Task-Related Effects on the Temporal and Spatial Dynamics of Resting-State Functional Connectivity in the Default Network

Recent evidence points to two potentially fundamental aspects of the default network (DN), which have been relatively understudied. One is the temporal nature of the functional interactions among nodes of the network in the resting-state, usually assumed to be static. The second is possible influences of previous brain states on the spatial patterns (i.e., the brain regions involved) of functional connectivity (FC) in the DN at rest. The goal of the current study was to investigate modulations in both the spatial and temporal domains. We compared the resting-state FC of the DN in two runs that were separated by a 45 minute interval containing cognitive task execution. We used partial least squares (PLS), which allowed us to identify FC spatiotemporal patterns in the two runs and to determine differences between them. Our results revealed two primary modes of FC, assessed using a posterior cingulate seed – a robust correlation among DN regions that is stable both spatially and temporally, and a second pattern that is reduced in spatial extent and more variable temporally after cognitive tasks, showing switching between connectivity with certain DN regions and connectivity with other areas, including some task-related regions. Therefore, the DN seems to exhibit two simultaneous FC dynamics at rest. The first is spatially invariant and insensitive to previous brain states, suggesting that the DN maintains some temporally stable functional connections. The second dynamic is more variable and is seen more strongly when the resting-state follows a period of task execution, suggesting an after-effect of the cognitive activity engaged during task that carries over into resting-state periods

Management of asthma in childhood: study protocol of a systematic evidence update by the Paediatric Asthma in Real Life (PeARL) Think Tank

IntroductionClinical recommendations for childhood asthma are often based on data extrapolated from studies conducted in adults, despite significant differences in mechanisms and response to treatments. The Paediatric Asthma in Real Life (PeARL) Think Tank aspires to develop recommendations based on the best available evidence from studies in children. An overview of systematic reviews (SRs) on paediatric asthma maintenance management and an SR of treatments for acute asthma attacks in children, requiring an emergency presentation with/without hospital admission will be conducted.Methods and analysisStandard methodology recommended by Cochrane will be followed. Maintenance pharmacotherapy of childhood asthma will be evaluated in an overview of SRs published after 2005 and including clinical trials or real-life studies. For evaluating pharmacotherapy of acute asthma attacks leading to an emergency presentation with/without hospital admission, we opted to conduct de novo synthesis in the absence of adequate up-to-date published SRs. For the SR of acute asthma pharmacotherapy, we will consider eligible SRs, clinical trials or real-life studies without time restrictions. Our evidence updates will be based on broad searches of Pubmed/Medline and the Cochrane Library. We will use A MeaSurement Tool to Assess systematic Reviews, V.2, Cochrane risk of bias 2 and REal Life EVidence AssessmeNt Tool to evaluate the methodological quality of SRs, controlled clinical trials and real-life studies, respectively. Next, we will further assess interventions for acute severe asthma attacks with positive clinical results in meta-analyses. We will include both controlled clinical trials and observational studies and will assess their quality using the previously mentioned tools. We will employ random effect models for conducting meta-analyses, and Grading of Recommendations Assessment, Development and Evaluation methodology to assess certainty in the body of evidence.Ethics and disseminationEthics approval is not required for SRs. Our findings will be published in peer reviewed journals and will inform clinical recommendations being developed by the PeARL Think Tank.PROSPERO registration numbers CRD42020132990, CRD42020171624.</p

LV2 – the secondary DN dynamic showing variable correlations.

<p>LV2 - The secondary resting-state spatiotemporal pattern of PCC correlations, showing a transition from relative stability of DN connectivity to switching between two different patterns of FC. A) The spatial pattern of FC seen in this LV. Activity in red regions (positive BSRs) is associated with increased activity in the PCC during those blocks with positive correlations between brain scores and PCC (seen in B), whereas increased activity in blue areas (negative BSRs) is correlated with increased activity in the PCC for blocks where the correlations are negative. B) Correlations across time. Rest1 shows relatively stable positive correlations between the PCC and other DN regions, while Rest2 shows switching between the two patterns of connectivity. Bars = 95% confidence intervals for the correlations.</p

Direct comparison of Rest1 and Rest2.

<p>Areas showing greater FC with PCC in Rest2 than Rest1, as found in the contrast analysis, and shown in red (BSRs>3.3). No negative BSRs met the threshold.</p

A time×run interaction analysis of Rest1/Task1/Task8/Rest2.

<p>Areas showing stronger FC with PCC in Rest2 relative to Rest1, and weaker FC in Task8 relative to Task1, as found in the interaction contrast analysis, and shown in red (BSRs>3.3). No negative BSRs met the threshold.</p

LV2 - Brain areas showing variable correlations with the PCC across time, during Rest2.

<p>MNI coordinates. BSR>3.3 is equivalent to p<0.001. Hem = hemisphere; PCC = posterior cingulate cortex, the seed used in the FC analysis. Labels in <i>italics</i> are regions positively correlated with the seed. See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013311#pone-0013311-g002" target="_blank">Figure 2</a>.</p

Correlation distributions in LV1 and LV2.

<p>Correlation values for all 10-sec blocks, sorted and plotted from lowest (most negative) to highest (most positive), to show the distributions in LV1 and LV2. A) LV1 – Rest1 correlations (squares) are not significantly different from Rest2 correlations (triangles). B) LV2 – Rest1 correlations (squares) are more positive than Rest2 correlations (triangles).</p

LV1 - Brain areas showing stable positive correlations with the PCC across time, for both Rest1 and Rest2.

<p>MNI coordinates. BSR>3.3 is equivalent to p<0.001. Hem = hemisphere; SMA = supplementary motor area; PCC = posterior cingulate cortex, the seed used in the FC analysis. See also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013311#pone-0013311-g001" target="_blank">Figure 1</a>.</p

LV1 – the primary DN dynamic showing stable correlations.

<p>LV1 - The primary resting-state spatiotemporal pattern of PCC correlations, showing positive FC across most of the ‘blocks’ in both resting runs. A) The spatial composition, capturing the DN. The red regions (with positive BSRs) indicate areas with positive correlation with the PCC seed (no negative BSRs met the threshold, value range displayed is consistent with <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013311#pone-0013311-g002" target="_blank">Figure 2</a>). B) The temporal structure – correlations of brain scores with seed activity across time for each 10 sec ‘block’. Bars = 95% confidence intervals. The spatial and temporal correlational patterns are very similar across Rest1 and Rest2.</p