The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Relationships between IQ and Regional Cortical Gray Matter Thickness in Healthy Adults
Open accessAbstract
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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Cites
"General Intelligence," Objectively Determined and Measured
Spearman, C. (1904) · The American Journal of Psychology · doi:10.2307/1412107 · Cited by 6,207
Intelligence: Knowns and unknowns.
Neisser, U., Boodoo, G., Bouchard, T. J., Boykin, A. W., Brody, N., Ceci, S. J., Halpern, D. F., Loehlin, J. C., Perloff, R., Sternberg, R. J., et al. (1996) · American Psychologist · doi:10.1037/0003-066x.51.2.77 · Cited by 2,913
The g factor: the science of mental ability
(1998) · Choice Reviews Online · doi:10.5860/choice.36-2443 · Cited by 2,746
Common regions of the human frontal lobe recruited by diverse cognitive demands
Duncan, J., & Owen, A. M. (2000) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01633-7 · Cited by 2,498
A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development
Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P., & Lancaster, J. (1995) · NeuroImage · doi:10.1006/nimg.1995.1012 · Cited by 1,584
Self-citationIntellectual ability and cortical development in children and adolescents
Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., Evans, A., Rapoport, J., & Giedd, J. (2006) · Nature · doi:10.1038/nature04513 · Cited by 1,543
Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children
Sowell, E. R., Thompson, P. M., Leonard, C. M., Welcome, S. E., Kan, E., & Toga, A. W. (2004) · The Journal of Neuroscience · doi:10.1523/jneurosci.1798-04.2004 · Cited by 1,481
Self-citationHonea, R., Crow, T. J., Passingham, D., & Mackay, C. E. (2005) · American Journal of Psychiatry · doi:10.1176/appi.ajp.162.12.2233 · Cited by 1,157
Permutation tests for multi-factorial analysis of variance
Anderson, M., & Braak, C. T. (2003) · Journal of Statistical Computation and Simulation · doi:10.1080/00949650215733 · Cited by 1,109
Neural mechanisms of general fluid intelligence
Gray, J. R., Chabris, C. F., & Braver, T. S. (2003) · Nature Neuroscience · doi:10.1038/nn1014 · Cited by 1,080
Cited by
Neurodevelopmental Trajectories of the Human Cerebral Cortex
Shaw, P., Kabani, N. J., Lerch, J. P., Eckstrand, K., Lenroot, R., Gogtay, N., Greenstein, D., Clasen, L., Evans, A., Rapoport, J. L., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.5309-07.2008 · Cited by 1,644
A meta-analysis of sex differences in human brain structure
Ruigrok, A. N. V., Salimi-Khorshidi, G., Lai, M.-C., Baron-Cohen, S., Lombardo, M. V., Tait, R. J., & Suckling, J. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.12.004 · Cited by 1,192
Imaging structural co-variance between human brain regions
Alexander-Bloch, A., Giedd, J. N., & Bullmore, E. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3465 · Cited by 1,064
The neuroscience of human intelligence differences
Deary, I. J., Penke, L., & Johnson, W. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2793 · Cited by 1,038
Storsve, A. B., Fjell, A. M., Tamnes, C. K., Westlye, L. T., Overbye, K., Aasland, H. W., & Walhovd, K. B. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.0391-14.2014 · Cited by 542
Metadata
- Authors
- Narr, K. L., Woods, R. P., Thompson, P. M., Szeszko, P., Robinson, D., Dimtcheva, T., Gurbani, M., Toga, A. W., & Bilder, R. M.
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-11-21
- Volume
- 17
- Issue
- 9
- Pages
- 2163-2171
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- OpenAlex
- W2143956675
- Cited by
- 344
- References
- 48
- FWCI
- 12.50
- Type
- journal article
- Language
- en
- Open access
- bronze
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