On the domain specificity of the human language faculty and the effects of principles of computational efficiency: contrasting language and mathematics

Resumo

The growth of language in the individual is determined by genetics, experience and principles of computational efficiency. The latter are taken to be part of natural laws affecting the development of biological systems. We discuss the effect of two principles of computational efficiency applying to the derivation of linguistic expressions and their interface representations. We develop the hypothesis that these principles are domain specific. They apply to language computations, but not to other cognitive computations. In this perspective, we contrast language and mathematics. We focus on indirect recursion, the recursive merger of a given projection X mediated by a functional element F: [X [ F X ]]. We posit that indirect recursion is forced by the principle of efficient computation
Minimize Symmetrical Relations, whereas the intermediate functional head is not necessarily legible at the sensorimotor interface as enforced by the principle of Minimize Externalization. We discuss the results of psycholinguistic studies on the processing of complex nominals in English, which bring experimental support to our hypothesis. Furthermore, we provide evidence that indirect recursion, enforced by Minimize Symmetrical Relations and Minimize Externalization, holds for complex numerals, according to language specific parameters, differentiating, for example, Russian from Arabic. The facts indicate that indirect recursion is characteristic of the computational procedure of the human language faculty, while concatenation is available for mathematical operations in humans and animals. We discuss recent contributions of neuroscience with respect to the identification of brain pathways for language and mathematical computation. Theoretical and experimental results indicate that Minimize Symmetrical Relations and Minimize Externalization affect the computation and the processing of linguistic expressions by the human brain whereas there is no evidence that this would be the case for mathematical formulae.

DOI: 10.17074/2238-975X.2015v11n1p28