Graph Theoretical Characteristics of EEG-Based Functional Brain Networks in Patients With Epilepsy: The Effect of Reference Choice and Volume Conduction - Anastasiadou, Maria N.; Christodoulakis, Manolis; Papathanasiou, Eleftherios S.; Papacostas, Savvas S.; Hadjipapas, Avgis; Mitsis, Georgios D. (Frontiers in Neuroscience, 2019)
It is well established that both volume conduction and the choice of recording reference (montage) affect the correlation measures obtained from scalp EEG, both in the time and frequency domains. As a result, a number of correlation measures have been proposed aiming to reduce these effects. In the present work, we aim to establish the extent to which widely used volume conduction and montage choice influence the properties of brain network graph theoretic measures over a wide range of time scales, as obtained from long-duration clinical scalp EEG data (multiple days) from patients with epilepsy, whereby the number of electrodes is low. We compare two standard and commonly used linear correlation measures, cross-correlation in the time domain and coherence in the frequency domain, with measures that account for volume conduction: corrected cross-correlation, imaginary coherence, phase lag index, and weighted phase lag index. We show that the graphs constructed with corrected cross-correlation and WPLI are more stable across different choices of reference. Also, we demonstrate that all the examined correlation measures revealed similar periodic patterns in the obtained graph measures when the bipolar and common reference (Cz) montage were used. This includes circadian-related periodicities (e.g. a clear decrease in connectivity during awake times and increase during sleep) as well as shorter periodicities (3 and 5 hours). On the other hand, different results were obtained when the average reference montage was used in combination with standard cross-correlation, coherence, imaginary coherence and PLI, which are likely due to the low number of electrodes and inadequate electrode coverage of the scalp. Finally, we demonstrate that, overall, seizure onset is correlated to the aforementioned periodicities. This suggests that even in the standard clinical setting of EEG recording in epilepsy, where only a limited number of scalp EEG measurements are available, graph-theoretic quantification of periodic patterns using appropriate montage and correlation measures corrected for volume conduction provides useful insights into seizure onset.