Evidence for a genetic component in chronometric performance assures us that reliable measures of individual differences reflect a biological basis and that variation in the brain mechanisms involved are not solely the result of influences occurring after conception. Any nongenetic effects could be attributable to exogenous biological influences, such as disease or trauma, or to nutrition in early development, or to purely experiential effects that transfer to an individual's performance on chronometric tasks, for instance, practice in playing video games.
In addition to heritability of individual differences in performance on a given chronometric task, it is important to know the nature of the task's correlation with other variables that lend some degree of ecological validity (i.e., the variable's correlation with 'real life' performances generally deemed as important in a given society). Two distinct variables, for example, reaction time (RT) and IQ, could each be highly heritable, but the correlation between them could be entirely due to nongenetic factors. The two variables, say, RT and IQ, could each be indirectly correlated with each other via each one's correlation with a quite different variable that causally affects both variables, for example, some nutritional factor. On the other hand, two variables could be genetically correlated. A genetic correlation, which is determined by a particular type of genetic analysis, indicates that the variables have certain genetic influences in common, though other specific genetic or environmental factors may also affect each variable independently. In the terminology of behavioral genetics, both genetic and environmental effects may be either common (or shared), in whole or in part, between two or more individuals, or they may be specific (or unshared) for each individual.
There are two types of genetic correlation between kinships: (1) simple genetic correlation and (2) pleiotropic correlation.
In a simple genetic correlation different genetic factors, a and b, for different phe-notypic traits, A and B, are correlated in the population because of population heterogeneity due to cross-assortative mating for the two traits. Hence within any given family, in meiosis, the genes for each trait are independently and randomly passed on to each of the offspring. Because of independent, random assortment of the genes going to each sibling, the causal connections a^A and b^B themselves have no causal connection in common. A well-established example is the population correlation between height and IQ. These phenotypes are correlated about .20 in the general population, although there is no causal connection whatsoever between genes for height and genes for IQ, as shown by the fact that there is zero correlation between the height and IQ of full siblings (Jensen & Sinha, 1993). All of the population correlation between height and IQ exists between families; none of the correlation exists within families (i.e., between full siblings).
In a pleiotropic correlation, a single gene has two (or more) different phenotypic effects, which therefore are necessarily correlated within families. The sibling who has the pleiotropic gene will show both phenotypic traits; the child who does not have the gene will show neither of the traits. An example is the double-recessive gene for phenylketonuria (PKU), which results in two effects:(1) mental retardation and (2) a lighter pigmentation of hair and skin color than the characteristic of the siblings without the PKU gene. (Nowadays, the unfortunate developmental consequences of PKU are ameliorated by dietary means.) Another likely example of pleiotropy is the well-established correlation (about + .25) between myopia and IQ. The absence of a within-family correlation between two distinct phenotypic traits contraindicates a pleiotropic correlation. The presence of a within-family correlation between two distinct phenotypes, however, is not by itself definitive evidence of pleiotropy, because the correlation could possibly be caused by some environmental factor that affects both phenotypes. Pleiotropy can be indicated by the method of cross-twin correlations between two distinct variables (e.g., different test scores), A and B. The method is applicable to both monozygotic, twins reared apart (MZA) and monozygotic, twins reared together -dizygotic, twins reared together (MZT-DZT) designs. Pleiotropy is indicated if the MZA twins in each pair (labeled MZA1 and MZA2), show essentially the same cross-correlations on tests A and B, i.e., the cross-correlation between test A scores of MZA1 and test B scores of MZA2, and twins 2 are significant and virtually the same as the correlations between A scores of MZA1 and B scores of MZA1 (and also the same for MZA2). The two main types of genetic correlation, simple, and pleiotropic, are illustrated in Figure 7.1, the direct and cross-twin correlations in Figure 7.2.
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