Structural brain variation and general intelligence

By Richard J. Haier, Rex E. Jung, Ronald A. Yeo, Kevin Head, Michael T. Alkire. NeuroImage, 2004

526 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Pediatrics, Perinatology and Child Health

View Paper: https://www.semanticscholar.org/paper/7f7dccae209b9234b0f72b1d87939cb08a1df67a

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

In Pediatrics, Perinatology and Child Health

Citations in the corpus

The neuroanatomy of general intelligence: sex matters (2005, background): “These results expand upon our previous report (Haier et al., 2004), which combined men and women into a single analysis to maximize statistical power.”
Gray Matter and Intelligence Factors: Is There a Neuro-g?. (2009, background): “In addition to the psychometrics of g and whether it is a unitary construct or not, many issues require further investigation, including the role of age and sex differences in brain structure and development (Haier et al., 2004; Haier, Jung, Yeo, Head & Alkire, 2005; Jung et al., 2005; Schmithorst &”
Where smart brains are different: A quantitative meta-analysis of functional and structural brain imaging studies on intelligence (2015, methodology): “, (fluid) intelligence (e.g., Gray et al., 2003; Haier et al., 2004).”
Efficiency of Functional Brain Networks and Intellectual Performance (2009, background): “…developmental course of specific high-order brain regions (Shaw et al., 2006), total brain volume and focal brain structure (Thompson et al., 2001; Haier et al., 2004; Colom et al., 2006; Hulshoff Pol et al., 2006; Choi et al., 2008), microstructural organization of white matter (Chiang et al.,…”
Gray matter correlates of fluid, crystallized, and spatial intelligence: Testing the P-FIT model (2009, methodology): “Haier and colleagues have shown that variation in structures throughout the brain wasrelatedtointelligence(Colom,Jung,H Johnson, Jung, Colom, & Haier, 2008; Haier, Jung, Yeo, Head, & Alkire, 2004, 2005 ) finding that (1) there are significant associations between brain variations in gray matter (GM”
Neural correlates of cognitive efficiency (2006, background): “Anatomical studies have shown individual differences in both white and gray matter that could mediate interactive activation changes between brain regions and subjects' processing speed performance (e.g., Haier et al., 2004, 2005).”
Genetic influences on human brain structure: A review of brain imaging studies in twins (2007, background): “More focally, several brain areas were found to be correlated with intelligence [Frangou et al., 2004; Haier et al., 2004; Reiss et al., 1996].”
Cognitive processing speed and the structure of white matter pathways: Convergent evidence from normal variation and lesion studies (2008, unknown): “Discussion Cognitive processing speed, as assessed by the Digit–Symbol Substitution subtest from WAIS-III, correlated positively with regional FA values in white matter of the left middle frontal gyrus, bilateral parietal lobes, and bilateral temporal lobes in a group of young healthy adults.”
Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders (2009, background): “…with equivalent IQ scores (Haier et al., 2005 ); the relative contributions of gray and white matter to explaining variations in IQ shifts with age (Haier et al., 2004 ; Johnson et al., 2008 ; Jung & Haier, 2007 ), and the strong correlation between whole-brain gray matter volume and IQ develops…”
Brain Anatomical Network and Intelligence (2009, methodology): “Utilizing voxel-based morphometry methods, recent studies have revealed correlations between IQ and certain specific brain regions involving the frontal, parietal, temporal and occipital lobes [3–5,47–50].”
The Neuroscience of Intelligence (2016, methodology): “Their patent is supported by previous research, including our MRI work (Haier et al., 2004), and on research from the South Korean group that reports correlations between predicted IQ scores and actual IQ scores for different samples (Choi et al.”
The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence (2007, methodology): “4) found correlations between gray matter volume within frontal (BAs 9, 10, 46), temporal (BAs 21, 22, 37, 42), parietal (BAs 3, 43), and occipital (BA 19) regions, with significant white matter–IQ correlations observed near BA 39 (Haier et al. 2004).”
Template-O-Matic: A toolbox for creating customized pediatric templates (2008, background): “…2004; Good et al., 2001; Lenroot et al., 2007; Wilke et al., 2007), handedness (Amunts et al., 1996; Hervé et al., 2006; Narr et al., 2007), and cognitive abilities (Colom et al., 2006; Haier et al., 2004; Reiss et al., 1996; Schmithorst et al., 2005; Thompson et al., 2001; Wilke et al., 2003b).”
Brain spontaneous functional connectivity and intelligence (2008, methodology): “Using VBM analysis in two independent samples, Haier and colleagues (Colom et al., 2006; Haier et al., 2004) found that greater amounts of gray matter were associated with higher IQ in discrete brain regions, including the frontal (BA10, 46, 9), temporal (BA21, 37, 22, 42), parietal (BA40, 43, 3),…”
Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI (2006, background): “General measures of intelligence correlate with global grey matter volumes (Andreasen et al., 1993; Reiss et al., 1996; Pennington et al., 2000; Posthuma et al., 2003; Wilke et al., 2003; Haier et al., 2004).”