Dataset Information

Functional connectivity in the social brain across childhood and adolescence.

ABSTRACT: Previous research has characterized a collection of neural regions which support social-cognitive processes. While this 'social brain' is often described as a cohesive unit, it has been largely assessed with univariate methodologies, which cannot account for functional relationships 'between' brain regions, and therefore cannot test the idea of the social brain as a network. In the present work, we utilized a multi-method approach to empirically assess the functional architecture of the social brain. Fifty participants (ages 8-16) completed a social evaluation task during an functional imaging scan. Results from three unique functional connectivity methodologies demonstrated that social brain regions show strong functional relationships, while also interfacing with non-social regions, suggesting that future work should consider network relationships between social brain regions in addition to traditional univariate approaches. We probed, but did not find age-related differences in social brain network organization, demonstrating that this functional architecture is in place by late childhood.

SUBMITTER: McCormick EM

PROVIDER: S-EPMC6123525 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Functional connectivity in the social brain across childhood and adolescence.

McCormick Ethan M EM van Hoorn Jorien J Cohen Jessica R JR Telzer Eva H EH

Social cognitive and affective neuroscience 20180901 8

Previous research has characterized a collection of neural regions which support social-cognitive processes. While this 'social brain' is often described as a cohesive unit, it has been largely assessed with univariate methodologies, which cannot account for functional relationships 'between' brain regions, and therefore cannot test the idea of the social brain as a network. In the present work, we utilized a multi-method approach to empirically assess the functional architecture of the social b ...[more]

PMID: 30085317

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Project description:The longitudinal study of typical neurodevelopment is key for understanding deviations due to specific factors, such as psychopathology. However, research utilizing repeated measurements remains scarce. Resting-state functional magnetic resonance imaging (MRI) studies have traditionally examined connectivity as 'static' during the measurement period. In contrast, dynamic approaches offer a more comprehensive representation of functional connectivity by allowing for different connectivity configurations (time varying connectivity) throughout the scanning session. Our objective was to characterize the longitudinal developmental changes in dynamic functional connectivity in a population-based pediatric sample. Resting-state MRI data were acquired at the ages of 10 (range 8-to-12, n = 3,327) and 14 (range 13-to-15, n = 2,404) years old using a single, study-dedicated 3 Tesla scanner. A fully-automated spatially constrained group-independent component analysis (ICA) was applied to decompose multi-subject resting-state data into functionally homogeneous regions. Dynamic functional network connectivity (FNC) between all ICA time courses were computed using a tapered sliding window approach. We used a k-means algorithm to cluster the resulting dynamic FNC windows from each scan session into five dynamic states. We examined age and sex associations using linear mixed-effects models. First, independent from the dynamic states, we found a general increase in the temporal variability of the connections between intrinsic connectivity networks with increasing age. Second, when examining the clusters of dynamic FNC windows, we observed that the time spent in less modularized states, with low intra- and inter-network connectivity, decreased with age. Third, the number of transitions between states also decreased with age. Finally, compared to boys, girls showed a more mature pattern of dynamic brain connectivity, indicated by more time spent in a highly modularized state, less time spent in specific states that are frequently observed at a younger age, and a lower number of transitions between states. This longitudinal population-based study demonstrates age-related maturation in dynamic intrinsic neural activity from childhood into adolescence and offers a meaningful baseline for comparison with deviations from typical development. Given that several behavioral and cognitive processes also show marked changes through childhood and adolescence, dynamic functional connectivity should also be explored as a potential neurobiological determinant of such changes.

Project description:Neonatal brain injury may impact brain development and lead to lifelong functional impairments. Hypoxic-ischemic encephalopathy (HIE) and congenital heart disease (CHD) are two common causes of neonatal brain injury differing in timing and mechanism. Maturation of whole-brain neural networks can be quantified during development using diffusion magnetic resonance imaging (dMRI) in combination with graph theory metrics. DMRI of 35 subjects with CHD and 62 subjects with HIE were compared to understand differences in the effects of HIE and CHD on the development of network topological parameters and functional outcomes. CHD newborns had worse 12-18 month language (P<0.01) and 30 month cognitive (P<0.01), language (P = 0.05), motor outcomes (P = 0.01). Global efficiency, a metric of brain integration, was lower in CHD (P = 0.03) than in HIE, but transitivity, modularity and small-worldness were similar. After controlling for clinical factors known to affect neurodevelopmental outcomes, we observed that global efficiency was highly associated with 30 month motor outcomes (P = 0.02) in both groups. To explore neural correlates of adverse language outcomes in CHD, we used hypothesis-based and data-driven approaches to identify pathways with altered structural connectivity. We found that connectivity strength in the superior longitudinal fasciculus (SLF) tract 2 was inversely associated with expressive language. After false discovery rate correction, a whole connectome edge analysis identified 18 pathways that were hypoconnected in the CHD cohort as compared to HIE. In sum, our study shows that neonatal structural connectivity predicts early motor development after HIE or in subjects with CHD, and regional SLF connectivity is associated with language outcomes. Further research is needed to determine if and how brain networks change over time and whether those changes represent recovery or ongoing dysfunction. This knowledge will directly inform strategies to optimize neurologic functional outcomes after neonatal brain injury.

Dataset Information

Functional connectivity in the social brain across childhood and adolescence.

Publications

Functional connectivity in the social brain across childhood and adolescence.

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