Abstract
The mechanisms for how large-scale brain networks contribute to sustained attention are unknown. Attention fluctuates from moment to moment, and this continuous change is consistent with dynamic changes in functional connectivity between brain networks involved in the internal and external allocation of attention. In this study, we investigated how brain network activity varied across different levels of attentional focus (i.e., “zones”). Participants performed a finger-tapping task, and guided by previous research, in-the-zone performance or state was identified by low reaction time variability and out-of-the-zone as the inverse. In-the-zone sessions tended to occur earlier in the session than out-of-the-zone blocks. This is unsurprising given the way attention fluctuates over time. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliable, network-level low-frequency fluctuations), we found that the activity between the default mode network (DMN) and task positive network (TPN) is significantly more anti-correlated during in-the-zone states versus out-of-the-zone states. Furthermore, it is the frontoparietal control network (FPCN) switch that differentiates the two zone states. Activity in the dorsal attention network (DAN) and DMN were desynchronized across both zone states. During out-of-the-zone periods, FPCN synchronized with DMN, while during in-the-zone periods, FPCN switched to synchronized with DAN. In contrast, the ventral attention network (VAN) synchronized more closely with DMN during in-the-zone periods compared with out-of-the-zone periods. These findings demonstrate that time-varying functional connectivity of low frequency fluctuations across different brain networks varies with fluctuations in sustained attention or other processes that change over time.
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Parts of the analyses were preregistered at https://osf.io/tcvgd. Data and materials for the experiment are available at https://osf.io/45ayg/?view_only=7238b505ee664b1f9d930e72a41080f9. Scripts for the QPP algorithm are openly available at https://github.com/GT-EmoryMINDlab/QPPLab. The rest of the preregistered analyses are beyond the scope of this paper and have yet to be completed.
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Seeburger, D.T., Xu, N., Ma, M. et al. Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task. Cogn Affect Behav Neurosci 24, 111–125 (2024). https://doi.org/10.3758/s13415-024-01156-1
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DOI: https://doi.org/10.3758/s13415-024-01156-1