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Journal Articles
Benjamin A. E. Hunt, Simeon M. Wong, Marlee M. Vandewouw, Matthew J. Brookes, Benjamin T. Dunkley ...
Publisher: Journals Gateway
Network Neuroscience (2019) 3 (2): 497–520.
Published: 01 March 2019
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Detailed characterization of typical human neurodevelopment is key if we are to understand the nature of mental and neurological pathology. While research on the cellular processes of neurodevelopment has made great advances, in vivo human imaging is crucial to understand our uniquely human capabilities, as well as the pathologies that affect them. Using magnetoencephalography data in the largest normative sample currently available (324 participants aged 6–45 years), we assess the developmental trajectory of resting-state oscillatory power and functional connectivity from childhood to middle age. The maturational course of power, indicative of local processing, was found to both increase and decrease in a spectrally dependent fashion. Using the strength of phase-synchrony between parcellated regions, we found significant linear and nonlinear (quadratic and logarithmic) trajectories to be characterized in a spatially heterogeneous frequency-specific manner, such as a superior frontal region with linear and nonlinear trajectories in theta and gamma band respectively. Assessment of global efficiency revealed similar significant nonlinear trajectories across all frequency bands. Our results link with the development of human cognitive abilities; they also highlight the complexity of neurodevelopment and provide quantitative parameters for replication and a robust footing from which clinical research may map pathological deviations from these typical trajectories. Author Summary Imagine that we could predict which children will go on to develop depression or anxiety disorders using functional brain imaging? This would allow early intervention and, in some, negation of the illness. The first step toward this goal is understanding the neurodevelopmental trajectory of healthy individuals. We can then recognize the developmental deviations with specific illnesses. We used the largest developmental MEG dataset available ( n = 324) to characterize the developmental trajectories of functional connectivity in a cohort aged 6–45 years. We find evidence for nonlinear trajectories in two graph theory metrics, heterogeneously defined in brain space with opposing trajectories in different oscillatory frequencies. Our findings highlight the intricacy of typical neurodevelopment and provide foundational quantifications for replication in different modalities and application to clinical cohorts.
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