The propagation of Cortico-Cortical Evoked Potentials (CCEPs) varies depending on numerous structural features of brain tissue. In this work, we show that combined dMRI-based connectivity enriched with microstructure data has the potential to measure cortico-cortical communication as it predicts CCEP-based effective connectivity. Our multiple linear regression model incorporates q-space indices like Q-space Inverse Variance, Non-Gaussianity and Return to Plane Probability with minimum streamline lengths obtained from tractography to predict delays and amplitudes of the P1 peaks in CCEPs. In our experiment, we use presurgical dMRI and intrasurgical ECoG recordings of 9 patients operated on brain tumor in the awake condition.
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