Though the organization of functional brain networks is modular at its core, modularity does not capture the full range of dynamic interactions between individual brain areas nor at the level of subnetworks. In this paper we present a hierarchical model that represents both flexible and modular aspects of intrinsic brain organization across time by constructing spatiotemporally flexible subnetworks. We also demonstrate that segregation and integration are complementary and simultaneous events. The method is based on combining the instantaneous phase synchrony analysis (IPSA) framework with community detection to identify a small, yet representative set of subnetwork components at the finest level of spatial granularity. At the next level, subnetwork components are combined into spatiotemporally flexibly subnetworks where temporal lag in the recruitment of areas within subnetworks is captured. Since individual brain areas are permitted to be part of multiple interleaved subnetworks, both modularity as well as more flexible tendencies of connectivity are accommodated for in the model. Importantly, we show that assignment of subnetworks to the same community (integration) corresponds to positive phase coherence within and between subnetworks, while assignment to different communities (segregation) corresponds to negative phase coherence or orthogonality. Together with disintegration, i.e. the breakdown of internal coupling within subnetwork components, orthogonality facilitates reorganization between subnetworks. In addition, we show that the duration of periods of integration is a function of the coupling strength within subnetworks and subnetwork components which indicates an underlying metastable dynamical regime. Based on the main tendencies for either integration or segregation, subnetworks are further clustered into larger meta-networks that are shown to correspond to combinations of core resting-state networks. We also demonstrate that subnetworks and meta-networks are coarse graining strategies that captures the quasi-cyclic recurrence of global patterns of integration and segregation in the brain. Finally, the method allows us to estimate in broad terms the spectrum of flexible and/or modular tendencies for individual brain areas.
Objectives
To investigate differences in brain volumes between children born extremely preterm and term born controls at term age and at 10 years of age.
Study design
Children born extremely preterm (EPT), up to 26 weeks and 6 days gestational age, in Stockholm between January 1 2004 to March 31 2007 were included in this population-based cohort study. A total of 45 EPT infants were included at term age and 51 EPT children were included at 10 years of age. There were 27 EPT children included at both time points. Two different control groups were recruited; 15 control infants were included at term age and 38 control children at 10 years of age. The primary outcomes were the grey and white matter volumes. Linear regression, adjusted for intracranial volume and sex, was used.
Results
At term age, the extremely preterm infants had significantly smaller grey matter volume compared to the control infants with an adjusted mean difference of 5.0 cm3 and a 95% confidence interval of −8.4 to −1.5 (p = 0.004). At 10 years of age the extremely preterm children had significantly smaller white matter volume compared to the control children with an adjusted mean difference of 6.0 cm3 and a 95% confidence interval of −10.9 to −1.0 (p = 0.010).
Conclusion
Extremely preterm birth was associated with reduced grey matter volume at term age and reduced white matter volume at 10 years of age compared to term born controls.
Aim
Little is known about the prevalence of discrete white matter abnormalities (WMA) beyond the first years in children born extremely preterm (EPT) and the relation to neurodevelopmental outcomes. Our aim was to investigate the prevalence of discrete WMA in children born EPT and the relationship to neonatal white matter injuries (WMI), white matter (WM) volume, WM diffusivity and neurodevelopment.
Methods
The study was a part of a longitudinal follow‐up study of EPT neonates. All children were scanned at Karolinska University hospital 2004–2007 (neonates) and 2014–2015 (children at 8–11 years). WMA was qualitatively assessed by visual inspection. Developmental assessment was conducted at 12 years.
Results
In total, 112 children (median age 10.3 years, 56 girls) underwent MRI of the brain (68 EPT, 45 controls). In the EPT group, a subset had MRI around term equivalent age (n = 61). In the EPT group, the prevalence of discrete WMA at 8–11 years was 52%. There was a positive association between WMI at TEA and 8–11 years. There was no association between WMI and WM volumes or diffusivity at 8–11 years. Discrete WMA was not related to neurodevelopmental outcomes.
Conclusion
Discrete WMA was prevalent in children born EPT at 8–11 years but were not related to neurodevelopmental outcomes.
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