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Inferring neural circuit structure from datasets of heterogeneous tuning curves

Fig 5

System identification of the SSN model from simulated tuning curve data using the cWGAN method and moment matching methods.

Top and bottom rows show the results of cWGAN and moment matching fits, respectively. (A) & (D): symmetric mean average percent error (sMAPE), Eq (44), of all parameters throughout training. (B) & (E): the (solid lines) and δJ_ab (shaded areas) parameters throughout training. The box to the right shows the true parameters as points () with error bars (δJ_ab). (C) & (F): σ_ab throughout training. Arrows to the right of the plot denote the true values of σ_ab; note that the E → I and I → I arrows occlude each other in panels C and F. In B-C and E-F colors represent connection-types as shown in the legend of B. The input heterogeneity parameter V (not plotted) converged to 0.100 for cWGAN, and to 0.116 for moment matching, compared to the value V = 0.1.

doi: https://doi.org/10.1371/journal.pcbi.1006816.g005