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)
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)
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2018-03
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The deposited data sets contain:
- Simulated spike trains from a network of interacting neurons
- Two-photon calcium imaging data from the mouse auditory cortex (Kanold Lab, UMD)
- 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.