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Transfer Entropy Reconstruction and Labeling of Neuronal Connections from Simulated Calcium Imaging

Figure 3

Optimal network reconstruction.

A ROC curves for the reconstruction of a network with both excitatory and inhibitory connections active, supposing to know a priori information about neuronal type. GTE is first applied to the “E+I” data. Next, following Dale's principle and exploiting the available information on neuronal type, links are classified according to their excitatory (red) or inhibitory (blue) nature. B ROC curves for the best possible identification of excitatory and inhibitory connections, when information on neuronal type is unaccessible. Excitatory links (red) are identified by adding together the Transfer Entropy scores of simulations run in “E–only” and “E+I” conditions, and later thresholding them. Inhibitory links (blue) are identified by computing the difference in Transfer Entropy scores between the runs with inhibition present and blocked. Inset: fraction of excitatory and inhibitory neurons correctly identified from these ROC curves. Results were not significantly different from random guess (see Methods). All the results were averaged over different network realizations. The shaded areas in the main plots, as well as the error bars in the inset, correspond to 95% confidence intervals.

Figure 3

doi: https://doi.org/10.1371/journal.pone.0098842.g003