How Does Your Cortex Grow?
By Armin Raznahan, P. Shaw, François Lalonde, M. Stockman, G. Wallace, Dede K. Greenstein, Liv S. Clasen, Nitin Gogtay, Jay N. Giedd. Journal of Neuroscience, 2011
681 citations recorded by the source corpus.
Understanding human cortical maturation is a central goal for developmental neuroscience. Significant advances toward this goal have come from two recent strands of in vivo structural magnetic resonance imaging research: (1) longitudinal study designs have revealed that factors such as sex, cognitive ability, and disease are often better related to variations in the tempo of anatomical change than to variations in anatomy at any one time point; (2) largely cross-sectional applications of new surface-based morphometry (SBM) methods have shown how the traditional focus on cortical volume (CV) can obscure information about the two evolutionarily and genetically distinct determinants of CV: cortical thickness (CT) and surface area (SA). Here, by combining these two strategies for the first time and applying SBM in >1250 longitudinally acquired brain scans from 647 healthy individuals aged 3–30 years, we deconstruct cortical development to reveal that distinct trajectories of anatomical change are hidden within, and give rise to, a curvilinear pattern of CV maturation. Developmental changes in CV emerge through the sexually dimorphic and age-dependent interaction of changes in CT and SA. Moreover, SA change itself actually reflects complex interactions between brain size-related changes in exposed cortical convex hull area, and changes in the degree of cortical gyrification, which again vary by age and sex. Knowing of these developmental dissociations, and further specifying their timing and sex-biases, provides potent new research targets for basic and clinical neuroscience.
Subfields: Aging, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/46819680870e5d1671aaf66247483481fdb624fa
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aging
In Cognitive Neuroscience
In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- Networks of anatomical covariance (2013, background): “…He et al., 2007, 2008, 2009a, 2009b; Khundrakpam et al., in press; Lerch et al., 2006; Lo et al., 2011; Mechelli et al., 2005; Raj et al., 2012; Ramnani et al., 2004; Raznahan et al., 2011a; Reid and Evans, 2013; Reid et al., 2010; Seeley et al., 2009; Zhou et al., 2012; Zielinski et al., 2010).”
- Trajectories of cortical thickness maturation in normal brain development – The importance of quality control procedures (2015, neutral): “…N C O R R E C other studies (Shaw et al., 2008; Raznahan et al., 2011).”
- Relating ADHD to the aperiodic component of the EEG signal in both males and females across development (2026, unknown): “…the nonlinear analysis was to evaluate the potential for a “ growth spurt ” in the aperiodic exponent, analogous to patterns observed in structural brain measures, where ADHD has been linked to shifts in the timing of developmental peaks (Shaw et al., 2007; 2013; Raznahan et al., 2011).”