A parallel architecture perspective on pre-activation and prediction in language processing

A recent trend in psycholinguistic research has been to posit prediction as an essential function of language processing. The present paper develops a linguistic perspective on viewing prediction in terms of pre-activation. We describe what predictions are and how they are produced. Our basic premises are that (a) no prediction can be made without knowledge to support it; and (b) it is therefore necessary to characterize the precise form of that knowledge, as revealed by a suitable theory of linguistic representations. We describe the Parallel Architecture (PA: Jackendoff, 2002; Jackendoff & Audring, 2020), which makes explicit our commitments about linguistic representations, and we develop an account of processing based on these representations. Crucial to our account is that what have been traditionally treated as derivational rules of grammar are formalized by the PA as lexical items, encoded in the same format as words. We then present a theory of prediction in these terms: linguistic input activates lexical items whose beginning (or incipit) corresponds to the input encountered so far; and prediction amounts to pre-activation of the as yet unheard parts of those lexical items (the remainder). Thus the generation of predictions is a natural byproduct of processing linguistic representations. We conclude that the PA perspective on pre-activation provides a plausible account of prediction in language processing that bridges linguistic and psycholinguistic theorizing.