Dynamics of structural priming
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This thesis is about how our syntactic choice changes with linguistic experience. Studies on syntactic priming show that our decisions are influenced by sentences that we have recently heard or recently spoken. They also show that not all sentences have an equal amount of influence; that repetition of verbs increases priming (the lexical-boost effect) and that some verbs are more susceptible to priming than others. This thesis explores how and why syntactic decisions change with time and what these observations tell us about the cognitive mechanism of speaking. Specifically, we set out to develop a theoretical account of syntactic priming. Theoretical accounts require mathematical models and this thesis develops a sequence of mathematical models for understanding various aspects of syntactic priming. Cognitive processes are modelled as dynamical systems that can change their behaviour when they process information. We use these dynamical systems to investigate how each episode of language comprehension or production affects syntactic decisions. We also use these systems to investigate how long priming persists, how groups of consecutive sentences affect structural decisions, why repeating words leads to greater syntactic priming and what this tells us about how words, concepts and syntax are cognitively represented. We obtain two kinds of results by simulating these mathematical models. The first kind of results reveal how syntactic priming evolves over time. We find that structural priming itself shows a gradual decay with time but the lexical enhancement of priming decays catastrophically – a result consistent with experimental observations. We also find that consecutive episodes of language processing add up nonlinearly in memory, which challenges the design of some existing psycholinguistic experiments. The second kind of results reveal how our syntax module might be connected to other cognitive modules. We find that the lexical enhancement of syntactic priming might be a consequence of how the modules of attention and working memory influence syntactic decisions. These models suggest a mechanism of priming that is in contrast to a previous prediction-based account. This prediction-based account proposes that we actively predict what we hear and structural priming is due to error-correction whenever our predictions do not match the stimuli. In contrast, our account embodies syntactic priming in cognitive processes of attention, working memory and long-term memory. It asserts that our linguistic decisions are not based solely on abstract rules but also depend on the cognitive implementation of each module. Our investigations also contribute a novel theoretical framework for studying syntactic priming. Previous studies analyse priming using error-correction or Hebbian learning algorithms. We introduce the formalism of dynamical systems. This formalism allows us to trace the effect of information processing through time. It explains how residual activation from a previous episode might play a role in structural decisions, thereby enriching our understanding of syntactic priming. Since these dynamical systems are also used to model neural processes, this theoretical framework brings our understanding of priming one step closer to its biological implementation, bridging the gap between neural processes and abstract thoughts.