Publications

Displaying 201 - 216 of 216
  • Van Geenhoven, V. (1998). On the Argument Structure of some Noun Incorporating Verbs in West Greenlandic. In M. Butt, & W. Geuder (Eds.), The Projection of Arguments - Lexical and Compositional Factors (pp. 225-263). Stanford, CA, USA: CSLI Publications.
  • Van Valin Jr., R. D. (2009). Privileged syntactic arguments, pivots and controllers. In L. Guerrero, S. Ibáñez, & V. A. Belloro (Eds.), Studies in role and reference grammar (pp. 45-68). Mexico: Universidad Nacional Autónoma de México.
  • Van Valin Jr., R. D. (1998). The acquisition of WH-questions and the mechanisms of language acquisition. In M. Tomasello (Ed.), The new psychology of language: Cognitive and functional approaches to language structure (pp. 221-249). Mahwah, New Jersey: Erlbaum.
  • Van Valin Jr., R. D. (2009). Role and reference grammar. In F. Brisard, J.-O. Östman, & J. Verschueren (Eds.), Grammar, meaning, and pragmatics (pp. 239-249). Amsterdam: Benjamins.
  • Van Valin Jr., R. D. (2010). Role and reference grammar as a framework for linguistic analysis. In B. Heine, & H. Narrog (Eds.), The Oxford handbook of linguistic analysis (pp. 703-738). Oxford: Oxford University Press.
  • van Hell, J. G., & Witteman, M. J. (2009). The neurocognition of switching between languages: A review of electrophysiological studies. In L. Isurin, D. Winford, & K. de Bot (Eds.), Multidisciplinary approaches to code switching (pp. 53-84). Philadelphia: John Benjamins.

    Abstract

    The seemingly effortless switching between languages and the merging of two languages into a coherent utterance is a hallmark of bilingual language processing, and reveals the flexibility of human speech and skilled cognitive control. That skill appears to be available not only to speakers when they produce language-switched utterances, but also to listeners and readers when presented with mixed language information. In this chapter, we review electrophysiological studies in which Event-Related Potentials (ERPs) are derived from recordings of brain activity to examine the neurocognitive aspects of comprehending and producing mixed language. Topics we discuss include the time course of brain activity associated with language switching between single stimuli and language switching of words embedded in a meaningful sentence context. The majority of ERP studies report that switching between languages incurs neurocognitive costs, but –more interestingly- ERP patterns differ as a function of L2 proficiency and the amount of daily experience with language switching, the direction of switching (switching into L2 is typically associated with higher switching costs than switching into L1), the type of language switching task, and the predictability of the language switch. Finally, we outline some future directions for this relatively new approach to the study of language switching.
  • Verhagen, J. (2009). Light verbs and the acquisition of finiteness and negation in Dutch as a second language. In C. Dimroth, & P. Jordens (Eds.), Functional categories in learner language (pp. 203-234). Berlin: Mouton de Gruyter.
  • Verkerk, A. (2009). A semantic map of secondary predication. In B. Botma, & J. Van Kampen (Eds.), Linguistics in the Netherlands 2009 (pp. 115-126).
  • Vernes, S. C. (2019). Neuromolecular approaches to the study of language. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 577-593). Cambridge, MA: MIT Press.
  • Von Stutterheim, C., Carroll, M., & Klein, W. (2009). New perspectives in analyzing aspectual distinctions across languages. In W. Klein, & P. Li (Eds.), The expression of time (pp. 195-216). Berlin: Mouton de Gruyter.
  • Weber, A., Crocker, M., & Knoeferle, P. (2010). Conflicting constraints in resource-adaptive language comprehension. In M. W. Crocker, & J. Siekmann (Eds.), Resource-adaptive cognitive processes (pp. 119-141). New York: Springer.

    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.
  • Willems, R. M., & Hagoort, P. (2010). Cortical motor contributions to language understanding. In L. Hermer (Ed.), Reciprocal interactions among early sensory and motor areas and higher cognitive networks (pp. 51-72). Kerala, India: Research Signpost Press.

    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.
  • Wittenburg, P., & Trilsbeek, P. (2010). Digital archiving - a necessity in documentary linguistics. In G. Senft (Ed.), Endangered Austronesian and Australian Aboriginal languages: Essays on language documentation, archiving and revitalization (pp. 111-136). Canberra: Pacific Linguistics.
  • Wood, N. (2009). Field recording for dummies. In A. Majid (Ed.), Field manual volume 12 (pp. V). Nijmegen: Max Planck Institute for Psycholinguistics.
  • Zhang, Y., Chen, C.-h., & Yu, C. (2019). Mechanisms of cross-situational learning: Behavioral and computational evidence. In Advances in Child Development and Behavior; vol. 56 (pp. 37-63).

    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.
  • Zuidema, W., & Fitz, H. (2019). Key issues and future directions: Models of human language and speech processing. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 353-358). Cambridge, MA: MIT Press.

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