Dynamic brain network configurations during rest and an attention task with frequent occurrence of mind wandering

Abstract

Mind wandering (MW) has become a prominent topic of neuroscientific investigation due to the importance of understanding attentional processes in our day‐to‐day experiences. Emerging evidence suggests a critical role for three large‐scale brain networks in MW: the default network (DN), the central executive network (CEN), and the salience network (SN). Advances in analytical methods for neuroimaging data (i.e., dynamic functional connectivity, DFC) demonstrate that the interactions between these networks are not static but dynamically fluctuate over time (Chang & Glover, 2010, NeuroImage, 50(1), 81–98). While the bulk of the evidence comes from studies involving resting‐state functional MRI, a few studies have investigated DFC during a task. Direct comparison of DFC during rest and task with frequent MW is scarce. The present study applies the DFC method to neuroimaging data collected from 30 participants who completed a resting‐state run followed by two runs of sustained attention to response task (SART) with embedded probes indicating a high prevalence of MW. The analysis identified five DFC states. Differences between rest and task were noted in the frequency of three DFC states. One DFC state characterized by negative DN–CEN/SN connectivity along with positive CEN–SN connectivity was more frequently observed during task vs. rest. Two DFC states, one of which was characterized by weaker connectivity between networks, were more frequently observed during rest than task. These findings suggest that the dynamic relationships between brain networks may vary as a function of whether ongoing cognitive activity unfolds in an “unconstrained” manner during rest or is “constrained” by task demands.

Reductions in task positive neural systems occur with the passage of time and are associated with changes in ongoing thought

“…statistics to highlight the association between hidden neural dynamics and self-generated cognitive states [30][31][32][33] . It also complements work suggesting that the brain flexibly is temporarily reconfigured into states that support task performance 13 by providing an understanding of how these states are disengaged over time following a task event.…”

Mindfulness training preserves sustained attention and resting state anticorrelation between default‐mode network and dorsolateral prefrontal cortex: A randomized controlled trial

“…We (Denkova et al, 2019;Greicius et al, 2003;Piccoli et al, 2015), and across individual adults stronger resting-state DMN-DLPFC anticorrelation is associated with greater working memory capacity (Hampson et al, 2010;Keller et al, 2015;Whitfield-Gabrieli et al, 2018) and faster processing speed (Ng et al, 2016). Conversely, such DMN-DLPFC anticorrelation is reduced when cognitive control processes are clinically impaired in individuals with ADHD (Hoekzema et al, 2014;Mattfeld et al, 2014) or schizophrenia (Whitfield-Gabrieli et al, 2009).…”

“…Further, lesions to DLPFC enhance distractibility and impair attention and goal‐directed behavior (Chao & Knight, 1998; Woods & Knight, 1986). The DMN is associated with mind‐wandering and task‐irrelevant thoughts (Christoff, Gordon, Smallwood, Smith, & Schooler, 2009; Denkova et al, 2019; Fox & Raichle, 2007; Posner, Park, & Wang, 2014). Greater activations in core nodes of the DMN, namely medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), and bilateral parietal cortices, lead to reduced vigilance and increased mind wandering (Christoff et al, 2009; Hinds et al, 2013).…”

“…Such functional segregation can also be measured as a negative correlation (or anticorrelation) in functional connectivity patterns between core nodes of these two networks. Indeed, studies have found enhanced anticorrelation between the DMN and DLPFC during attention‐demanding tasks (Denkova et al, 2019; Greicius et al, 2003; Piccoli et al, 2015). Further, stronger anticorrelations between the DMN and a network of task‐activated regions, including DLPFC, were associated with more consistent performance on an attention‐demanding task (Kelly et al, 2008).…”

Evoked and intrinsic brain network dynamics in children with autism spectrum disorder

“…Time series extracted from the six ROIs during task and resting-state runs were converted to z statistics and then concatenated into a single group matrix (787 TR × 44 subjects) following previous studies ( Hutchison and Morton, 2015 , Denkova et al, 2019 ). The concatenated matrix was subjected to k -means clustering.…”