Publications

Displaying 1 - 16 of 16
  • Chang, F., & Fitz, H. (2014). Computational models of sentence production: A dual-path approach. In M. Goldrick, & M. Miozzo (Eds.), The Oxford handbook of language production (pp. 70-89). Oxford: Oxford University Press.

    Abstract

    Sentence production is the process we use to create language-specific sentences that convey particular meanings. In production, there are complex interactions between meaning, words, and syntax at different points in sentences. Computational models can make these interactions explicit and connectionist learning algorithms have been useful for building such models. Connectionist models use domaingeneral mechanisms to learn internal representations and these mechanisms can also explain evidence of long-term syntactic adaptation in adult speakers. This paper will review work showing that these models can generalize words in novel ways and learn typologically-different languages like English and Japanese. It will also present modeling work which shows that connectionist learning algorithms can account for complex sentence production in children and adult production phenomena like structural priming, heavy NP shift, and conceptual/lexical accessibility.
  • Fitz, H. (2014). Computermodelle für Spracherwerb und Sprachproduktion. Forschungsbericht 2014 - Max-Planck-Institut für Psycholinguistik. In Max-Planck-Gesellschaft Jahrbuch 2014. München: Max Planck Society for the Advancement of Science. Retrieved from http://www.mpg.de/7850678/Psycholinguistik_JB_2014?c=8236817.

    Abstract

    Relative clauses are a syntactic device to create complex sentences and they make language structurally productive. Despite a considerable number of experimental studies, it is still largely unclear how children learn relative clauses and how these are processed in the language system. Researchers at the MPI for Psycholinguistics used a computational learning model to gain novel insights into these issues. The model explains the differential development of relative clauses in English as well as cross-linguistic differences
  • Hagoort, P. (2014). Introduction to section on language and abstract thought. In M. S. Gazzaniga, & G. R. Mangun (Eds.), The cognitive neurosciences (5th ed., pp. 615-618). Cambridge, Mass: MIT Press.
  • Hagoort, P., & Levinson, S. C. (2014). Neuropragmatics. In M. S. Gazzaniga, & G. R. Mangun (Eds.), The cognitive neurosciences (5th ed., pp. 667-674). Cambridge, Mass: MIT Press.
  • Schoffelen, J.-M., & Gross, J. (2014). Studying dynamic neural interactions with MEG. In S. Supek, & C. J. Aine (Eds.), Magnetoencephalography: From signals to dynamic cortical networks (pp. 405-427). Berlin: Springer.
  • Van Leeuwen, T. M., Petersson, K. M., Langner, O., Rijpkema, M., & Hagoort, P. (2014). Color specificity in the human V4 complex: An fMRI repetition suppression study. In T. D. Papageorgiou, G. I. Cristopoulous, & S. M. Smirnakis (Eds.), Advanced Brain Neuroimaging Topics in Health and Disease - Methods and Applications (pp. 275-295). Rijeka, Croatia: Intech. doi:10.5772/58278.
  • Casasanto, D. (2009). Space for thinking. In V. Evans, & P. Chilton (Eds.), Language, cognition and space: State of the art and new directions (pp. 453-478). London: Equinox Publishing.
  • Casasanto, D. (2009). When is a linguistic metaphor a conceptual metaphor? In V. Evans, & S. Pourcel (Eds.), New directions in cognitive linguistics (pp. 127-145). Amsterdam: Benjamins.
  • Fedor, A., Pléh, C., Brauer, J., Caplan, D., Friederici, A. D., Gulyás, B., Hagoort, P., Nazir, T., & Singer, W. (2009). What are the brain mechanisms underlying syntactic operations? In D. Bickerton, & E. Szathmáry (Eds.), Biological foundations and origin of syntax (pp. 299-324). Cambridge, MA: MIT Press.

    Abstract

    This chapter summarizes the extensive discussions that took place during the Forum as well as the subsequent months thereafter. It assesses current understanding of the neuronal mechanisms that underlie syntactic structure and processing.... It is posited that to understand the neurobiology of syntax, it might be worthwhile to shift the balance from comprehension to syntactic encoding in language production
  • Goldin-Meadow, S., Ozyurek, A., Sancar, B., & Mylander, C. (2009). Making language around the globe: A cross-linguistic study of homesign in the United States, China, and Turkey. In J. Guo, E. Lieven, N. Budwig, S. Ervin-Tripp, K. Nakamura, & S. Ozcaliskan (Eds.), Crosslinguistic approaches to the psychology of language: Research in the tradition of Dan Isaac Slobin (pp. 27-39). New York: Psychology Press.
  • Hagoort, P. (2009). The fractionation of spoken language understanding by measuring electrical and magnetic brain signals. In B. C. J. Moore, L. K. Tyler, & W. Marslen-Wilson (Eds.), The perception of speech: From sound to meaning (pp. 223-248). New York: Oxford University Press.
  • Hagoort, P. (2009). Reflections on the neurobiology of syntax. In D. Bickerton, & E. Szathmáry (Eds.), Biological foundations and origin of syntax (pp. 279-296). Cambridge, MA: MIT Press.

