Publications

Abstract

No idea is older in the history of linguistics than the thought that there is, somehow hidden underneath the surface of sentences, a form or a structure which provides a semantic analysis and lays bare their logical structure. In Plato’s Cratylus the theory was proposed, deriving from Heraclitus’ theory of explanatory underlying structure in physical nature, that words contain within themselves bits of syntactic structure giving their meanings. The Stoics held the same view and maintained moreover that every sentence has an underlying logical structure, which for them was the Aristotelian subject- predicate form. They even proposed transformational processes to derive the surface from the deep structure. The idea of a semantically analytic logical form underlying the sentences of every language kept reappearing in various guises at various times. Quite recently it re-emerged under the name of generative semantics.

Abstract

Traditional psycholinguistic studies take place in controlled experimental labs and typically involve testing undergraduate psychology or linguistics students. Investigating psycholinguistics in this manner calls into question the external validity of findings, that is, the extent to which research findings generalize across languages and cultures, as well as ecologically valid settings. Here we consider three ways in which psycholinguistics can be taken out of the lab. First, researchers can conduct cross-cultural fieldwork in diverse languages and cultures. Second, they can conduct online experiments or experiments in institutionalized public spaces (e.g., museums) to obtain large, diverse participant samples. And, third, researchers can perform studies in more ecologically valid settings, to increase the real-world generalizability of findings. By moving away from the traditional lab setting, psycholinguists can enrich their understanding of language use in all its rich and diverse contexts.

Abstract

The artificial grammar learning (AGL) paradigm enables systematic investigation of the acquisition of linguistically relevant structures. It is a paradigm of interest for language processing research, interfacing with theoretical linguistics, and for comparative research on language acquisition and evolution. This chapter presents a key for understanding major variants of the paradigm. An unbiased summary of neuroimaging findings of AGL is presented, using meta-analytic methods, pointing to the crucial involvement of the bilateral frontal operculum and regions in the right lateral hemisphere. Against a background of robust posterior temporal cortex involvement in processing complex syntax, the evidence for involvement of the posterior temporal cortex in AGL is reviewed. Infant AGL studies testing for neural substrates are reviewed, covering the acquisition of adjacent and non-adjacent dependencies as well as algebraic rules. The language acquisition data suggest that comparisons of learnability of complex grammars performed with adults may now also be possible with children.

Abstract

The primary goal of psycholinguistic research is to understand the architectures and mechanisms that underlie human language comprehension and production. This entails an understanding of how linguistic knowledge is represented and organized in the brain and a theory of how that knowledge is accessed when we use language. Research has traditionally emphasized purely linguistic aspects of on-line comprehension, such as the influence of lexical, syntactic, semantic and discourse constraints, and their tim -course. It has become increasingly clear, however, that nonlinguistic information, such as the visual environment, are also actively exploited by situated language comprehenders.

Abstract

Field data are drawn from a particular speech community at a certain place and time. The intent of this survey is to enrich understanding of the various socio-cultural contexts in which linguistic and “cognitive” data may have been collected, so that we can explore the role which societal, cultural and contextual factors may play in this material. The questionnaire gives guidelines concerning types of ethnographic information that are important to cross-cultural and cross-linguistic enquiry, and will be especially useful to researchers who do not have specialised training in anthropology.

Abstract

How do languages encode different kinds of movement, and what features do people pay attention to when describing motion events? This document outlines topics concerning the investigation of “enter” and “exit” events. It helps contextualise research tasks that examine this domain (see 'Motion Elicitation' and 'Enter/Exit animation') and gives some pointers about what other questions can be explored.

Abstract

How do languages encode different kinds of movement, and what features do people pay attention to when describing motion events? This task investigates the expression of “enter” and “exit” activities, that is, events involving motion in(to) and motion out (of) container-like items. The researcher first uses particular stimuli (a ball, a cup, rice, etc.) to elicit descriptions of enter/exit events from one consultant, and then asks another consultant to demonstrate the event based on these descriptions. See also the related entries Enter/Exit Animation and Background Questions for Enter/Exit Research.

Abstract

Here we review evidence from cognitive neuroscience for a tight relation between language and action in the brain. We focus on two types of relation between language and action. First, we investigate whether the perception of speech and speech sounds leads to activation of parts of the cortical motor system also involved in speech production. Second, we evaluate whether understanding action-related language involves the activation of parts of the motor system. We conclude that whereas there is considerable evidence that understanding language can involve parts of our motor cortex, this relation is best thought of as inherently flexible. As we explain, the exact nature of the input as well as the intention with which language is perceived influences whether and how motor cortex plays a role in language processing.

Abstract

Word learning happens in everyday contexts with many words and many potential referents for those words in view at the same time. It is challenging for young learners to find the correct referent upon hearing an unknown word at the moment. This problem of referential uncertainty has been deemed as the crux of early word learning (Quine, 1960). Recent empirical and computational studies have found support for a statistical solution to the problem termed cross-situational learning. Cross-situational learning allows learners to acquire word meanings across multiple exposures, despite each individual exposure is referentially uncertain. Recent empirical research shows that infants, children and adults rely on cross-situational learning to learn new words (Smith & Yu, 2008; Suanda, Mugwanya, & Namy, 2014; Yu & Smith, 2007). However, researchers have found evidence supporting two very different theoretical accounts of learning mechanisms: Hypothesis Testing (Gleitman, Cassidy, Nappa, Papafragou, & Trueswell, 2005; Markman, 1992) and Associative Learning (Frank, Goodman, & Tenenbaum, 2009; Yu & Smith, 2007). Hypothesis Testing is generally characterized as a form of learning in which a coherent hypothesis regarding a specific word-object mapping is formed often in conceptually constrained ways. The hypothesis will then be either accepted or rejected with additional evidence. However, proponents of the Associative Learning framework often characterize learning as aggregating information over time through implicit associative mechanisms. A learner acquires the meaning of a word when the association between the word and the referent becomes relatively strong. In this chapter, we consider these two psychological theories in the context of cross-situational word-referent learning. By reviewing recent empirical and cognitive modeling studies, our goal is to deepen our understanding of the underlying word learning mechanisms by examining and comparing the two theoretical learning accounts.