Sentence Comprehension: The Integration of Habits and Rules

Using sentence comprehension as a case study for all of cognitive science, David Townsend and Thomas Bever offer an integration of two major approaches, the symbolic-computational and the associative-connectionist. The symbolic-computational approach emphasizes the formal manipulation of symbols that underlies creative aspects of language behavior. The associative-connectionist approach captures the intuition that most behaviors consist of accumulated habits. The authors argue that the sentence is the natural level at which associative and symbolic information merge during comprehension.

The authors develop and support an analysis-by-synthesis model that integrates associative and symbolic information in sentence comprehension. This integration resolves problems each approach faces when considered independently. The authors review classic and contemporary symbolic and associative theories of sentence comprehension, and show how recent developments in syntactic theory fit well with the integrated analysis-by-synthesis model. They offer analytic, experimental, and neurological evidence for their model and discuss its implications for broader issues in cognitive science, including the logical necessity of an integration of symbolic and connectionist approaches in the field.

Thomas G. Bever is Chair of the Linguistics Department at the University of Arizona.