# Diagnosing Schizophrenia Using Effective Connectivity of Resting-State EEG Data
## 3 Results and Discussion  
Using the Relief algorithm, Table 2 shows the \(N_{\text{r}}=10\) most discriminating features between SCZ and HC that provided the highest performance, where the second column of the table indicates the frequency band of the features and the third column shows the areas of the brain that the EC between them using STE is selected as a discriminating feature. For example, from the first row of the table, the first feature is the directed EC from C3 to T3 at \(\theta\) frequency band. The illustration of these selected features is shown in Figure 2. The number of features is considerably lower than 106 training samples at each fold that will prevent over-fitting (the feature to the number of training samples ratio is 10/106 \(\times\) 100 = 9.43%). From Table 2, four of the selected features are from the connectivity between the occipital areas at different frequency bands (features 4-6, 10). The other features are from left centro-temporal (features 1 and 9), frontal (feature 7), fronto-temporal (feature 8) and parieto-temporal (features 2 and 3), which were also identified in previous studies. Several studies verify a significant alteration in these areas and their connection in SCZs compared to HCs. Here, we briefly describe the outcomes of some of the most recent studies. [PERSON] et al. [60] conducted a systematic review that reports the results of the relevance of schizophrenia to the occipital lobe. They found out there is enough evidence that supports the concept of a decrease in the volume of the occipital lobe in SCZs. In another study, [PERSON] et al. [61] showed that the prevalence of occipital bending is nearly three times higher among SCZs in comparison to HCs. [PERSON] et al. [62] found a significant decrease in SCZs' source activities in comparison to HCs, especially in the \begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature \#** & **Frequency Band** & **Effective Connectivity Feature** \\ \hline
1 & \(\theta\) & C3 to T3 \\
2 & \(\theta\) & F3 to T3 \\
3 & \(\theta\) & P4 to T4 \\
4 & \(\theta\) & O1 to O2 \\
5 & \(\theta\) & O1 to O2 \\
6 & \(\alpha\) & O1 to O2 \\
7 & \(\beta\) & Fp1 to F4 \\
8 & \(\beta\) & F8 to T4 \\
9 & \(\beta\) & C3 to T3 \\
10 & \(\beta\) & O1 to O2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The 10 discriminating features between SCZ and HC groups. Figure 2: A rough schematic drawing which shows the selected features by connections (solid thick blue lines). -medial frontal area, superior temporal gyrus, and temporo-parietal junction (TPJ)) using the recorded event-related potentials (ERPs) in response to auditory oddball paradigms. [PERSON] et al. [63] applied a new form of multivariate synchronization analysis called the S-estimator to the high-density resting-state EEG data of SCZs and HCs. They revealed higher synchronization across the left fronto-centro-temporal locations and right fronto-entro-temporal locations in SCZs than in HCs. [PERSON] et al. [64] found that SCZs have a greater complexity than HCs in fronto-centro-temporal regions using multiscale entropy in resting-state EEG activity. [PERSON] et al. [65] acquired 3T MRI scans from SCZs and HCs. They revealed that SCZs have significantly smaller bilateral superior temporal gyrus volumes than HCs. [PERSON] et al. [66] found significantly smaller hemodynamic changes in SCZs than in HCs in the ventro-lateral prefrontal cortex and the anterior part of the temporal cortex (VLPFC/aTC) and dorso-lateral prefrontal cortex and frontopolar cortex (DLPFC/FPC) regions using 52-channel near-infrared spectroscopy (NIRS). [PERSON] et al. [67] used the Lempel-Ziv algorithm to assess the complexity of EEG signals in SCZs. They found a higher complexity in the resting-state EEG signals of SCZs at the right frontal area. Using a multivariable TE (MTE), [PERSON] et al. [68] discovered the brain dysfunction in EC for SCZs in the EEG signals of the oddball task that deteriorated in the parietal and frontal lobes.