#Welcome
This folder contains MATLAB code and data files from
Koppe G, Toutounji H, Kirsch P, Lis S, Durstewitz D. (2019). Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI. PLOS Computational Biology
Copyright: 2019 Georgia Koppe, Dept. of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University 2019 Daniel Durstewitz, Dept. of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University
The folder 'code_PLRNN_BOLD_SSM' found in the zip-file contains code for the probabilistic fMRI state space model ('PLRNN-BOLD-SSM' and 'LDS-BOLD-SSM'), as well as experimental data described in the journal article. For an example of how to start the code and run the algorithm on the given data set (including 'Algorithm-1'), please run 'Main_data_example.m'.
The folder 'code_PLRNN_SSM' found in the zip-file contains code for the probabilistic state space model ('PLRNN-SSM' and 'LDS-SSM'), as well as self-generated benchmark system data obtained from the Lorenz and van der Pol systems described in the journal article. For an example of how to start the code and run the algorithm on the given data set (including 'Algorithm-1'), please run 'Main_benchmark_example.m'.
In case of questions or comments, please contact georgia.koppe@zi-mannheim.de or daniel.durstewitz@zi-mannheim.de.
Note that the code may be modified with additional options being included with time.