PartialDirectedCoherence

Code to derive the different variants of Partial Directed Coherence (PDC). A detailed description of these functional connectivity measures can be found in:

Baccalá, L. A., & Sameshima, K. (2014). Partial directed coherence. Methods in brain connectivity inference through multivariate time series analysis, 57-73.

The function relies on routines and codes from the Source Information Flow Toolbox (SIFT):

Mullen, T. R. (2014). The dynamic brain: Modeling neural dynamics and interactions from human electrophysiological recordings. University of California, San Diego. Available from ProQuest Dissertations & Theses A&I. (1619637939). Retrieved from https://search.proquest.com/docview/1619637939?accountid=17206

Delorme, A., Mullen, T., Kothe, C., Akalin Acar, Z., Bigdely-Shamlo, N., Vankov, A., & Makeig, S. (2011). EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing. Computational intelligence and neuroscience, vol. 2011, Article ID 130714, 12 pages.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.