Publications

Displaying 1 - 52 of 52
  • Yu, X. (2021). Foreign language learning in study-abroad and at-home contexts. PhD Thesis, Raboud University Nijmegen, Nijmegen.
  • Armeni, K. (2021). On model-based neurobiology of language comprehension: Neural oscillations, processing memory, and prediction. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Bentum, M. (2021). Listening with great expectations: A study of predictive natural speech processing. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Bergmann, C. (2014). Computational models of early language acquisition and the role of different voices. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Bosker, H. R. (2014). The processing and evaluation of fluency in native and non-native speech. PhD Thesis, Utrecht University, Utrecht.

    Abstract

    Disfluency is a common characteristic of spontaneously produced speech. Disfluencies (e.g., silent pauses, filled pauses [uh’s and uhm’s], corrections, repetitions, etc.) occur in both native and non-native speech. There appears to be an apparent contradiction between claims from the evaluative and cognitive approach to fluency. On the one hand, the evaluative approach shows that non-native disfluencies have a negative effect on listeners’ subjective fluency impressions. On the other hand, the cognitive approach reports beneficial effects of native disfluencies on cognitive processes involved in speech comprehension, such as prediction and attention.

    This dissertation aims to resolve this apparent contradiction by combining the evaluative and cognitive approach. The reported studies target both the evaluation (Chapters 2 and 3) and the processing of fluency (Chapters 4 and 5) in native and non-native speech. Thus, it provides an integrative account of native and non-native fluency perception, informative to both language testing practice and cognitive psycholinguists. The proposed account of fluency perception testifies to the notion that speech performance matters: communication through spoken language does not only depend on what is said, but also on how it is said and by whom.
  • Brehm, L. (2014). Speed limits and red flags: Why number agreement accidents happen. PhD Thesis, University of Illinois at Urbana-Champaign, Urbana-Champaign, Il.
  • Buckler, H. (2014). The acquisition of morphophonological alternations across languages. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Choi, J. (2014). Rediscovering a forgotten language. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Cutler, A., Aslin, R. N., Gervain, J., & Nespor, M. (Eds.). (2021). Special issue in honor of Jacques Mehler, Cognition's founding editor [Special Issue]. Cognition, 213.
  • Evans, N., Levinson, S. C., & Sterelny, K. (Eds.). (2021). Thematic issue on evolution of kinship systems [Special Issue]. Biological theory, 16.
  • Eviatar, Z., & Huettig, F. (Eds.). (2021). Literacy and writing systems [Special Issue]. Journal of Cultural Cognitive Science.
  • Felker, E. R. (2021). Learning second language speech perception in natural settings. PhD Thesis, Radboud University, Nijmegen.
  • Forkel, S. J. (2014). Identification of anatomical predictors of language recovery after stroke with diffusion tensor imaging. PhD Thesis, King's College London, London.

    Abstract

    Background Stroke-induced aphasia is associated with adverse effects on quality of life and the ability to return to work. However, the predictors of recovery are still poorly understood. Anatomical variability of the arcuate fasciculus, connecting Broca’s and Wernicke’s areas, has been reported in the healthy population using diffusion tensor imaging tractography. In about 40% of the population the arcuate fasciculus is bilateral and this pattern is advantageous for certain language related functions, such as auditory verbal learning (Catani et al. 2007). Methods In this prospective longitudinal study, anatomical predictors of post-stroke aphasia recovery were investigated using diffusion tractography and arterial spin labelling. Patients An 18-subject strong aphasia cohort with first-ever unilateral left hemispheric middle cerebral artery infarcts underwent post stroke language (mean 5±5 days) and neuroimaging (mean 10±6 days) assessments and neuropsychological follow-up at six months. Ten of these patients were available for reassessment one year after symptom onset. Aphasia was assessed with the Western Aphasia Battery, which provides a global measure of severity (Aphasia Quotient, AQ). Results Better recover from aphasia was observed in patients with a right arcuate fasciculus [beta=.730, t(2.732), p=.020] (tractography) and increased fractional anisotropy in the right hemisphere (p<0.05) (Tract-based spatial statistics). Further, an increase in left hemisphere perfusion was observed after one year (p<0.01) (perfusion). Lesion analysis identified maximal overlay in the periinsular white matter (WM). Lesion-symptom mapping identified damage to periinsular structure as predictive for overall aphasia severity and damage to frontal lobe white matter as predictive of repetition deficits. Conclusion These findings suggest an important role for the right hemisphere language network in recovery from aphasia after left hemispheric stroke.

    Additional information

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  • Frances, C. (2021). Semantic richness, semantic context, and language learning. PhD Thesis, Universidad del País Vasco-Euskal Herriko Unibertsitatea, Donostia.

