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Lev-Ari, S. (in press). The influence of social network properties on language processing and use. In M. S. Vitevitch (
Ed.), Network Science in Cognitive Psychology. New York, NY: Routledge.
McQueen, J. M., & Meyer, A. S. (in press). Towards a comprehensive cognitive architecture for language use. In P. Hagoort (
Ed.), Human language: From genes and brain to behavior. Cambridge, MA: MIT Press.
Brehm, L., & Goldrick, M. (2018). Connectionist principles in theories of speech production. In S.-A. Rueschemeyer, & M. G. Gaskell (
Eds.), The Oxford Handbook of Psycholinguistics (2nd ed., pp. 372-397). Oxford: Oxford University Press.
AbstractThis chapter focuses on connectionist modeling in language production, highlighting how core principles of connectionism provide coverage for empirical observations about representation and selection at the phonological, lexical, and sentence levels. The first section focuses on the connectionist principles of localist representations and spreading activation. It discusses how these two principles have motivated classic models of speech production and shows how they cover results of the picture-word interference paradigm, the mixed error effect, and aphasic naming errors. The second section focuses on how newer connectionist models incorporate the principles of learning and distributed representations through discussion of syntactic priming, cumulative semantic interference, sequencing errors, phonological blends, and code-switching
Mani, N., Mishra, R. K., & Huettig, F. (2018). Introduction to 'The Interactive Mind: Language, Vision and Attention'. In N. Mani, R. K. Mishra, & F. Huettig (
Eds.), The Interactive Mind: Language, Vision and Attention (pp. 1-2). Chennai: Macmillan Publishers India.
Mitterer, H., Brouwer, S., & Huettig, F. (2018). How important is prediction for understanding spontaneous speech? In N. Mani, R. K. Mishra, & F. Huettig (
Eds.), The Interactive Mind: Language, Vision and Attention (pp. 26-40). Chennai: Macmillan Publishers India.
Shao, Z., & Meyer, A. S. (2018). Word priming and interference paradigms. In A. M. B. De Groot, & P. Hagoort (
Eds.), Research methods in psycholinguistics and the neurobiology of language: A practical guide (pp. 111-129). Hoboken: Wiley.
Gordon, P. C., Lowder, M. W., & Hoedemaker, R. S. (2016). Reading in normally aging adults. In H. Wright (
Ed.), Cognitive-Linguistic Processes and Aging (pp. 165-192). Amsterdam: Benjamins. doi:10.1075/z.200.07gor.
AbstractThe activity of reading raises fundamental theoretical and practical questions about healthy cognitive aging. Reading relies greatly on knowledge of patterns of language and of meaning at the level of words and topics of text. Further, this knowledge must be rapidly accessed so that it can be coordinated with processes of perception, attention, memory and motor control that sustain skilled reading at rates of four-to-five words a second. As such, reading depends both on crystallized semantic intelligence which grows or is maintained through healthy aging, and on components of fluid intelligence which decline with age. Reading is important to older adults because it facilitates completion of everyday tasks that are essential to independent living. In addition, it entails the kind of active mental engagement that can preserve and deepen the cognitive reserve that may mitigate the negative consequences of age-related changes in the brain. This chapter reviews research on the front end of reading (word recognition) and on the back end of reading (text memory) because both of these abilities are surprisingly robust to declines associated with cognitive aging. For word recognition, that robustness is surprising because rapid processing of the sort found in reading is usually impaired by aging; for text memory, it is surprising because other types of episodic memory performance (e.g., paired associates) substantially decline in aging. These two otherwise quite different levels of reading comprehension remain robust because they draw on the knowledge of language that older adults gain through a life-time of experience with language.
Smith, A. C., Monaghan, P., & Huettig, F. (2016). Complex word recognition behaviour emerges from the richness of the word learning environment. In K. Twomey, A. C. Smith, G. Westermann, & P. Monaghan (
Eds.), Neurocomputational Models of Cognitive Development and Processing: Proceedings of the 14th Neural Computation and Psychology Workshop (pp. 99-114). Singapore: World Scientific. doi:10.1142/9789814699341_0007.
AbstractComputational models can reflect the complexity of human behaviour by implementing multiple constraints within their architecture, and/or by taking into account the variety and richness of the environment to which the human is responding. We explore the second alternative in a model of word recognition that learns to map spoken words to visual and semantic representations of the words’ concepts. Critically, we employ a phonological representation utilising coarse-coding of the auditory stream, to mimic early stages of language development that are not dependent on individual phonemes to be isolated in the input, which may be a consequence of literacy development. The model was tested at different stages during training, and was able to simulate key behavioural features of word recognition in children: a developing effect of semantic information as a consequence of language learning, and a small but earlier effect of phonological information on word processing. We additionally tested the role of visual information in word processing, generating predictions for behavioural studies, showing that visual information could have a larger effect than semantics on children’s performance, but that again this affects recognition later in word processing than phonological information. The model also provides further predictions for performance of a mature word recognition system in the absence of fine-coding of phonology, such as in adults who have low literacy skills. The model demonstrated that such phonological effects may be reduced but are still evident even when multiple distractors from various modalities are present in the listener’s environment. The model demonstrates that complexity in word recognition can emerge from a simple associative system responding to the interactions between multiple sources of information in the language learner’s environment.
