# mne.beamformer.dics_source_power¶

mne.beamformer.dics_source_power(info, forward, noise_csds, data_csds, reg=0.01, label=None, pick_ori=None, verbose=None)

Dynamic Imaging of Coherent Sources (DICS).

Calculate source power in time and frequency windows specified in the calculation of the data cross-spectral density matrix or matrices. Source power is normalized by noise power.

NOTE : This implementation has not been heavily tested so please report any issues or suggestions.

Parameters: info : dict Measurement info, e.g. epochs.info. forward : dict Forward operator. noise_csds : instance or list of instances of CrossSpectralDensity The noise cross-spectral density matrix for a single frequency or a list of matrices for multiple frequencies. data_csds : instance or list of instances of CrossSpectralDensity The data cross-spectral density matrix for a single frequency or a list of matrices for multiple frequencies. reg : float The regularization for the cross-spectral density. label : Label | None Restricts the solution to a given label. pick_ori : None | ‘normal’ If ‘normal’, rather than pooling the orientations by taking the norm, only the radial component is kept. verbose : bool, str, int, or None If not None, override default verbose level (see mne.verbose). stc : SourceEstimate | VolSourceEstimate Source power with frequency instead of time.

Notes

The original reference is: Gross et al. Dynamic imaging of coherent sources: Studying neural interactions in the human brain. PNAS (2001) vol. 98 (2) pp. 694-699