# Multi-Graph Assessment of Temporal and Extratemporal Lobe Epilepsy in Resting-State fMRI
## 4 Discussion
### Network Analysis Comparisons  
Further investigation regarding the eight brain sectors revealed that hub regions are dependent on the type of graph. For instance, the subcortical regions had almost zero mean degree hub probability in the undirected graphs of Pearson and MI, while in the directed graph of Granger causality, their role was crucial across all three groups. The causal influence exerted from deep brain structures to the cortical areas has been highlighted in various studies [81; 82]. Although, this causality has not been found before in graph characteristics, or it was not as prominent as in our study. On the other hand, the subcortical regions presented non-zero probability values both in the mean betweenness hub probability of the Pearson connectivity graphs and in the mean local efficiency hub probability of the MI graphs, in all groups. In the directed graphs of Granger causality, all the groups present high hub probability levels in the subcortical area, based on the degree centrality and the local efficiency. This suggests that the subcortical regions are significant in every type of graph, but their role differs based on the metric. In the Pearson graph, the subcortical regions may display a higher role as network mediators, minimizing the distances in the interaction between other regions. The review of [PERSON] and [PERSON] proposes the meta-networks of the brain, based both on anatomic and functional connectivity, and suggested the mediating role of subcortical regions (especially thalamus, amygdala, and hippocampus) in pathways supporting higher cognitive functions [83]. In the MI and Granger graphs, the mean local efficiency hub probability denotes that the removal of those nodes would affect the efficient information flow in the whole brain network. Further, in the Granger graphs, this brain sector includes most of the hubs based on the degree centrality, suggesting that the regions with most connections (inflow and outflow) are included in the deep brain structures. On this premise, the study of [PERSON] and [PERSON] [84] analyzed the anatomical connectivity of the brain, showing that the subcortical regions of the thalamus, putamen, and hippocampus are recognized as hubs using all types of centralities mentioned in our study. They concluded by classifying those regions as 'provincial hubs,' meaning that their value is profound mainly at a local level. In our study, we confirm this regional importance of the subcortical regions, both in the MI and Granger causality graphs, where the values of the mean local efficiency hub probability are high compared to the other brain sectors. Concerning the mean local efficiency hub probability of the Brain Sectors in the Pearson graphs, the TLE patients show near-zero values, with statistical differences compared to the ETLE group in the cingulate cortex and the frontal lobe, as well as in the motor area compared to the controls. This outcome, combined with the fact that we found the lowest global efficiency in the TLE group compared to the other two groups, suggests that the brain regions of TLE patients do not communicate locally in such an efficient way, and this nodal observation also affects the overall efficiency in the communication of the brain network. The study of [PERSON] et al. [85] verifies this, suggesting that TLE patients present lower nodal efficiency in many regions, resulting in significant reduction of global efficiency metrics compared to healthy controls. On the other hand, the mean local efficiency hub probability of the ETLE patients presents similar values with the control group. The divergence observed between the two types of epilepsy may include information regarding the complexity of the epileptic network, where the different patterns of hub reorganization might correspond to the attempt of the epileptic brain to mitigate neurocognitive deficits.