Understanding of the brain and the principles governing neural processing requires theories
that are parsimonious, can account for a diverse set of phenomena, and can make testable …

Categorical perception (CP) is likely the single finding from speech perception with the
biggest impact on cognitive science. However, within speech perception, it is widely known …

Like its predecessor, the revised Speech Learning Model (SLM-r) focuses on the learning of
L2 vowels and consonants (or “sounds,” for short) across the life-span. To define the context …

This volume outlines a model of language that can be characterized as functionalist, usage-
based, dynamic, and complex-adaptive. The core idea is that linguistic structure is not stable …

Why our use of language is highly creative yet also constrained We use words and phrases
creatively to express ourselves in ever-changing contexts, readily extending language …

We consider several key aspects of prediction in language comprehension: its
computational nature, the representational level (s) at which we predict, whether we use …

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the
brain deal successfully with the continual deluge of linguistic input? We argue that, to deal …

The discriminative lexicon is introduced as a mathematical and computational model of the
mental lexicon. This novel theory is inspired by word and paradigm morphology but …

It has been proposed that hierarchical prediction is a fundamental computational principle
underlying neurocognitive processing. Here, we ask whether the brain engages distinct …

Generalized additive mixed models are introduced as an extension of the generalized linear
mixed model which makes it possible to deal with temporal autocorrelational structure in …