Sowell ER, Thompson PM, Holmes CJ, Batth R, Jernigan TL, Toga AW. Localizing age-related changes in brain structure between childhood and adolescence using statistical parametric mapping. Neuroimage 9: 587-597
Department of Psychiatry, University of California, San Diego, San Diego, California, United States NeuroImage
(Impact Factor: 6.36).
06/1999; 9(6 Pt 1):587-97. DOI: 10.1006/nimg.1999.0436
Volumetric studies have consistently shown reductions in cerebral gray matter volume between childhood and adolescence, with the most dramatic changes occurring in the more dorsal cortices of the frontal and parietal lobes. The purpose of this study was to examine the spatial location of these changes employing methods typical of functional imaging studies. T1-weighted structural MRI data (1.2 mm) were analyzed for nine normally developing children and nine normal adolescents. Validity and reliability of the tissue segmentation protocol were assessed as part of several preprocessing analyses prior to statistical parametric mapping (SPM). Using SPM96, a simple contrast of average gray matter differences between the two age groups revealed 57 significant clusters (SPM[Z] height threshold, P<0.001, extent threshold 50, uncorrected). The pattern and distribution of differences were consistent with earlier findings from the volumetric assessment of the same subjects. Specifically, more differences were observed in dorsal frontal and parietal regions with relatively few differences observed in cortices of the temporal and occipital lobes. Permutation tests were conducted to assess the overall significance of the gray matter differences and validity of the parametric maps. Twenty SPMs were created with subjects randomly assigned to groups. None of the random SPMs approached the number of significant clusters observed in the age difference SPM (mean number of significant clusters = 5.8). The age effects observed appear to result from regions that consistently segment as gray matter in the younger group and consistently segment as white matter in the older group. The utility of these methods for localizing relatively subtle structural changes that occur between childhood and adolescence has not previously been examined.
Available from: Suleyman Kaplan
- "Especially, the volume of prefrontal cortex in humans and animals reduces throughout the adolescence (Sowell et al., 1999, 2001; Stiles and Jernigan, 2010). Development in some regions of the brain continues till the second and third decades of life. "
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ABSTRACT: Rapid advances in technology involve increased exposures to radio-frequency/microwave radiation from mobile phones and other wireless transmitting devices. As cell phones are held close to the head during talking and often stored next to the reproductive organs, studies are mostly focused on the brain. In fact, more research is especially needed to investigate electromagnetic field (EMF)'s effects on the central nervous system (CNS). Several studies clearly demonstrate that EMF emitted by cell phones could affect a range of body systems and functions. Recent work has demonstrated that EMF inhibit the formation and differentiation of neural stem cells during embryonic development and also affect reproductive and neurological health of adults that have undergone prenatal exposure. The aim of this review is to discuss the developing CNS and explain potential impacts of EMF on this system.
