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Inherent limits on the identification of a neural basis for general intelligence

Published online by Cambridge University Press:  26 July 2007

Clancy Blair
Clancy Blair
Affiliation:
Department of Human Development and Family Studies, Pennsylvania State University, University Park, PA 16802. cbb11@psu.edu
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Abstract

The target article provides a thoughtful review and synthesis of studies examining the neural basis of cognitive abilities associated with intelligence test performance. In its attempt to present a new or generative theory of the neural basis for intelligence, however, the review faces specific limits to its theoretical model that relate to processes of development and the role of automaticity in cognition.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 30 , Issue 2 , April 2007 , pp. 154 - 155
Copyright
Copyright © Cambridge University Press 2007

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References

Blair, C. (2006) How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences 29(2):109–25.CrossRefGoogle ScholarPubMed
Colom, R., Rebollo, I., Palacios, A., Juan-Espinosa, M. & Kyllonen, P. C. (2004) Working memory is (almost) perfectly predicted by g. Intelligence 32(3):277–96.CrossRefGoogle Scholar
Duncan, J., Burgess, P. & Emslie, H. (1995) Fluid intelligence after frontal lobe lesions. Neuropsychologia 33(3):261–68.CrossRefGoogle ScholarPubMed
Eslinger, P., Blair, C., Wang, J., Lipovsky, B., Realmuto, J., Baker, D., Thorne, S., Gamson, D., Zimmerman, E., Yang, Q. & Rohrer, L. (submitted) A developmental functional magnetic resonance imaging study of neural systems subserving relational reasoning in childhood and adolescence.Google Scholar
Flynn, J. R., (in press) What is intelligence? Beyond the Flynn Effect. Cambridge University Press.Google Scholar
Gray, J. R., Chabris, C. F. & Braver, T. S. (2003) Neural mechanisms of general fluid intelligence. Nature Neuroscience 6(3):316–22.Google Scholar
Haier, R. J., Chueh, D., Touchette, P., Lott, I., Buchsbaum, M. S., Macmillan, D., Sandman, C., Lacasse, L. & Sosa, E. (1995) Brain size and cerebral glucose metabolic rate in nonspecific mental retardation and Down syndrome. Intelligence 20(2):191–210.CrossRefGoogle Scholar
Haier, R. J., Siegel, B. V., Nuechterlein, K. H., Hazlett, E., Wu, J. C., Paek, J., Browning, H. L. & Buchsbaum, M. S. (1988) Cortical glucose metabolic rate correlates of abstract reasoning and attention studied with positron emission tomography. Intelligence 12(2):199–217.CrossRefGoogle Scholar
Hunt, J. M. (1961) Intelligence and experience. Ronald Press.Google Scholar
Klingberg, T., Forssberg, H. & Westerberg, H. (2002) Increased brain activity in frontal and parietal cortex underlies the development of visuospatial working memory capacity during childhood. Journal of Cognitive Neuroscience 14:1–10.CrossRefGoogle ScholarPubMed
Lee, K. H., Choi, Y. Y., Gray, J. R., Cho, S. H., Chae, J. H., Lee, S. & Kim, K. (2006) Neural correlates of superior intelligence: Stronger recruitment of posterior parietal cortex. NeuroImage 29(2):578–86.CrossRefGoogle ScholarPubMed
Rivera, S. M., Reiss, A. L., Eckert, M. A. & Menon, V. (2005) Developmental changes in mental arithmetic: Evidence for increased functional specialization in the left inferior parietal cortex. Cerebral Cortex 15:1779–90.Google Scholar
Waltz, J. A., Knowlton, B. J., Holyoak, K. J., Boone, K. B., Mishkin, F. S., Santos, M., Thomas, C. R. & Miller, B. L. (1999) A system for relation reasoning in the human prefrontal cortex. Psychological Science 10:119–25.Google Scholar