## 4 Discussion
Second, our investigation of brain network dynamics relied on specific, well-established cortical parcellations [30; 31]. While these atlases are prevalent in functional MRI research, facilitating comparability with the vast body of existing literature, they represent only a subset of available parcellation schemes. These parcellation, while foundational, is now relatively dated [57]. Using additional or more contemporary atlases, potentially derived from different modalities or based on different organizational principles, could offer further insights into the robustness and generalizability of our findings across various network definitions. Third, in our cross-frequency coupling (CFC) analysis, we focused on mean values and metrics reflecting the upper tail of the distribution (i.e., maximum values). This decision was motivated by the observation that neurophysiological measures often exhibit skewed distributions where the mean alone provides an incomplete representation, potentially obscuring functionally relevant extreme values [13]. While we interpret these as speculatively representing baseline and peak coupling capacity, respectively, this is a simplification. A more exhaustive characterization of the entire CFC distribution, or the exploration of alternative metrics beyond the mean and maximum, could provide a more nuanced understanding of CFC dynamics. Future studies could also benefit from explicitly modelling the skewness or other distributional properties [49]. The observed correlation between the brain age gap derived from the cross-frequency coupling (CFC) and performance specifically on the picture priming task, but not other cognitive tasks, warrants further consideration. While the precise reasons for this specificity remain fully elucidated, the neurophysiological underpinnings of picture priming offer plausible explanations. Picture priming tasks rely on the efficient processing and integration of visual object information, processes known to involve coordinated activity across several brain regions where CFC plays a crucial modulatory role. For instance, the fusiform gyrus, a key region for object recognition and consistently implicated in picture priming, exhibits enhanced theta/alpha band evoked power for repeated stimuli, suggesting that CFC within this region may facilitate more efficient neural processing during priming [58]. Similarly, the inferior temporal cortex, critical for visual object memory, shows enhanced theta/alpha-beta phase-amplitude coupling during visual working memory, indicating a potential role for CFC in maintaining primed representations [59]. Furthermore, successful priming often involves attentional modulation and decision-making processes supported by the prefrontal cortex, where theta-gamma CFC is implicated in coordinating large-scale network activity [59; 60]. Finally, the parietal cortex, involved in attention and integrating sensory information with working memory, demonstrates theta-gamma phase synchronization during memory matching, a related cognitive function [61]. Therefore, the sensitivity of the CFC-derived brain age gap to picture priming performance might stem from its capacity to capture the integrity of these distributed, CFC-mediated neural interactions that are particularly critical for the rapid recognition and facilitated processing inherent to priming effects, potentially more so than for the cognitive domains assessed by our other tasks. In conclusion, our study demonstrates associations between cross-frequency coupling (CFC) and semantic memory performance, framed within the context of brain age. By defining the brain age gap (BAG) relative to typical ageing trajectories within resting-state fMRI networks, we specifically investigated how different characteristics of network-specific CFC relate to cognition.