Chen, A. (2015). Children’s use of intonation in reference and the role of input. In L. Serratrice, & S. E. M. Allen (
Eds.), The acquisition of reference (pp. 83-104). Amsterdam: Benjamins.
AbstractStudies on children’s use of intonation in reference are few in number but are diverse in terms of theoretical frameworks and intonational parameters. In the current review, I present a re-analysis of the referents in each study, using a three-dimension approach (i.e. referential givenness-newness, relational givenness-newness, contrast), discuss the use of intonation at two levels (phonetic, phonological), and compare findings from different studies within a single framework. The patterns stemming from these studies may be limited in generalisability but can serve as initial hypotheses for future work. Furthermore, I examine the role of input as available in infant direct speech in the acquisition of intonational encoding of referents. In addition, I discuss how future research can advance our knowledge.
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Hintz, F., & Huettig, F. (2015). The complexity of the visual environment modulates language-mediated eye gaze. In R. Mishra, N. Srinivasan, & F. Huettig (
Eds.), Attention and Vision in Language Processing (pp. 39-55). Berlin: Springer. doi:10.1007/978-81-322-2443-3_3.
AbstractThree eye-tracking experiments investigated the impact of the complexity of the visual environment on the likelihood of word-object mapping taking place at phonological, semantic and visual levels of representation during language-mediated visual search. Dutch participants heard spoken target words while looking at four objects embedded in displays of different complexity and indicated the presence or absence of the target object. During filler trials the target objects were present, but during experimental trials they were absent and the display contained various competitor objects. For example, given the target word “beaker”, the display contained a phonological (a beaver, bever), a shape (a bobbin, klos), a semantic (a fork, vork) competitor, and an unrelated distractor (an umbrella, paraplu). When objects were presented in simple four-object displays (Experiment 2), there were clear attentional biases to all three types of competitors replicating earlier research (Huettig and McQueen, 2007). When the objects were embedded in complex scenes including four human-like characters or four meaningless visual shapes (Experiments 1, 3), there were biases in looks to visual and semantic but not to phonological competitors. In both experiments, however, we observed evidence for inhibition in looks to phonological competitors, which suggests that the phonological forms of the objects nevertheless had been retrieved. These findings suggest that phonological word-object mapping is contingent upon the nature of the visual environment and add to a growing body of evidence that the nature of our visual surroundings induces particular modes of processing during language-mediated visual search.
Huettig, F., Srinivasan, N., & Mishra, R. (2015). Introduction to 'Attention and vision in language processing'. In R. Mishra, N. Srinivasan, & F. Huettig (
Eds.), Attention and vision in language processing. (pp. V-IX). Berlin: Springer.
Huettig, F. (2015). Literacy influences cognitive abilities far beyond the mastery of written language. In I. van de Craats, J. Kurvers, & R. van Hout (
Eds.), Adult literacy, second language, and cognition. LESLLA Proceedings 2014. Nijmegen: Centre for Language Studies.
AbstractRecent experimental evidence from cognitive psychology and cognitive neuroscience shows that reading acquisition has non-trivial consequences for cognitive processes other than reading per se. In the present chapter I present evidence from three areas of cognition: phonological processing, prediction in language processing, and visual search. These findings suggest that literacy on cognition influences are far-reaching. This implies that a good understanding of the dramatic impact of literacy acquisition on the human mind is an important prerequisite for successful education policy development and guidance of educational support.
Lev-Ari, S. (2015). Adjusting the manner of language processing to the social context: Attention allocation during interactions with non-native speakers. In R. K. Mishra, N. Srinivasan, & F. Huettig (
Eds.), Attention and Vision in Language Processing (pp. 185-195). New York: Springer. doi:10.1007/978-81-322-2443-3_11.
Norcliffe, E., & Konopka, A. E. (2015). Vision and language in cross-linguistic research on sentence production. In R. K. Mishra, N. Srinivasan, & F. Huettig (
Eds.), Attention and vision in language processing (pp. 77-96). New York: Springer. doi:10.1007/978-81-322-2443-3_5.
AbstractTo what extent are the planning processes involved in producing sentences fine-tuned to grammatical properties of specific languages? In this chapter we survey the small body of cross-linguistic research that bears on this question, focusing in particular on recent evidence from eye-tracking studies. Because eye-tracking methods provide a very fine-grained temporal measure of how conceptual and linguistic planning unfold in real time, they serve as an important complement to standard psycholinguistic methods. Moreover, the advent of portable eye-trackers in recent years has, for the first time, allowed eye-tracking techniques to be used with language populations that are located far away from university laboratories. This has created the exciting opportunity to extend the typological base of vision-based psycholinguistic research and address key questions in language production with new language comparisons.
