(Georgia Institute of Technology, 2023-05-01)
Seeburger, Dolly
There is ambiguity in the literature about how large-scale brain networks contribute to focused attention. Part of the problem comes from the methods of analyses that treat the correlates of attention as a static and discrete measure when in actuality, attention fluctuates from moment to moment. This continuous change in attention is consistent with the dynamic changes in functional connectivity between brain regions involved in the internal and external allocation of attention (Liu & Dyun, 2013). Namely, the default mode network (DMN) and the task positive network (TPN)(Fox et al., 2005). In this study, I investigated how brain network activity varied across different levels of attentional focus (e.g., “zones”). Participants performed a finger-tapping task and, guided by previous research (Esterman et al., 2013), in-the-zone was marked by low reaction time variability and out-of-the-zone as the inverse. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliably observed spontaneous low-frequency fluctuations), I found that the activity between DMN and TPN was more anti-correlated during in-the-zone states versus out-of-the-zone states. Further investigation showed that it is the fronto-parietal control network (FPCN) of the TPN that drives the differentiation. During in-the-zone periods, FPCN synchronized with the dorsal attention network, while during out-of-the-zone periods, FPCN synchronized with DMN. In contrast, the ventral attention network synchronized more closely with DMN during in-the-zone periods compared to out-of-the-zone periods. These findings suggest that time-varying functional connectivity in the low-frequency can tell us how different networks of the brain work together during periods of sustained attention.