Dynamic functional connectivity of neurocognitive networks in children

Abstract

The human brain is highly dynamic, supporting a remarkable range of cognitive abilities that emerge over the course of development. While flexible and dynamic coordination between neural systems is firmly established for children, our understanding of brain functional organization in early life has been built largely on the implicit assumption that functional connectivity (FC) is static. Understanding the nature of dynamic neural interactions during development is a critical issue for cognitive neuroscience, with implications for neurodevelopmental pathologies that involve anomalies in brain connectivity. In this work, FC dynamics of neurocognitive networks in a sample of 146 youth from varied sociodemographic backgrounds were delineated. Independent component analysis, sliding time window correlation, and k-means clustering were applied to resting-state fMRI data. Results revealed six dynamic FC states that re-occur over time and that complement, but significantly extend, measures of static FC. Moreover, the occurrence and amount of time spent in specific FC states are related to the content of self-generated thought during the scan. Additionally, some connections are more variable over time than are others, including those between inferior parietal lobe and precuneus. These regions contribute to multiple networks and likely play a role in adaptive processes in childhood. Age-related increases in temporal variability of FC among neurocognitive networks were also found. Taken together, these findings lay the groundwork for understanding how variation in the developing chronnectome is related to risk for neurodevelopmental disorders. Understanding how brain systems reconfigure with development should provide insight into the ontogeny of complex, flexible cognitive processes. Hum Brain Mapp 38:97-108, 2017. © 2016 Wiley Periodicals, Inc.

Keywords: brain development; central executive network; default mode network; fMRI; independent component analysis; intrinsic activity; intrinsic connectivity; resting-state; salience network; state variability.

Figure 1

Core neurocognitive networks. Group independent component analysis was used to parcellate the brain into intrinsic connectivity networks (ICNs). See Supporting Information Table S1 for color key and more detailed information on each component ICN. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 2

Static functional connectivity (FC) of core neurocognitive networks in children. FC was averaged for all participants for the entire length of the resting‐state scan to produce the static correlation matrix. Intrinsic connectivity networks (ICNs) are labeled with their corresponding component number. See Supporting Information Table S1 for more detailed information on each component. Abbreviations: left, L; right, R; middle frontal gyrus, MiFG; inferior parietal lobe, IPL, superior temporal gyrus, STG; inferior frontal gyrus, IFG; anterior cingulate cortex, ACC; posterior cingulate cortex, PCC; angular gyrus, AG; parahippocampal gyrus, PHG; middle temporal gyrus, MTG; anterior insula, aInsula; posterior insula, pInsula; middle cingulate cortex, MCC. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 3

Dynamic functional connectivity (FC) states in children. Dynamic FC states are derived using k‐means clustering. Total number and percentage of occurrences is listed above each state. Intrinsic connectivity networks (ICNs) are divided into central executive (CEN), default mode (DMN) and salience (SN) sub‐networks. See Figure 1 and Supporting Information Table S1 for abbreviations and more detailed information on each component. [Color figure can be viewed at http://wileyonlinelibrary.com.]

Figure 4

Variability in connections over time. Larger standard deviations indicate more variable, or less stable, connections over the course of the measurement period. See Figure 1 and Supporting Information Table S1 for abbreviations and more detailed information on each component. [Color figure can be viewed at http://wileyonlinelibrary.com.]