Huettig, F. (2014). Role of prediction in language learning. In P. J. Brooks, & V. Kempe (
Eds.), Encyclopedia of language development (pp. 479-481). London: Sage Publications.
Konopka, A. E., & Brown-Schmidt, S. (2014). Message encoding. In V. Ferreira, M. Goldrick, & M. Miozzo (
Eds.), The Oxford handbook of language production (pp. 3-20). New York: Oxford University Press.
Smith, A. C., Monaghan, P., & Huettig, F. (2014). Modelling language – vision interactions in the hub and spoke framework. In J. Mayor, & P. Gomez (
Eds.), Computational Models of Cognitive Processes: Proceedings of the 13th Neural Computation and Psychology Workshop (NCPW13). (pp. 3-16). Singapore: World Scientific Publishing.
AbstractMultimodal integration is a central characteristic of human cognition. However our understanding of the interaction between modalities and its influence on behaviour is still in its infancy. This paper examines the value of the Hub & Spoke framework (Plaut, 2002; Rogers et al., 2004; Dilkina et al., 2008; 2010) as a tool for exploring multimodal interaction in cognition. We present a Hub and Spoke model of language–vision information interaction and report the model’s ability to replicate a range of phonological, visual and semantic similarity word-level effects reported in the Visual World Paradigm (Cooper, 1974; Tanenhaus et al, 1995). The model provides an explicit connection between the percepts of language and the distribution of eye gaze and demonstrates the scope of the Hub-and-Spoke architectural framework by modelling new aspects of multimodal cognition.
Clifton, C. J., Meyer, A. S., Wurm, L. H., & Treiman, R. (2013). Language comprehension and production. In A. F. Healy, & R. W. Proctor (
Eds.), Handbook of Psychology, Volume 4, Experimental Psychology. 2nd Edition (pp. 523-547). Hoboken, NJ: Wiley.
AbstractIn this chapter, we survey the processes of recognizing and producing words and of understanding and creating sentences. Theory and research on these topics have been shaped by debates about how various sources of information are integrated in these processes, and about the role of language structure, as analyzed in the discipline of linguistics. In this chapter, we describe current views of fluent language users' comprehension of spoken and written language and their production of spoken language. We review what we consider to be the most important findings and theories in psycholinguistics, returning again and again to the questions of modularity and the importance of linguistic knowledge. Although we acknowledge the importance of social factors in language use, our focus is on core processes such as parsing and word retrieval that are not necessarily affected by such factors. We do not have space to say much about the important fields of developmental psycholinguistics, which deals with the acquisition of language by children, or applied psycholinguistics, which encompasses such topics as language disorders and language teaching. Although we recognize that there is burgeoning interest in the measurement of brain activity during language processing and how language is represented in the brain, space permits only occasional pointers to work in neuropsychology and the cognitive neuroscience of language. For treatment of these topics, and others, the interested reader could begin with two recent handbooks of psycholinguistics (Gaskell, 2007; Traxler & Gemsbacher, 2006) and a handbook of cognitive neuroscience (Gazzaniga, 2004).
Huettig, F. (2013). Young children’s use of color information during language-vision mapping. In B. R. Kar (
Ed.), Cognition and brain development: Converging evidence from various methodologies (pp. 368-391). Washington, DC: American Psychological Association Press.
Mishra, R. K., Olivers, C. N. L., & Huettig, F. (2013). Spoken language and the decision to move the eyes: To what extent are language-mediated eye movements automatic? In V. S. C. Pammi, & N. Srinivasan (
Eds.), Progress in Brain Research: Decision making: Neural and behavioural approaches (pp. 135-149). New York: Elsevier.
AbstractRecent eye-tracking research has revealed that spoken language can guide eye gaze very rapidly (and closely time-locked to the unfolding speech) toward referents in the visual world. We discuss whether, and to what extent, such language-mediated eye movements are automatic rather than subject to conscious and controlled decision-making. We consider whether language-mediated eye movements adhere to four main criteria of automatic behavior, namely, whether they are fast and efficient, unintentional, unconscious, and overlearned (i.e., arrived at through extensive practice). Current evidence indicates that language-driven oculomotor behavior is fast but not necessarily always efficient. It seems largely unintentional though there is also some evidence that participants can actively use the information in working memory to avoid distraction in search. Language-mediated eye movements appear to be for the most part unconscious and have all the hallmarks of an overlearned behavior. These data are suggestive of automatic mechanisms linking language to potentially referred-to visual objects, but more comprehensive and rigorous testing of this hypothesis is needed.