## 4 Discussion
\begin{table}
\begin{tabular}{c c c} \hline
**Coefficients** & **SCWT** & **MAT** \\ \hline  & Intrahemispheric & \\ \(\Delta\delta_{1}\)-coherence & \(-23\) (\(-40\); \(-6\)) & \(-19\) (\(-35\); \(-4\)) \\ \(\Delta\delta_{2}\)-coherence & \(-21\) (\(-33\); \(-8\)) & \(-10\) (\(-20\); \(1\)) \\ \(\Delta\delta\)-coherence & \(-7\) (\(-17\); \(2\)) & \(-4\) (\(-11\); \(2\)) \\ \(\Delta\theta\)-coherence & \(-2\) (\(-10\); \(2\)) & \(2\) (\(-3\); \(7\)) \\  & Interhemispheric & \\ \(\Delta\delta_{1}\)-coherence & \(-6\) (\(-30\); \(32\)) & \(-9\) (\(-32\); \(27\)) \\ \(\Delta\delta_{2}\)-coherence & \(7\) (\(-26\); \(57\)) & \(29\) (\(0\); \(81\)) \\ \(\Delta\delta\)-coherence & \(26\) (\(8\); \(55\)) & \(30\) (\(11\); \(70\)) \\ \(\Delta\theta\)-coherence & \(6\) (\(-3\); \(16\)) & \(13\) (\(4\); \(26\)) \\ \hline \end{tabular}
\end{table} 
Table 1: Medians and the first and third quartiles of distributions of individual differences between the coefficients of interhemispheric and intrahemispheric coherence of EEG leads at the stages of stress and rest. (stage S2), the changes in interhemispheric couplings are more pronounced in the \(\delta_{2}\)-, \(\delta\)-, and \(\theta\)-ranges than in the \(\delta_{1}\)-range. In general, it can be seen that changes in interhemispheric couplings are more pronounced across all frequency ranges during the MAT than during the SCWT; these can be explained by the greater cognitive load on volunteers during SCWT. An increase or decrease in the coherence between a pair of EEG leads at different stages of the experiment was, in most cases, accompanied by a similar dynamic in the indices of directional coupling (Figure 4). For example, a decrease in intrahemispheric coherence between EEG leads in the \(\delta_{1}\)-range (Figure 4a) and the \(\delta_{2}\)-range (Figure 4b) during the SCWT correlates with a decrease in directional coupling from the frontal, central, and parietal leads to occipital leads within the same hemisphere (Figure 4e,f). A decrease in interhemispheric coherence in the \(\delta_{1}\)-range during the MAT (Figure 4a) correlates with a decrease in directional coupling between the frontal, central, and parietal EEG leads of the left and right hemispheres (Figure 4e). An increase in intrahemispheric coherence between EEG leads in the \(\delta_{2}\)-range during the MAT correlates with an increase in unidirectional coupling from the leads of the right hemisphere to the leads of the left hemisphere. Good agreement between the results of the coupling analysis obtained using the methods based on estimation of phase coherence coefficients and directional coupling indices increases the reliability of our results due to the qualitative difference between these methods. It should be noted that for most pairs of EEG leads, the revealed directional couplings were bidirectional (lines in Figure 4e-h). In cases where couplings between the leads were identified as unidirectional (arrows in Figure 4e-h), it is difficult to systematize the structure of such directional couplings. We assume that the couplings between the pairs of EEG leads are mainly bidirectional, but the insufficient sensitivity of the method did not allow us in some cases to identify a statistically significant coupling in the opposite direction. The obtained results allow us to conclude that the considered methods are efficient for the detection of stress. Moreover, these methods are able to distinguish the states of stress caused by pattern recognition (SCWT) and intensive solving of formal tasks (MAT). Note that during SCWT (stage S1) the phase coherence coefficients decrease in the \(\delta_{2}\)-range, while during MAT (stage S2) these coefficients increase in this range (Figure 3b,f). At the same time, under stress caused by SCWT, an increase in interhemispheric couplings in the \(\delta\)-range is observed, while interhemispheric couplings in the \(\delta_{1}\)-range do not change (Figure 4).