Experimental Data from Sheikhattar et al. (2018) Extracting neuronal functional network dynamics via adaptive Granger causality analysis, Proceedings of the National Academy of Sciences (PNAS), 2018 (www.pnas.org/cgi/doi/10.1073/pnas.1718154115)

The deposited data sets contain: 1) Simulated spike trains from a network of interacting neurons 2) Two-photon calcium imaging data from the mouse auditory cortex (Kanold Lab, UMD) 3) Single-unit spike data from the ferret auditory and prefrontal cortices (Neural Systems Lab, UMD) Please refer to readme.txt for further details. These data are used in the following article: A. Sheikhattar, S. Miran, J. Liu, J. B. Fritz, S. A. Shamma, P. O. Kanold, and B. Babadi (2018). Extracting neuronal functional network dynamics via adaptive Granger causality analysis, Proceedings of the National Academy of Sciences (PNAS), 2018 (www.pnas.org/cgi/doi/10.1073/pnas.1718154115) and are disseminated for public use in the spirit of easing reproducibility. The MATLAB implementation of the algorithms used in this work are deposited on Github at https://github.com/Arsha89/AGC Analysis