Connectionism is an important theoretical framework for the study of human cognition and behavior. Also known as Parallel Distributed Processing (PDP) or Artificial Neural Networks (ANN), connectionism advocates that learning, representation, and processing of information in mind are parallel, distributed, and interactive in nature. It argues for the emergence of human cognition as the outcome of large networks of interactive processing units operating simultaneously. Inspired by findings from neural science and artificial intelligence, connectionism is a powerful computational tool, and it has had profound impact on many areas of research, including linguistics. Since the beginning of connectionism, many connectionist models have been developed to account for a wide range of important linguistic phenomena observed in monolingual research, such as speech perception, speech production, semantic representation, and early lexical development in children. Recently, the application of connectionism to bilingual research has also gathered momentum. Connectionist models are often precise in the specification of modeling parameters and flexible in the manipulation of relevant variables in the model to address relevant theoretical questions, therefore they can provide significant advantages in testing mechanisms underlying language processes.
Throughout the 20th century, structuralist and generative linguists have argued that the study of the language system (langue, competence) must be separated from the study of language use (parole, performance), but this view of language has been called into question by usage-based linguists who have argued that the structure and organization of a speaker’s linguistic knowledge is the product of language use or performance. On this account, language is seen as a dynamic system of fluid categories and flexible constraints that are constantly restructured and reorganized under the pressure of domain-general cognitive processes that are not only involved in the use of language but also in other cognitive phenomena such as vision and (joint) attention. The general goal of usage-based linguistics is to develop a framework for the analysis of the emergence of linguistic structure and meaning.
In order to understand the dynamics of the language system, usage-based linguists study how languages evolve, both in history and language acquisition. One aspect that plays an important role in this approach is frequency of occurrence. As frequency strengthens the representation of linguistic elements in memory, it facilitates the activation and processing of words, categories, and constructions, which in turn can have long-lasting effects on the development and organization of the linguistic system. A second aspect that has been very prominent in the usage-based study of grammar concerns the relationship between lexical and structural knowledge. Since abstract representations of linguistic structure are derived from language users’ experience with concrete linguistic tokens, grammatical patterns are generally associated with particular lexical expressions.