Investigating the functional neural network dynamics of cognitive-affective action planning during threat processing

Introduction The current investigation used functional neuroimaging data from four different tasks involving threatening/fearful faces and screams to understand the functional organization of neural networks. Methods Emphasis was placed on graph theory metrics of both local connectivity (participation coefficient, betweenness centrality) and global connectivity (global efficiency, modularity) to assess intra- and inter-network connectivity across a highly parcellated (412 nodes) brain template. A total of 124 participants (57% female; M Age = 22.06) were included in the investigation. Both mass univariate linear mixed effects models and multivariate classification via support vector machine were employed to uncover the nature of network dynamics across 8 well described intrinsic connectivity networks (ICNs). Results Our findings suggest that a diffuse pattern of strengthened intra-network connectivity defined social threat processing. Univariate analyses exhibited a preponderance of nodes within the somatomotor network, indicating the potential for motor preparation during social threat processing. Multivariate classification exhibited more diffuse focal participation from limbic, default, visual, attentional, control and somatomotor ICNs. Conclusion Our results suggest the role of intra- and inter-network functional organization in response to threat and carries implications for viewing various networks through dynamic perspectives.