From correlation to causation: Estimating effective connectivity from zero-lag covariances of brain signals
Fig 2
Networks inferred from a simulated Ornstein-Uhlenbeck process.
A shows the original network. B shows the network inferred with our new method from the zero-lag covariances. White and black entries indicate true negative (TN) and true positive (TP) connections, blue and red entries indicate false negative (FN) and false positive (FP) connections, respectively. In this example, the performance measures are AUC = 0.98, PRS = 0.97 and PCC = 0.95. C depicts the sample covariance (functional connectivity) matrix directly estimated from the data. In C, as a consequence of symmetry, the number of wrongly estimated connections is quite high, the performance measures are AUC = 0.93, PRS = 0.54, and PCC = 0.29. D shows the Receiver Operating Characteristic Curve and the Precision Recall Curve for the networks estimated from zero-lag covariance Gest in blue/orange and of the functional connectivity C in red/cyan. The areas under these curves are the AUC and PRS, respectively.