ABSTRACTBackgroundThe Nicotine Withdrawal Syndrome (NWS) includes affective and cognitive disruptions whose incidence and severity vary across time during acute abstinence. However, most network-level neuroimaging employs static measures of resting state functional connectivity (rsFC), assuming time-invariance, and unable to capture dynamic brain-behavior relationships. Recent advances in rsFC signal processing allow characterization of “time varying connectivity” (TVC), which characterizes network communication between sub-networks that reconfigure over the course of data collection. As such, TVC may more fully describe network dysfunction related to the NWS.MethodsTo isolate alterations in the frequency and diversity of communication across network boundaries as a function of acute nicotine abstinence we scanned cigarette smokers in the nicotine sated and abstinent states and applied a previously-validated method to characterize TVC at a network and nodal level within the brain.ResultsDuring abstinence, we found brain wide decreases in the frequency of interactions between network nodes in different modular communities (i.e. temporal flexibility; TF). In addition, within a subset of the networks examined the variability of these interactions across community boundaries (i.e. spatiotemporal diversity; STD) also decreased. Finally, within two of these networks the decrease in STD was significantly related to NWS clinical symptoms.ConclusionsEmploying multiple measures of TVC in a within subjects’ design, we characterized a novel set of changes in network communication and link these changes to specific behavioral symptoms of the NWS. These reductions in TVC provide a meso-scale network description of the relative inflexibility of specific large-scale brain networks as a result of acute abstinence.
Time varying connectivity across the brain changes as a function of nicotine abstinence state