How the brain negotiates divergent executive processing demands: Evidence of network reorganization in fleeting brain states

M. Liu, R.A. Backer, R.C. Amey, C.E. Forbes

Research output: Contribution to JournalArticleAcademicpeer-review


© 2021During performance in everyday contexts, multiple networks draw from shared executive resources to maintain attention, regulate arousal, and solve problems. At times, requirements for attention and self-regulation appear to be in competition. How does the brain attempt to resolve conflicts arising from such divergent processing demands? Here we demonstrate that the brain is capable of managing multiple processes via rapidly cycling between functional brain states over time, as it is typically regarded. Treating the brain as a complex system, comprising relationships within and between functional networks, we implemented Hidden Markov Modeling (HMM) on electroencephalographic (EEG) data to identify nonlinear brain states in both intra and internetwork synchrony that produced better performance for women subjects who were tasked with solving difficult problems under autobiographically-relevant, evaluative stress. Prior work often found that emotion-regulation and default-mode network (ERN and DMN) activity conflicted with the frontoparietal network's (FPN) ability to facilitate executive functioning necessary for problem solving. Contrastingly, we discovered that fleeting, nonlinear states dominated by FPN and ERN internetwork synchrony supported optimum performance generally, while during stress, states dominated by ERN and DMN intranetwork synchrony were more important for performance. These results imply that the brain may be capable of resolving competing processes through networks’ cooperative dynamics. Further, data suggests a novel role for DMN as a mechanism for integrating external threats with internal, self-referent processing during evaluative stress within the observed population.
Original languageEnglish
Article number118653
Publication statusPublished - 15 Dec 2021
Externally publishedYes


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