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Dynamic coupling of Whole-Brain Neuronal and Neurotransmitter Systems

Kringelbach, M. L., Cruzat, J., Cabral, J., Knudsen, G. M., Carhart-Harris, R. L., Whybrow, P. C., Logothetis N. K. & Deco, G.
(2020) Proceedings of the National Academy of Sciences

Barcelona,Spain. March, 2020.

First, run LEiDA_PsiloData.m to extract the probabilistic metastable substate (PMS) space for the empirical psilocybin BOLD data (placebo and active condition) using the leading eigenvector dynamics analysis (LEiDA) method.

Second, run optim_placebo_psilo.m for fitting the whole-brain model to the PMS space of the placebo condition of psilocybin using only the neuronal system. Use the output from LEiDA_PsiloData.m. This yields a global neuronal coupling parameter (G=1.6). Use read_G_cluster.mat to visualize the results.

Third, proceed to study the role of the neurotransmitter dynamical system by coupling both systems in the model run neuromodulador2D_psilo_raphenorm.m using the output from LEiDA_PsiloData.m and incorporating the connectivity of the raphe nucleus. Use read_Gw_2D_cluster.m to visualize the results.

Further, for finding the optimum fit of mutually coupled whole-brain model as a function of excitatory and inhibitory coupling parameters for when the system is disconnected (Ws E and I =0), use psilo_w_0.m, and use psilo_w_optimum.m for finding the most significantly optimal fit to the empirical PMS. Use read_single_w.m to visualize both outputs.

Finally, for the various manipulations to the model use manipulation_psilo_raphenorm.m and read_manipulation.m for visualization.