Popular science book and public lecture. At 22 minutes Duncan gives a good pragmatic discussion of g in response to an anti-g interlocutor (Howard Gardner disciple). The streaming player at the link doesn't let me skip ahead, so probably better to download the file and play on your machine if you just want to hear this part of the discussion. Best thing to do is get it via iTunes so you can listen to the whole talk at your leisure :-)
A Neural Basis for General Intelligence (Science)
Universal positive correlations between different cognitive tests motivate the concept of “general intelligence” or Spearman's g. Here the neural basis for g is investigated by means of positron emission tomography. Spatial, verbal, and perceptuo-motor tasks with high-g involvement are compared with matched low-g control tasks. In contrast to the common view that g reflects a broad sample of major cognitive functions, high-g tasks do not show diffuse recruitment of multiple brain regions. Instead they are associated with selective recruitment of lateral frontal cortex in one or both hemispheres. Despite very different task content in the three high-g–low-g contrasts, lateral frontal recruitment is markedly similar in each case. Many previous experiments have shown these same frontal regions to be recruited by a broad range of different cognitive demands. The results suggest that “general intelligence” derives from a specific frontal system important in the control of diverse forms of behavior.
The paper above is from 2000. Below is a more recent one, supplied by a commenter. The authors claim a linear model using MRI measurements of brain features (essentially, volumes and activities of particular subregions identified using fMRI) can account for 50% of the variance in g as measured in psychometric tests. Their sample size for the imaging analysis and initial fit of parameters was about 200, and an independent group of 48 was used to test the model.
Multiple Bases of Human Intelligence Revealed by Cortical Thickness and Neural Activation (Journal of Neuroscience)
Choi et al.
We hypothesized that individual differences in intelligence (Spearman’s g) are supported by multiple brain regions, and in particular that fluid (gF) and crystallized ( gC) components of intelligence are related to brain function and structure with a distinct profile of association across brain regions. In 225 healthy young adults scanned with structural and functional magnetic resonance imaging sequences, regions of interest (ROIs) were defined on the basis of a correlation between g and either brain structure or brain function. In these ROIs, gC was more strongly related to structure (cortical thickness) than function, whereas gF was more strongly related to function (blood oxygenation level-dependent signal during reasoning) than structure. We further validated this finding by generating a neurometric prediction model of intelligence quotient (IQ) that explained 50% of variance in IQ in an independent sample. The data compel a nuanced view of the neurobiology of intelligence, providing the most persuasive evidence to date for theories emphasizing multiple distributed brain regions differing in function.
From the conclusions:
... Although our model still does not approach the predictive power of psychometric tests, its high accuracy suggests that neurometric assessments of intelligence may soon become a useful complement to psychometric test. For example, brain images might be used to improve intelligence estimates for individuals whose psychometric scores systematically underestimate their IQ. We hope that future research will build on our neurometric model of intelligence, both refining it so that it generalizes to other populations and expanding it to enhance its accuracy.
Will someone please alert the ghost of Stephen J. Gould concerning dangerous reification activity? I imagine he might still be capable of issuing a fatwa (perhaps via the IMF ;-) despite the fact that this research was conducted in Korea. I'm sure these Koreans and their Yale collaborator are cooking their data just like old George Morton.
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