Exploring the Interplay between BOLD Signal Variability, Complexity, static and dynamic Functional Brain Network Features during Movie Viewing

As the brain is dynamic and complex, knowledge of brain signal variability and complexity is crucial in our understanding of brain function. Recent resting-fMRI studies revealed links between BOLD signal variability or complexity with static/dynamics features of functional brain networks (FBN). However, no study has examined the relationships between these brain metrics. The association between brain signal variability and complexity is still understudied. Here we investigated the association between movie naturalistic-fMRI BOLD signal variability/complexity and static/dynamic FBN features using graph theory analysis. We found that variability positively correlated with fine-scale complexity but negatively correlated with coarse-scale complexity. Hence, variability and coarse-scale complexity correlated with static FC oppositely. Specifically, regions with high centrality and clustering coefficient were related to less variable but more complex signal. Similar relationship persisted for dynamic FBN, but the associations with certain aspects of regional centrality dynamics became insignificant. Our findings demonstrate that the relationship between BOLD signal variability, static/dynamic FBN with BOLD signal complexity depends on the temporal scale of signal complexity. Additionally, altered correlation between variability and complexity with dynamic FBN features may indicate the complex, time-varying feature of FBN and reflect how BOLD signal variability and complexity co-evolve with dynamic FBN over time.