    Abstract

    This contribution focuses on the neural infrastructure for parsing and syntactic encoding. From an anatomical point of view, it is argued that Broca's area is an ill-conceived notion. Functionally, Broca's area and adjacent cortex (together Broca's complex) are relevant for language, but not exclusively for this domain of cognition. Its role can be characterized as providing the necessary infrastructure for unification (syntactic and semantic). A general proposal, but with required level of computational detail, is discussed to account for the distribution of labor between different components of the language network in the brain.Arguments are provided for the immediacy principle, which denies a privileged status for syntax in sentence processing. The temporal profile of event-related brain potential (ERP) is suggested to require predictive processing. Finally, since, next to speed, diversity is a hallmark of human languages, the language readiness of the brain might not depend on a universal, dedicated neural machinery for syntax, but rather on a shaping of the neural infrastructure of more general cognitive systems (e.g., memory, unification) in a direction that made it optimally suited for the purpose of communication through language.
  • Hagoort, P., Baggio, G., & Willems, R. M. (2009). Semantic unification. In M. S. Gazzaniga (Ed.), The cognitive neurosciences, 4th ed. (pp. 819-836). Cambridge, MA: MIT Press.

    Abstract

    Language and communication are about the exchange of meaning. A key feature of understanding and producing language is the construction of complex meaning from more elementary semantic building blocks. The functional characteristics of this semantic unification process are revealed by studies using event related brain potentials. These studies have found that word meaning is assembled into compound meaning in not more than 500 ms. World knowledge, information about the speaker, co-occurring visual input and discourse all have an immediate impact on semantic unification, and trigger similar electrophysiological responses as sentence-internal semantic information. Neuroimaging studies show that a network of brain areas, including the left inferior frontal gyrus, the left superior/middle temporal cortex, the left inferior parietal cortex and, to a lesser extent their right hemisphere homologues are recruited to perform semantic unification.
  • Hagoort, P. (2009). Taalontwikkeling: Meer dan woorden alleen. In M. Evenblij (Ed.), Brein in beeld: Beeldvorming bij heersenonderzoek (pp. 53-57). Den Haag: Stichting Bio-Wetenschappen en Maatschappij.
  • Petersson, K. M., Ingvar, M., & Reis, A. (2009). Language and literacy from a cognitive neuroscience perspective. In D. Olsen, & N. Torrance (Eds.), Cambridge handbook of literacy (pp. 152-181). Cambridge: Cambridge University Press.
  • Van Berkum, J. J. A. (2009). The neuropragmatics of 'simple' utterance comprehension: An ERP review. In U. Sauerland, & K. Yatsushiro (Eds.), Semantics and pragmatics: From experiment to theory (pp. 276-316). Basingstoke: Palgrave Macmillan.

    Abstract

    In this chapter, I review my EEG research on comprehending sentences in context from a pragmatics-oriented perspective. The review is organized around four questions: (1) When and how do extra-sentential factors such as the prior text, identity of the speaker, or value system of the comprehender affect the incremental sentence interpretation processes indexed by the so-called N400 component of the ERP? (2) When and how do people identify the referents for expressions such as “he” or “the review”, and how do referential processes interact with sense and syntax? (3) How directly pragmatic are the interpretation-relevant ERP effects reported here? (4) Do readers and listeners anticipate upcoming information? One important claim developed in the chapter is that the well-known N400 component, although often associated with ‘semantic integration’, only indirectly reflects the sense-making involved in structure-sensitive dynamic composition of the type studied in semantics and pragmatics. According to the multiple-cause intensified retrieval (MIR) account -- essentially an extension of the memory retrieval account proposed by Kutas and colleagues -- the amplitude of the word-elicited N400 reflects the computational resources used in retrieving the relatively invariant coded meaning stored in semantic long-term memory for, and made available by, the word at hand. Such retrieval becomes more resource-intensive when the coded meanings cued by this word do not match with expectations raised by the relevant interpretive context, but also when certain other relevance signals, such as strong affective connotation or a marked delivery, indicate the need for deeper processing. The most important consequence of this account is that pragmatic modulations of the N400 come about not because the N400 at hand directly reflects a rich compositional-semantic and/or Gricean analysis to make sense of the word’s coded meaning in this particular context, but simply because the semantic and pragmatic implications of the preceding words have already been computed, and now define a less or more helpful interpretive background within which to retrieve coded meaning for the critical word.

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