Development of distinct control networks through segregation and integration

By Damien A. Fair, Nico U F Dosenbach, Jessica A. Church, Alexander Li Cohen, Shefali Brahmbhatt, Francis M. Miezin, Deanna M. Barch, Marcus E. Raichle, Steven E. Petersen, Bradley L. Schlaggar. Proceedings of the National Academy of Sciences of the United States of America, 2007

1,281 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/8aa63e11e925f576acf216ac5732c62b185e9945

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In Cellular and Molecular Neuroscience

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Citations in the corpus

Development of Large-Scale Functional Brain Networks in Children (2009, methodology): “This suggests a process of greater functional segregation in children and greater functional integration in young-adults at the whole-brain level, not just in circumscribed nodes of the attentional control [27] and default node networks [28].”
Growing together and growing apart: Regional and sex differences in the lifespan developmental trajectories of functional homotopy (2010, background): “…maturational processes throughout the lifespan: several studies have demonstrated developmental shifts from diffuse short-range RSFC in childhood to the increasingly focal, long-range RSFC in young adulthood (Fair et al., 2007, 2008; Fransson et al., 2007; Kelly et al., 2009; Supekar et al., 2009).”
Patterns of hemodynamic low-frequency oscillations in the brain are modulated by the nature of free thought during rest (2012, background): “, 2010), development (Dosenbach et al., 2010; Fair et al., 2007), aging (Achard and Bullmore, 2007; Allen et al.”
Recent progress and outstanding issues in motion correction in resting state fMRI (2014, positive): “For example, between (distant) regions of the default mode network, children had weaker signal correlations than young adults (Fair et al., 2007), and these same (distant) correlations were weaker in older subjects than in young adults (Andrews-Hanna et al., 2007).”
Inter-Individual Differences in Resting State Functional Connectivity Predict Task-Induced BOLD Activity (2010, background): “This finding further supports the potential utility of resting-state approaches to study the developing (b18 years old) and aging (N65 years old) brain, which are both characterized by greater spatial extent of activation andRSFC (Andrews-Hanna et al. 2007;Durston et al., 2006; Emery et al., 2008; F”
Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) (2012, background): “…et al., 2006; Horovitz et al., 2009; Larson-Prior et al., 2009) and sedation (Greicius et al., 2008; Kiviniemi et al., 2003; Peltier et al., 2005; Vincent et al., 2007) allowing for comparisons across development (Dosenbach et al., 2010; Fair et al., 2007) and even species (Vincent et al., 2007).”
Groupwise whole-brain parcellation from resting-state fMRI data for network node identification (2013, neutral): “Nodes have been defined using task-based fMRI studies (Arfanakis et al., 2000; Biswal et al., 1995; Cordes et al., 2000; Fair et al., 2007; Hoffman et al., 2011; Stevens et al., 2012) but these activate only a very limited fraction of the brain and thus this approach is not appropriate for…”
A dual-networks architecture of top-down control. (2008, methodology): “Instead, we contend that functionally and anatomically distinguishable regions of prefrontal (the dlPFC and aPFC), frontal (the dFC, dACC/msFC and aI/fO) and parietal cortex (the IPL, IPS and precuneus) contribute specific individual control functions [11] as nodes within two separate control networ”
Resting-state functional connectivity in the human brain revealed with diffuse optical tomography (2009, methodology): “The discovery of functional connectivity (fc-MRI) has led to its use as an important tool throughout neuroimaging research (Fox and Raichle, 2007), including insights into childhood brain development (Fair et al., 2007; Fransson et al., 2007; Fair et al., 2008).”
Functional Brain Networks Develop from a “Local to Distributed” Organization (2009, methodology): “We suggested that these global developmental processes support the maturation of a dual-control system and its functional connections with the cerebellar network [22].”
Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI (2015, background): “…directly interfere with current hypotheses about local and long-distance functional connectivity in the context of neurodevelopment and Autism Spectrum Disorders (ASD; Courchesne and Pierce (2005), Fair et al. (2007, 2008, 2009), Kelly et al. (2009), Dosenbach et al. (2010), Power et al. (2010)).”