Many theories have been developed to characterize variations in intelligence across the population (Carroll, 1993). For example, many scholars assume that individuals primarily vary on one attribute, called g or general intelligence. That is, people who exhibit elevated levels of g are adept at most tasks that demand intelligence or mental ability. People who exhibit low levels of g are impaired on most of these tasks.
Indeed, many researchers have attempted to characterize the biological basis of g. Some scholars maintain that g corresponds to neuronal plasticity--the rate at which the neurons and brain structure can change over time (see Garlick, 2002). Other scholars maintain that g primarily reflects processing efficiency, such as speed at which processes are completed as well as storage capacity (see Neubauer, Grabner, Freudenthaler, Beckman, & Guthke, 2004;; Haier, 1993).
Nevertheless, all scholars recognize that people can be more proficient than peers on one ask but less proficient than peers on other tasks, even after level of practice is controlled. That is, g and practice cannot be the only determinants of performance on various tasks.
To explain this observation, researchers tend to assume that other facets of intelligence, in addition to g, differentiate people. For example, some researchers assume that two facets of intelligence can be distinguished, sometimes called fluid and crystalized. Fluid intelligence is closely associated with entrenched capacities, such as reasoning ability. Crystalized intelligence is closely associated with capabilities that are learnt over time, such as vocabulary. Many other variations of this model have also been developed.
The verbal-perceptual-image rotation model represents a more recent attempt to characterize the facets of intelligence. The first variant of this model was developed by Johnson and Bouchard (2005). According to this model, g can be divided into three distinct facets: verbal, perceptual, and image rotation. As this model implies, people who excel on verbal tasks, such as the capacity to identify many words that begin with a specific letter, do not always excel on perceptual tasks, such as memorizing a visual pattern, or image rotation. Nevertheless, because of g, or generic capabilities, performance on these distinct capabilities are significantly, but not strongly, correlated with each other.
The second variant of this model was proposed by Johnson and Bouchard (2006). This model highlights that, besides g, performance varies across two dimensions. The first dimension differentiates verbal skills and image rotation. That is, people who excel on verbal skills do not excel on image rotation, and vice versa, at least after g is controlled. The second dimension represents focus of attention. In particular, people who excel on tasks that demand focusing on specific details do not excel on tasks that demand dividing attention on many details, and vice versa, again after controlling g.
The verbal-perceptual-image rotation model emerged from some data that were collected by Johnson and Bouchard (2005). In particular, they administered a battery of 42 mental ability tests to 436 adults. After subjecting these data, they uncovered three primary factors. The first factor, verbal, corresponded to fluency, scholastic ability, and verbal tasks. The second factor, perceptual, corresponded to spatial ability, perceptual speed, and content memory. The final factor corresponded to image rotation.
Furthermore, these three factors were positively correlated with each other. That is, g seemed to underpin or affect all three factors.
Johnson and Bouchard (2006) then conducted a similar study to clarify this model. In particular, they first undertook a regression to examine how performance on all the tasks relates to g or general intelligence. The residuals of these regression analyses represent variations in performance that cannot be explained by g. Next, they subjected these residuals-that is, performance that is unrelated to g-to confirmatory factor analyses. These analyses uncovered some intriguing results.
Specifically, two dimensions emerged. The first dimension differentiated verbal performance from image rotation. That is, after general intelligence was controlled, verbal performance was inversely related to image rotation. The second dimension distinguished focal attention from diffuse attention. Performance on tasks that demand a focus on specific details was inversely associated with performance on tasks that demand attention to many details, after controlling general intelligence.
Johnson, Jung, Colom, and Haier (2008) undertook a preliminary study to examine the neurological correlates of the verbal-perceptual-image rotation model of intelligence. Specifically, they examined whether the volumes of specific regions correlate with the two dimensions: image rotation versus verbal ability and focal attention versus diffuse attention.
Two distinct samples of participants, comprising 23 and 25 individuals respectively, completed the WAIS. To represent image rotation versus verbal ability, the difference between scores on block design and vocabulary was calculated. To represent focal attention versus diffuse attention, the researchers subtracted performance on coding and digit span from performance on block design and information. In addition, structural MRI was undertaken to measure the volume of grey matter, representing cell bodies, and white matter, representing axons-and often corresponding to the transmission of information-across the cortex and cerebellum.
People who performed well on image rotation instead of verbal ability showed elevated levels of:
People who performed well on verbal ability instead of image rotation showed elevated levels of:
People who performed well on focal attention versus diffuse attention showed elevated levels of:
Finally, people who performed well on diffuse attention versus focal attention showed elevated levels of:
These results indicate that many regions affect these facets of intelligence. Yet, because of the limited sample sizes, these findings need to be replicated.
Twin studies indicate that intelligence is appreciably explained by hereditary variation. Nevertheless, the association between variations on specific genes and general intelligence has been gravely overestimated, according to Chabris et al. (2012).
Specifically, these authors examined the associations between 12 specific genetic variations--in the genes DTNBP1, CTSD, DRD2,ANKK1, CHRM2, SSADH, COMT, BDNF, CHRNA4, DISC1, APOE, and SNAP25--and general intelligence in three large samples over time. Tests of intelligence included the Henmon-Nelson Test of Mental Ability and the WAIS. Only one of 32 relationships reached significance, appreciably fewer than expected by chance given the large sample size. These findings imply that general intelligence cannot be ascribed to merely a circumscribed set of genes. Conceivably, the pursuit of specific genes to explain intelligence is, at this time, a futile endeavor.
According to the parieto-fronto integration theory of intelligence, developed by Jung and Haier (2007), the regions that underpin intelligence depends on the stage of processing. Specifically, this theory assumes that information processing entails four overlapping stages:
The arcuate fasciculus, a neural pathway that connects the temporal parietal junction with frontal regions, as well as other white matter, is integral to the communication of information across these regions. Nevertheless, only the parietal regions and dorsolateral prefrontal cortex are essential to intelligence, according to this model.
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Carroll, J. B. (1993). Human cognitive abilities: A survey of factor analytic studies. Cambridge, England: Cambridge University Press.
Chabris, C. F., Hebert, B. M., Benjamin, D. J., Beauchamp, J., Cesarini, D., van der Loos, M., Johannesson, M., et al. (2012). Most reported genetic associations with general intelligence are probably false positives. Psychological science, 23, 1314-1323. doi:10.1177/0956797611435528
Johnson, W., & Bouchard Jr., T. J. (2005). The Structure of Human Intelligence: It's verbal, perceptual, and image rotation (VPR), not fluid and crystallized. Intelligence, 33, 3930-416.
Johnson, W., & Bouchard Jr., T. J. (2006). Sex differences in mental ability: g masks the dimensions on which they lie. Intelligence, 35, 23-39.
Johnson, W., Jung, R. E., Colom, R., & Haier, R. J. (2008). Cognitive abilities independent of IQ correlate with regional brain structure. Intelligence, 36, 18-28.
Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral Brain Sciences, 30, 135-154.
Last Update: 7/19/2016