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Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

Figure 6

Dependence of performance level on network clustering, conditioning level and light scattering artifacts.

The color panels show the overall reconstruction performance level, quantified by TP (black, 0% true positives; white, 100% true positives), for different target ground-truth clustering coefficients and as a function of the used conditioning level. Five different reconstruction algorithms are compared: cross-correlation (XC), Granger Causality (GC) with order , Mutual Information (MI), and Transfer Entropy (TE) with Markov orders . The top row corresponds to simulations without artifacts, and the bottom row to simulations including light scattering. Reconstructions with linear methods perform well only in the absence of light scattering artifacts. TE reconstruction with shows the best overall reconstruction performance, even with light scattering and for any target clustering coefficient. An optimal reconstruction is obtained in a narrow range surrounding the conditioning value of .

Figure 6

doi: https://doi.org/10.1371/journal.pcbi.1002653.g006