Publications

Displaying 101 - 113 of 113
  • Skiba, R. (1989). Funktionale Beschreibung von Lernervarietäten: Das Berliner Projekt P-MoLL. In N. Reiter (Ed.), Sprechen und Hören: Akte des 23. Linguistischen Kolloquiums, Berlin (pp. 181-191). Tübingen: Niemeyer.
  • Thomaz, A. L., Lieven, E., Cakmak, M., Chai, J. Y., Garrod, S., Gray, W. D., Levinson, S. C., Paiva, A., & Russwinkel, N. (2019). Interaction for task instruction and learning. In K. A. Gluck, & J. E. Laird (Eds.), Interactive task learning: Humans, robots, and agents acquiring new tasks through natural interactions (pp. 91-110). Cambridge, MA: MIT Press.
  • Van Berkum, J. J. A., & Nieuwland, M. S. (2019). A cognitive neuroscience perspective on language comprehension in context. In P. Hagoort (Ed.), Human language: From genes and brain to behavior (pp. 429-442). Cambridge, MA: MIT Press.
  • Van Wijk, C., & Kempen, G. (1985). From sentence structure to intonation contour: An algorithm for computing pitch contours on the basis of sentence accents and syntactic structure. In B. Müller (Ed.), Sprachsynthese: Zur Synthese von natürlich gesprochener Sprache aus Texten und Konzepten (pp. 157-182). Hildesheim: Georg Olms.
  • Van Wijk, C., & Kempen, G. (1982). Kost zinsbouw echt tijd? In R. Stuip, & W. Zwanenberg (Eds.), Handelingen van het zevenendertigste Nederlands Filologencongres (pp. 223-231). Amsterdam: APA-Holland University Press.
  • Verga, L., Schwartze, M., & Kotz, S. A. (2023). Neurophysiology of language pathologies. In M. Grimaldi, E. Brattico, & Y. Shtyrov (Eds.), Language Electrified: Neuromethods (pp. 753-776). New York, NY: Springer US. doi:10.1007/978-1-0716-3263-5_24.

    Abstract

    Language- and speech-related disorders are among the most frequent consequences of developmental and acquired pathologies. While classical approaches to the study of these disorders typically employed the lesion method to unveil one-to-one correspondence between locations, the extent of the brain damage, and corresponding symptoms, recent advances advocate the use of online methods of investigation. For example, the use of electrophysiology or magnetoencephalography—especially when combined with anatomical measures—allows for in vivo tracking of real-time language and speech events, and thus represents a particularly promising venue for future research targeting rehabilitative interventions. In this chapter, we provide a comprehensive overview of language and speech pathologies arising from cortical and/or subcortical damage, and their corresponding neurophysiological and pathological symptoms. Building upon the reviewed evidence and literature, we aim at providing a description of how the neurophysiology of the language network changes as a result of brain damage. We will conclude by summarizing the evidence presented in this chapter, while suggesting directions for future research.
  • 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., & Klein, W. (1989). Referential movement in descriptive and narrative discourse. In R. Dietrich, & C. F. Graumann (Eds.), Language processing in social context (pp. 39-76). Amsterdam: Elsevier.
  • Weissenborn, J., & Stralka, R. (1984). Das Verstehen von Mißverständnissen. Eine ontogenetische Studie. In Zeitschrift für Literaturwissenschaft und Linguistik (pp. 113-134). Stuttgart: Metzler.
  • Weissenborn, J. (1984). La genèse de la référence spatiale en langue maternelle et en langue seconde: similarités et différences. In G. Extra, & M. Mittner (Eds.), Studies in second language acquisition by adult immigrants (pp. 262-286). Tilburg: Tilburg University.
  • Weissenborn, J. (1986). Learning how to become an interlocutor. The verbal negotiation of common frames of reference and actions in dyads of 7–14 year old children. In J. Cook-Gumperz, W. A. Corsaro, & J. Streeck (Eds.), Children's worlds and children's language (pp. 377-404). Berlin: Mouton de Gruyter.
  • 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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