## 4 Discussion  
To our knowledge, this is the first study that has applied the novel technology of graph neural networks (GNNs) in this domain to investigate structural brain changes in children with trauma exposure and comorbid psychopathologies. To this aim, we collected and analyzed MRI-based brain data from participants with significant trauma exposure and from controls and applied a whole-brain, ROI-based GNN approach to analyze their brain constructional patterns. The analysis revealed notable differences in network patterns between the two groups. A simple comparison of mean densities across brain regions using \(t\)-tests showed significant differences in areas such as the middle temporal gyrus, where the control group exhibited higher mean density compared to the trauma-exposed group, and the left inferior temporal gyrus, with the control group again showing higher density compared to the trauma-exposed group. These findings highlighted specific brain regions with pronounced density variation between the trauma-exposed and control groups. However, by applying GNNs, we extended these results to uncover deeper, non-linear patterns by accounting for the  
Figure 4: Filtered brain networks for trauma-exposed (**top**) and control (**bottom**) groups. The intensity of the blue color in the figure represents the importance of the connections. The numbers correspond to the ROI indices based on the AAL atlas. complex and intrinsic connectivity between brain regions, providing a more comprehensive understanding of the underlying network differences. By applying the GNN training process, the trauma-exposed group exhibited a simpler network structure, as evidenced by higher and more consistent reconstruction loss. In contrast, the control group demonstrated more diverse and complex network patterns, suggesting greater variability and richness in brain connectivity. These findings indicate that the GNN model effectively captured and distinguished the underlying patterns in brain structures related to trauma exposure and comorbid psychopathologies, providing meaningful insights into the network differences between the two groups. The simpler network patterns observed in the trauma-exposed group may reflect neural adaptations to chronic stress or trauma. Research has suggested that prolonged exposure to stress during critical developmental periods can disrupt typical neural connectivity patterns, leading to more rigid and less adaptive networks [24]. This may result from the heightened allostatic load, where the brain reallocates resources to prioritize survival-oriented processes, such as hypervigilance or threat detection, at the expense of higher-order cognitive and emotional functions [25]. In this context, the reduced network variability and complexity in the trauma-exposed group may be indicative of impaired neuroplasticity, limiting the brain's ability to adapt to novel stimuli or environments. At the ROI level, the control group showed higher node importance in brain regions typically associated with general functions, such as the right lingual gyrus for visual perception [26], which may reflect the normal patterns of neuro-cognitive functions in adolescence [27]. In contrast, the trauma-exposed group exhibited high node importance in regions related to cognitive and emotional regulation, particularly the posterior cerebellum (Cerebellum 7b) [28]. This region is known to play a key role in integrating cognitive and emotional processes under conditions of stress [29]. These findings align with clinical observations of children with trauma exposure, who often exhibit difficulties in flexible problem-solving [30], emotional regulation [31], and social adaptation [32]. The prominence of the posterior cerebellum in the trauma-exposed group may reflect neural adaptations to trauma, highlighting its increased role in compensating for stress-related disruptions [33].