The brain-sex theory of occupational choice: a counterexample

The brain-sex theory of occupational choice suggests that males and females in male-typical careers show a male pattern of cognitive ability in terms of better spatial than verbal performance on cognitive tests with the reverse pattern for females and males in female-typical careers, These differences are thought to result from patterns of cerebral functional lateralisation. This study Sought Such occupationally related effects using synonym generation (verbal ability) and mental rotation (spatial ability) tasks used previously. It also used entrants to these careers as participants to examine whether patterns of cognitive abilities might predate explicit training and practice. Using a population of entrants to sex-differentiated University Courses, a moderate occupational effect on the synonym generation task was found, along with a weak (p<.10) sex effect on the mental rotation task. Highest performance on the mental rotation task was by female Students in fashion design, a female-dominated occupation which makes substantial visuospatial demands and attracts many students with literacy problems such as dyslexia. This group then appears to be a counterexample to the brain-sex theory. However, methodological issues Surrounding previous Studies are highlighted: the simple synonym task appears to show limited discrimination of the sexes, leading to questions concerning the legitimacy of inferences about lateralisation based on scores from that test. Moreover, the human figure-based mental rotation task appears to tap the wrong aspect of visuospatial skill, likely to be needed for male-typical courses such as engineering, Since the fashion-clesign career is also one that attracts disproportionately many male students whose sexual orientation is homosexual, data were examined for evidence of female-typical patterns of cognitive performance among that subgroup. This was not found. This study therefore provides Do evidence for the claim that female-pattern cerebral functional lateralisation is likely in gay males.

What is universal and what differs in language development?

Goldin-Meadow (2015) presents an exceptional synthesis of work from studies of children acquiring language under variable circumstances of input or processing abilities. Deaf children who acquire homesign without any well- formed model from which to learn language represent a powerful example. Goldin-Meadow argues that the resilient properties of language that nevertheless emerge include simple syntactic structures, hierarchical organisa- tion, markers modulating the meaning of sentences, and social-communicative functions. Among the fragile or input-dependent properties are the orders that the language follows, the parts into which words are decomposed, and the features that distinguish nominals from predicates. Separation of these two types of properties poses questions concerning the innate constraints on language acquisition (perhaps these equate to the resilient properties) and con‐ cerning the specificity of processes to language (e.g., whether properties such as hierarchical organisation are specific to language or originate in the structure of thought). The study of the resilient properties of human language in the face of adversity and the relation of these properties to the information that is encoded in the human genome represent a research strategy that draws inferences about species universals (properties that all humans share) from data about individual differences (IDs; factors that make humans different from one another). In the following, we suggest three reasons to be cautious about this approach.

Fractionating Human Intelligence

What makes one person more intellectually able than another? Can the entire distribution of human intelligence be accounted for by just one general factor? Is intelligence supported by a single neural system? Here, we provide a perspective on human intelligence that takes into account how general abilities or ‘‘factors’’ reflect the functional organiza- tion of the brain. By comparing factor models of individual differences in performance with factor models of brain functional organization, we demon- strate that different components of intelligence have their analogs in distinct brain networks. Using simulations based on neuroimaging data, we show that the higher-order factor ‘‘g’’ is accounted for by cognitive tasks corecruiting multiple networks. Finally, we confirm the independence of these com- ponents of intelligence by dissociating them using questionnaire variables. We propose that intelli- gence is an emergent property of anatomically distinct cognitive systems, each of which has its own capacity.