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Working memory and language are tightly intertwined cognitive systems. Working memory enables language acquisition and vocabulary expansion; it supports both language comprehension and language production. Language, on the other hand, provides key representations that support efficient and robust encoding and maintenance of information in working memory, as well as the ability to compress information and the redundancy to reconstruct it in case of partial information loss. The close relationship can also be observed in the overlap and integration of brain systems and networks supporting working memory and language processing. This chapter examines the brain substrate of working memory and language processes, focusing on their interdependence, synergy, and the mechanisms underlying their close integration. It integrates key theoretical models and empirical evidence from behavioural and neuroimaging studies, computational modelling, and insights based on patterns of working memory and language dysfunctions due to brain injury and disease.
Computational models are like the new kids in town for the field of decision making. This field is dominated by axiomatic utility theories or simple heuristic rule models. Decision theory has a long history, starting as early as the seventeenth century with probabilistic theories of gambling by Blaise Pascal and Pierre Fermat. In an attempt to retain the basic utility framework, constraints on utility theories are being relaxed, and the formulas are becoming more deformed. Recently, many researchers have responded to the growing corpus of phenomena that challenge traditional utility models by applying wholly different approaches. This chapter provides concrete illustration of how the computational approach can account for all of the behavioral paradoxes that have contested utility theories. The extent to which the other computational models have been successful in accounting for the results is also discussed.