Article

Neurodevelopmental Trajectories of the Human Cerebral Cortex

Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892, USA.
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 05/2008; 28(14):3586-94. DOI: 10.1523/JNEUROSCI.5309-07.2008
Source: PubMed

ABSTRACT

Understanding the organization of the cerebral cortex remains a central focus of neuroscience. Cortical maps have relied almost exclusively on the examination of postmortem tissue to construct structural, architectonic maps. These maps have invariably distinguished between areas with fewer discernable layers, which have a less complex overall pattern of lamination and lack an internal granular layer, and those with more complex laminar architecture. The former includes several agranular limbic areas, and the latter includes the homotypical and granular areas of association and sensory cortex. Here, we relate these traditional maps to developmental data from noninvasive neuroimaging. Changes in cortical thickness were determined in vivo from 764 neuroanatomic magnetic resonance images acquired longitudinally from 375 typically developing children and young adults. We find differing levels of complexity of cortical growth across the cerebrum, which align closely with established architectonic maps. Cortical regions with simple laminar architecture, including most limbic areas, predominantly show simpler growth trajectories. These areas have clearly identified homologues in all mammalian brains and thus likely evolved in early mammals. In contrast, polysensory and high-order association areas of cortex, the most complex areas in terms of their laminar architecture, also have the most complex developmental trajectories. Some of these areas are unique to, or dramatically expanded in primates, lending an evolutionary significance to the findings. Furthermore, by mapping a key characteristic of these development trajectories (the age of attaining peak cortical thickness) we document the dynamic, heterochronous maturation of the cerebral cortex through time lapse sequences ("movies").

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    • "d environmental factors (Schmitt et al., 2007). Figure is reproduced with permission. 145 healthy subjects between 4 and 20 years old. Their study incorporated an artificial neural network for tissue classification. Their results demonstrated linear increases in white matter and nonlinear changes in cortical gray matter that varied by brain region.Shaw et al. (2008)presented a large-scale cortical thickness study investigating 764 MRI examinations acquired longitudinally from 375 typically developing children and young adults. They used regression analysis to determine if each cortical measurement was best modeled by a cubic, quadratic, or linear function as they vary with age. They determined that"
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    ABSTRACT: Multivariate analysis (MVA) is a class of statistical and pattern recognition techniques that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neurological medical imaging related challenges including the evaluation of healthy brain development, the automated analysis of brain tissues and structures through image segmentation, evaluating the effects of genetic and environmental factors on brain development, evaluating sensory stimulation's relationship with functional brain activity and much more. Compared to adult imaging, pediatric, neonatal and fetal imaging have attracted less attention from MVA researchers, however, recent years have seen remarkable MVA research growth in pre-adult populations. This paper presents the results of a systematic review of the literature focusing on MVA applied to healthy subjects in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in brain MRI, the field is still young and significant research growth will continue into the future.
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    • "Accordingly, an important direction for future works would be to focus on the relationship between gray matter maturation and the development of the proprioceptive network. A first approach may capitalize on the nonlinear (cubic) trajectory for age-related change in cortical thickness, which reflects a period of initial childhood increase ( peak thickness ∼10 years), followed by a thinning of gray matter in adolescence and then stabilization of cortical thickness in adulthood (Paus 2005; Shaw et al. 2008). Examining whether the development of the proprioceptive network parallels this trajectory, involving presumably network expansion during childhood before pruning to a more restricted topology in adolescence, would confer further support to the gray matter contribution to network development. "
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    • "Indeed, developmental differences account for much of the variation in fMRI activation patterns between non-depressed adults and adolescents during emotion processing (Cho et al., 2012). Furthermore, cortical thickness of distinct brain regions develops differently depending on their organization and function (Huttenlocher and Dabholkar, 1997; Shaw et al., 2008). Specifically, changes in the composition of the insular cortex during adolescence correspond to improved emotional regulatory skills and refinement of functioning such as improved impulsecontrol (Sisk and Zehr, 2005; Steinberg et al., 2009). "
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