Available from: Melinda Arnett
- "Morphological and connectivity changes in a number of brain regions (Durston et al., 2001; Giedd, 2008; Sowell et al., 2002) make the adolescent brain more vulnerable to the effects of environmental stimuli (Schindler et al., 2014; Steinberg, 2005; Wheeler et al., 2013). Moreover, in adolescent rodents the HPA axis undergoes reorganization (Arnsten & Shansky, 2004; Meaney et al., 1985; Sowell et al., 1999), making this developmental period sensitive to the effects of stress. Due to the propensity of the developing adolescent brain to be influenced by external stimuli, we further hypothesize that adolescent mice will be more susceptible to the effects of PVN GR disruption. "
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ABSTRACT: Glucocorticoid receptors (GR) in the paraventricular nucleus of the hypothalamus (PVN) are important regulators of negative feedback regulation of the hypothalamic-pituitary-adrenal (HPA) axis. Previous evaluation of endogenous PVN GR function in adult mice demonstrated that mice with loss of GR exon 3 in the PVN (Sim1Cre-GRe3Δ) have a hyperactive HPA axis, growth impairment and metabolic disruptions. Here, we hypothesized that lack of negative feedback inhibition of the HPA axis through PVN GR, as demonstrated through loss of PVN GR early in life, will have developmental-stage-specific consequences. Immunofluorescence revealed that Sim1Cre-GRe3Δ mice display PVN GR loss as early as post-natal day 2 compared to control mice. Sim1Cre-GRe3Δ mice compared to controls also displayed increased corticotropin-releasing hormone (CRH) mRNA in the PVN at post-natal day 10, as shown by in situ hybridization. Corticosterone radioimmunoassay revealed that the disruptions in PVN GR and CRH expression led to elevated basal corticosterone secretion in male Sim1Cre-GRe3Δ mice by early adolescence and increased stress-induced (restraint) corticosterone secretion in late adolescence into adulthood. In comparison, female Sim1Cre-GRe3Δ mice did not display corticosterone disruption until adulthood. Circadian rhythmicity of corticosterone secretion was normal for male and female mice at all age groups regardless of genotype with one exception. In late adolescence, female Sim1Cre-GRe3Δ mice had disrupted circadian corticosterone secretion due to significantly elevated circulating levels at nadir. We conclude that PVN GR function matures at an earlier developmental time point in male than in female mice and thus leads to later differential stress responsiveness between sexes.
Available from: Katya Rubia
- "GPC identified a distributed network predictive of controls in later developing lateral and medial fronto-striatal and parieto-temporal regions that are crucial for motor response inhibition [Aron and Poldrack , 2006; Cai et al., 2012; Chambers et al., 2006, 2009; Juan and Muggleton, 2012; Rubia et al., 2003, 2007b, 2013]. Structurally [Sowell et al., 1999, 2004] and functionally during inhibition tasks (Adleman et al., 2002; Bunge et al., 2002; Rubia et al., 2000; Rubia et al., 2007b; Rubia et al., 2006, Rubia et al., 2013) [for review see (Rubia, 2013)], these lateral prefrontal, striatal and parietal brain regions develop later than the ventromedial prefrontal, limbic (i.e., hippocampus, amygdala) and paralimbic areas (insula) that were predictive of ADHD patients. Our finding of high magnitude weights predictive of controls in later developing lateral fronto-striato-parietal regions and for ADHD in earlier developing ventromedial fronto-limbic regions hence suggest that the ADHD discrimination networks are reflective of more immature activation patterns, while the control discrimination patterns are reflective of a more mature activation pattern for Stop task performance. "
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ABSTRACT: Attention-deficit/hyperactivity disorder (ADHD) is currently diagnosed on the basis of subjective measures, despite evidence for multi-systemic structural and neurofunctional deficits. A consistently observed neurofunctional deficit is in fine-temporal discrimination (TD). The aim of this proof-of-concept study was to examine the feasibility of distinguishing patients with ADHD from controls using multivariate pattern recognition analyses of functional magnetic resonance imaging (fMRI) data of TD.
A total of 20 medication-naive adolescent male patients with ADHD and 20 age-matched healthy controls underwent fMRI while performing a TD task. The fMRI data were analyzed with Gaussian process classifiers to predict individual ADHD diagnosis based on brain activation patterns.
The pattern of brain activation correctly classified up to 80% of patients and 70% of controls, achieving an overall classification accuracy of 75%. The distributed activation networks with the highest delineation between patients and controls corresponded to a distributed network of brain regions involved in TD and typically compromised in ADHD, including inferior and dorsolateral prefrontal, insula, and parietal cortices, and the basal ganglia, anterior cingulate, and cerebellum. These regions overlapped with areas of reduced activation in patients with ADHD relative to controls in a univariate analysis, suggesting that these are dysfunctional regions.
We show evidence that pattern recognition analyses combined with fMRI using a disorder-sensitive task such as timing have potential in providing objective diagnostic neuroimaging biomarkers of ADHD.
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