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Stochastic Hodgkin-Huxley Model: 14x28D Langevin Simulation (Pu and Thomas, 2020).

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Matlab code for Pu and Thomas' Neural Computation paper

Fast and Accurate Langevin Simulations of Stochas-tic Hodgkin-Huxley Dynamics

  1. Figure 1 (HH diagram) is generated by the tex code.
  2. Figure 2 (4D and 14D HH models) can be generated from codes in folder "Figure2". It takes roughly 3-5 minutes to run the script Fig2.m on a laptop.
  3. Figure 3 (convergence to the multinomial submanifold) can be generated by codes in folder "Figure3". It takes roughly 3-5 minutes to run the script Fig3.m on a laptop.
  4. Figure 4 (Edge importance under voltage clamp) is reproduced with permission from Figs. 10 & 13 of Schmidt and Thmas (2014) paper. Code is reproduced with permission.
  5. Figure 5 (edge importance under current clamp) can be reproduced from codes in folder "Figure5".
    • to generate figure 5, one needs to run hundreds repeated simulations, high performance computing is recommended
    • one can modify the code gene_data_SS.m to generate as many samples as desired
    • fig5data.mat can be loaded and viewed by plot_fig5.m
  6. Figure 6 (pathwise equivalency) can be generated by the code Fig6.m, which takes roughly 1-2 minutes to run on a laptop.
  7. Figures 7, 8 and 9, as well as codes for generating Table 3, are included in the folder "All_models"
    • cluster computing or high performance computing is recommended for generating the data for these tables and figures
    • details of the simulation for the paper is specified in Section 5
    • simulation efficiency is computed through the same laptop computer; the time might be different using different machines but the ratio should be roughly the same
    • since the data for all plots in Figs. 7-9 and Table 3 are more than 500 MB, data for the plots are not uploaded here but one should be able to re-generate the data with the provided code

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