Criticality in probabilistic models of spreading dynamics in brain networks: Epileptic seizures
Fig 3
The proposed probabilistic model captures the spread timing in patient-specific Epileptor network models.
The plots show the results for patient-specific network P1, EZ-61. A A stochastic realization of an Epileptor network simulation in this patient-specific network. The vertical axis specifies the node index in the patient-specific network while the horizontal axis is time centered at the seizure onset time in the EZ node (node 61). Red diamonds specify the expected seizure onset time predicted by the model. B Linear relation between mean seizure onset times in Epileptor networks versus the mean onset time in the model for all points in phase space in which we observe full spread (yellow area in Fig 2). We note that, while a linear relation between the seizure onset times is observed for all points in phase space, the slope of the line varies depending on w and E. We rescaled all the lines to align with the diagonal. C Seizure-onset ordering in Epileptor networks versus the proposed model for all points in phase space in which we observe full spread. Red dots specify the 95 percentile of the data.