## 4 Discussion  
In this work, functional plasticity of the resting human brain underlying driving experience was evaluated using a newly proposed framework that combines functional connectivity with effective connectivity analysis. The results showed that, compared with nondrivers, the driver group established enhanced functional connectivity between the pre-SMA and several prefrontal regions. It was also found that driving-related changes were restricted to the pre-SMA and did not extend to the SMA proper. Effective connectivity analysis using spectral DCM further revealed the directionality of these connections, indicating that the pre-SMA had established a hierarchical organization with the other regions, i.e., in the context of predictive coding theory, the pre-SMA was located at a higher level, and the effective connections to the rest of the regions were inhibitory feedback connections. Particularly, the connection strength of pre-SMA\(\rightarrow\)ISFG was significantly enhanced in the drivers and exhibited significant classification ability to distinguish drivers from controls. Resting-state brain network analysis frequently requires the specification of regions of interest (ROIs). A common method uses atlases derived from structural boundaries. The main problem in using structural ROIs is that they are generally rather coarse and tend to combine functionally distinct ROIs [25; 38]. In this paper, we focused on the region of SMA, where the sub-regions of this area have been reported to show different structural [31] and functional connectivity [33] profiles. Therefore, by using a two-level segmentation algorithm we have proposed previously [36], the functionally distinct sub-regions (i.e., the pre-SMA and SMA proper) showing group-level consistency were obtained for further analysis (see Figure 1). Based on the respective time series of the pre-SMA and SMA proper, we then explored the group difference in functional connectivity between drivers and nondrivers. We found that the drivers showed stronger functional connectivity between the pre-SMA and several prefrontal regions, including the ISFG and the IOFC (approximating [PERSON]'s area 10, see Table 2). Driving is a highly complicated behavior that requires the simultaneous integration of lower-level tasks of action with higher-level cognitive processing and decision making [14]. It is suggested that the prefrontal cortex plays a pivotal role in switching between externally versus internally oriented thoughts, and maintaining the stable implementation of sustained mental plans [39; 40], whereas the pre-SMA is more responsible for complicated cognitive situations. Therefore, the integration of the pre-SMA and prefrontal cortex may equip humans with the ability to pursue a long-term driving plan and meanwhile respond to the demands of the immediate driving context. In addition, considering that prior experience can modify functional connectivity strength, the increased functional connectivity between the pre-SMA and the prefrontal regions \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Effective Connectivity** & \begin{tabular}{c} **Sensitivity** \\ **(\%)** \\ \end{tabular} & \begin{tabular}{c} **Specificity** \\ **(\%)** \\ \end{tabular} & \
\begin{tabular}{c} **Accuracy** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **Correlation** \\ **(\(p\) Value)** \\ \end{tabular} \\ \hline Pre-SMA\(\rightarrow\)pre-SMA & 80 & 60 & 70 & 0.3352 & 0.0172 \\ Pre-SMA\(\rightarrow\)IOFC & 65 & 55 & 60 & 0.0977 & 0.2744 \\ Pre-SMA\(\rightarrow\)ISFG & 80 & 65 & 72.5 & 0.4057 & 0.0047 \\ IOFC\(\rightarrow\)ISFG & 70 & 55 & 62.5 & 0.0556 & 0.3666 \\ ISFG\(\rightarrow\)ISFG & 60 & 55 & 57.5 & \(-\)0.2116 & 0.9050 \\ IMTG\(\rightarrow\)IOFC & 55 & 50 & 52.5 & 0.1609 & 0.1606 \\ IMTG\(\rightarrow\)IMTG & 80 & 45 & 62.5 & \(-\)0.0222 & 0.5542 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Predictive validity of the significant effective connectivity. may be caused by the persistent occupation of this neural circuit when driving.