Intrinsic network static and dynamic functional connectivity associated with induced affect

The examination of the neural mechanisms of affect has shifted from a functional localization approach towards a distributed network neuroscience approach. The present study examined the topology of brain networks relevant to affective processing [i.e. the salience (SN), default mode (DMN), ventral attention (VAN), dorsal attention (DAN), and frontoparietal (FPN) networks] during a novel fMRI-based affect-induction task in which participants (N = 73) mentally visualized neutral, positive, and negative self-nominated acquaintances. We used graph-theory metrics to compute the static (i.e. mean) and dynamic (i.e. time-varying) functional integration of networks with the rest of the brain (using participation coefficient) and within-network coherence (using within-module degree). Static DAN within-module degree differentiated the negative from the neutral condition, whereas dynamic VAN participation coefficient differentiated the negative from the positive condition. These results are consistent with the constructionist account that emotions emerge from flexible network configurations and contribute to growing network-based understandings of affective processing.