Can intelligence be studied scientifically?
Yes, absolutely. There is a myth that there is no definition or assessment of intelligence precise enough for scientific investigation. For most empirical research studies, intelligence is defined as a general mental ability common to all specific mental abilities. This is the g-factor, first described by Charles Spearman more than 100 years ago. There are other more specific factors as well, including verbal, numerical, and spatial. Some mental abilities are more g-loaded than others but g is pervasive.
IQ tests sample several mental abilities so IQ is a good estimate of g. So is the total SAT score. The g-factor is normally distributed (i.e. the Bell Curve) in the population so where you fall is relative to other people and can be described as a percentile. An IQ sore of 130, for example, is in the top 2 percent of the population. However, IQ points are not like pounds or pints—they are not absolute measures, so caution is required when interpreting changes in IQ or other intelligence test scores. Note that advances in technology usually lead to more precise definitions—think about how the definitions of an atom or a gene have changed with research advances. The same is true for intelligence.
What does brain imaging research show about intelligence?
Richard’s first imaging paper with positron emission tomography (PET) in 1988 identified inverse correlations between cerebral glucose metabolic rate and performance on a high g-loaded test of intelligence. This finding was the basis for the brain efficiency hypothesis of intelligence.
There are now numerous studies supporting and refining the efficiency hypothesis. For example, two brain imaging papers showed increased efficiency after acquiring expertise in the computer game Tetris. Nearly 100 brain imaging studies of intelligence now demonstrate that intelligence test scores are correlated to specific brain characteristics, including gray and white matter, and functional activity in specific brain areas.
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The Parieto-Frontal Integration Theory (P-FIT) model of intelligence
A detailed model of relevant brain areas and the neural basis of intelligence was developed with Rex Jung and published in 2007, along with commentaries from other researchers in the field. (This paper was identified by Thomson Reuters Essential Science Indicators as a Fast Breaking Paper in the field of Neuroscience & Behavior, and was one of the most cited papers—upper 1 percent—in its discipline during the subsequent two years). A number of independent papers now support the P-FIT model.