‘dSPM’ | ‘sLORETA’: Inverse method to use (MNE, dSPM, sLORETA).
lambda2float: The regularisation parameter.
verbosebool | str | int | None: Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

resmat: array, shape (n_orient_inv * n_dipoles, n_orient_fwd * n_dipoles): Resolution matrix (inverse operator times forward operator). The result of applying the inverse operator to the forward operator. If source orientations are not fixed, all source components will be computed (i.e. for n_orient_inv > 1 or n_orient_fwd > 1). The columns of the resolution matrix are the point-spread functions (PSFs) and the rows are the cross-talk functions (CTFs).