Relationships between IQ and Regional Cortical Gray Matter Thickness in Healthy Adults

Laboratory of Neuro Imaging, Department of Neurology, Geffen School of Medicine at the University of California, Los Angeles (UCLA), Los Angeles, CA 90095-7334, USA.
Cerebral Cortex (Impact Factor: 8.67). 10/2007; 17(9):2163-71. DOI: 10.1093/cercor/bhl125
Source: PubMed


Prior studies show positive correlations between full-scale intelligence quotient (FSIQ) and cerebral gray matter measures. Few imaging studies have addressed whether general intelligence is related to regional variations in brain tissue and the associated influences of sex. Cortical thickness may more closely reflect cytoarchitectural characteristics than gray matter density or volume estimates. To identify possible localized relationships, we examined FSIQ associations with cortical thickness at high spatial resolution across the cortex in healthy young adult (age 17-44 years) men (n = 30) and women (n = 35). Positive relationships were found between FSIQ and intracranial gray and white matter but not cerebrospinal fluid volumes. Significant associations with cortical thickness were evident bilaterally in prefrontal (Brodmann's areas [BAs] 10/11, 47) and posterior temporal cortices (BA 36/37) and proximal regions. Sex influenced regional relationships; women showed correlations in prefrontal and temporal association cortices, whereas men exhibited correlations primarily in temporal-occipital association cortices. In healthy adults, greater intelligence is associated with larger intracranial gray matter and to a lesser extent with white matter. Variations in prefrontal and posterior temporal cortical thickness are particularly linked with intellectual ability. Sex moderates regional relationships that may index dimorphisms in cognitive abilities, overall processing strategies, or differences in structural organization.

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Available from: Robert Bilder, Oct 05, 2015
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    • "e l s e v i e r . c o m / l o c a t e / y n i m g (Narr et al., 2007) and white matter tracts (Van Beek et al., 2014). A brain network perspective provides a quantitative model for elucidating the association between the efficiency of brain networks and intelligence (Cole et al., 2012; van den Heuvel et al., 2009). "
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    • "According to the radial unit hypothesis, cortical thickness is influenced by the number of neurons within a column [Rakic, 1988], and it reflects cytoarchitectural characteristics of the neuropil [Narr et al., 2007]. In addition, cortical thickness is associated with PFC-mediated cognitive function [Ehrlich et al., 2012; Narr et al., 2007] and psychiatric disorders [Alexander-Bloch et al., 2014]. In sum, cortical thickness tends to reflect cortical columnar architecture and capture in vivo change of the PFC, and thus can be a promising endophenotype in a study of the in vivo neural mechanisms of the RAB2A gene. "
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    ABSTRACT: Calbindin-containing γ-aminobutyric acid (GABA)ergic interneurons in the prefrontal cortex (PFC) have been found to play an important role in working memory (WM) and their malfunctions have been linked to psychiatric disorders. A recent genome-wide association and expression-SNP study indicated that the RAB2A gene was associated with the density of prefrontal calbindin-positive neurons, suggesting this gene may have a broader influence on prefrontal structure and function. Using multimodal MRI and behavioral tasks, the current study investigated the effect of RAB2A on prefrontal morphology, resting-state functional connectivity, and WM performance in a large sample of healthy Han Chinese subjects. Results showed that the RAB2A AGCAAA haplotype was associated with improved WM accuracy, increased cortical thickness in the left inferior frontal gyrus, and decreased functional connectivity between the left inferior frontal gyrus and the left dorsolateral PFC. Our findings provide consistent evidence supporting the effect of RAB2A on the structure and function of the PFC and related cognitive functions. These results should provide new insights into the neural mechanisms underlying the GABAergic genes' role in WM as well as its dysfunction. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    Human Brain Mapping 08/2015; DOI:10.1002/hbm.22924 · 5.97 Impact Factor
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    • "With regard to effects of sex, some functional studies found an association between intelligence and brain activation only in men, not in women (Haier & Benbow, 1995; O'Boyle, Benbow, & Alexander, 1995), while in other studies the sexes differed with respect to the direction of the association (Fink & Neubauer, 2006; Grabner, Fink, Stipacek, Neuper, & Neubauer, 2004; Neubauer & Fink, 2003), or sex interacted with task content in moderating the association between intelligence and brain activation (Jausovec & Jausovec, 2008; Neubauer, Grabner, Fink, & Neuper, 2005; Neubauer et al., 2002). Structural studies reported grey matter correlates of intelligence to be more pronounced in men than in women (Haier et al., 2005) or to be located in different brain regions for men and women (Narr et al., 2007). White matter correlates of intelligence, on the other hand, were reported to be more pronounced in women than in men (Davatzikos & Resnick, 1998; Gur et al., 1999; Haier et al., 2005; Pfleiderer et al., 2004) or to show associations of opposing directions in men and women (Schmithorst, 2009; Tang et al., 2010). "
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    ABSTRACT: Individual differences in general intelligence have been associated with differences in brain structure and function. The currently most popular theory of the neural bases of intelligence – the Parieto-Frontal Integration Theory of Intelligence (P-FIT) – describes a network of frontal and parietal brain regions as the main neural basis of intelligence. Here, we put the theory to an empirical test by conducting voxel-based quantitative meta-analyses of 12 structural and 16 functional human brain imaging studies, testing for statistically significant spatial convergence across studies. We focused our analyses on studies reporting associations between individual differences in intelligence (as assessed by established tests of psychometric intelligence) and either (a) brain activation during a cognitive task (functional meta-analysis) or (b) amount of grey matter as assessed by voxel-based morphometry (structural meta-analysis). The functional meta-analysis resulted in eight clusters distributed across both hemispheres, located in lateral frontal, medial frontal, parietal, and temporal cortices. The structural meta-analysis of VBM studies resulted in 12 clusters distributed in lateral and medial frontal, temporal, and occipital cortices, as well as in subcortical structures. Results of the functional and structural meta-analyses did not show any overlap — although both independently showed good match with the P-FIT. Based on the meta-analyses, we present an updated model for the brain bases of intelligence that extends previous models in also considering the posterior cingulate cortex and subcortical structures as relevant for intelligence, and in differentiating between positive and negative associations of intelligence and brain activation. From a critical review of original studies and methods, we derive important suggestions for future research on brain correlates of intelligence.
    Intelligence 05/2015; 51:10-27. DOI:10.1016/j.intell.2015.04.009 · 3.25 Impact Factor
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