    Abstract

    As knowing a foreign language becomes a necessity in the modern world, a large portion of
    the population is faced with the challenge of learning a language in a classroom. This, in turn,
    presents a unique set of difficulties. Acquiring a language with limited and artificial exposure makes
    learning new information and vocabulary particularly difficult. The purpose of this thesis is to help us
    understand how we can compensate—at least partially—for these difficulties by presenting
    information in a way that aids learning. In particular, I focused on variables that affect semantic
    richness—meaning the amount and variability of information associated with a word. Some factors
    that affect semantic richness are intrinsic to the word and others pertain to that word’s relationship
    with other items and information. This latter group depends on the context around the to-be-
    learned items rather than the words themselves. These variables are easier to manipulate than
    intrinsic qualities, making them more accessible tools for teaching and understanding learning. I
    focused on two factors: emotionality of the surrounding semantic context and contextual diversity.
    Publication 1 (Frances, de Bruin, et al., 2020b) focused on content learning in a foreign
    language and whether the emotionality—positive or neutral—of the semantic context surrounding
    key information aided its learning. This built on prior research that showed a reduction in
    emotionality in a foreign language. Participants were taught information embedded in either
    positive or neutral semantic contexts in either their native or foreign language. When they were
    then tested on these embedded facts, participants’ performance decreased in the foreign language.
    But, more importantly, they remembered better the information from the positive than the neutral
    semantic contexts.
    In Publication 2 (Frances, de Bruin, et al., 2020a), I focused on how emotionality affected
    vocabulary learning. I taught participants the names of novel items described either in positive or
    neutral terms in either their native or foreign language. Participants were then asked to recall and
    recognize the object's name—when cued with its image. The effects of language varied with the
    difficulty of the task—appearing in recall but not recognition tasks. Most importantly, learning the
    words in a positive context improved learning, particularly of the association between the image of
    the object and its name.
    In Publication 3 (Frances, Martin, et al., 2020), I explored the effects of contextual
    diversity—namely, the number of texts a word appears in—on native and foreign language word
    learning. Participants read several texts that had novel pseudowords. The total number of
    encounters with the novel words was held constant, but they appeared in 1, 2, 4, or 8 texts in either
    their native or foreign language. Increasing contextual diversity—i.e., the number of texts a word
    appeared in—improved recall and recognition, as well as the ability to match the word with its
    meaning. Using a foreign language only affected performance when participants had to quickly
    identify the meaning of the word.
    Overall, I found that the tested contextual factors related to semantic richness—i.e.,
    emotionality of the semantic context and contextual diversity—can be manipulated to improve
    learning in a foreign language. Using positive emotionality not only improved learning in the foreign
    language, but it did so to the same extent as in the native language. On a theoretical level, this
    suggests that the reduction in emotionality in a foreign language is not ubiquitous and might relate
    to the way in which that language as learned.
    The third article shows an experimental manipulation of contextual diversity and how this
    can affect learning of a lexical item, even if the amount of information known about the item is kept
    constant. As in the case of emotionality, the effects of contextual diversity were also the same
    between languages. Although deducing words from context is dependent on vocabulary size, this
    does not seem to hinder the benefits of contextual diversity in the foreign language.
    Finally, as a whole, the articles contained in this compendium provide evidence that some
    aspects of semantic richness can be manipulated contextually to improve learning and memory. In
    addition, the effects of these factors seem to be independent of language status—meaning, native
    or foreign—when learning new content. This suggests that learning in a foreign and a native
    language is not as different as I initially hypothesized, allowing us to take advantage of native
    language learning tools in the foreign language, as well.
  • Frost, R. (2014). Learning grammatical structures with and without sleep. PhD Thesis, Lancaster University, Lancaster.
  • Ganushchak, L. Y., & Acheson, D. J. (Eds.). (2014). What's to be learned from speaking aloud? - Advances in the neurophysiological measurement of overt language production. [Research topic] [Special Issue]. Frontiers in Language Sciences. Retrieved from http://www.frontiersin.org/Language_Sciences/researchtopics/What_s_to_be_Learned_from_Spea/1671.

    Abstract

    Researchers have long avoided neurophysiological experiments of overt speech production due to the suspicion that artifacts caused by muscle activity may lead to a bad signal-to-noise ratio in the measurements. However, the need to actually produce speech may influence earlier processing and qualitatively change speech production processes and what we can infer from neurophysiological measures thereof. Recently, however, overt speech has been successfully investigated using EEG, MEG, and fMRI. The aim of this Research Topic is to draw together recent research on the neurophysiological basis of language production, with the aim of developing and extending theoretical accounts of the language production process. In this Research Topic of Frontiers in Language Sciences, we invite both experimental and review papers, as well as those about the latest methods in acquisition and analysis of overt language production data. All aspects of language production are welcome: i.e., from conceptualization to articulation during native as well as multilingual language production. Focus should be placed on using the neurophysiological data to inform questions about the processing stages of language production. In addition, emphasis should be placed on the extent to which the identified components of the electrophysiological signal (e.g., ERP/ERF, neuronal oscillations, etc.), brain areas or networks are related to language comprehension and other cognitive domains. By bringing together electrophysiological and neuroimaging evidence on language production mechanisms, a more complete picture of the locus of language production processes and their temporal and neurophysiological signatures will emerge.
  • Greenfield, M. D., Honing, H., Kotz, S. A., & Ravignani, A. (Eds.). (2021). Synchrony and rhythm interaction: From the brain to behavioural ecology [Special Issue]. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 376.
  • Huisman, J. L. A. (2021). Variation in form and meaning across the Japonic language family: With a focus on the Ryukyuan languages. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Kaufeld, G. (2021). Investigating spoken language comprehension as perceptual inference. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Klein, W. (Ed.). (1989). Kindersprache [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (73).
  • Klein, W. (Ed.). (1976). Psycholinguistik [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (23/24).
  • Klein, W. (Ed.). (1988). Sprache Kranker [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (69).
  • Klein, W. (Ed.). (1982). Zweitspracherwerb [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (45).
  • Kok, P. (2014). On the role of expectation in visual perception: A top-down view of early visual cortex. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Kösem, A. (2014). Cortical oscillations as temporal reference frames for perception. PhD Thesis, Université Pierre et Marie Curie-Paris VI, Paris.
  • Levshina, N., & Moran, S. (Eds.). (2021). Efficiency in human languages: Corpus evidence for universal principles [Special Issue]. Linguistics Vanguard, 7(s3).
  • Lopopolo, A. (2021). Properties, structures and operations: Studies on language processing in the brain using computational linguistics and naturalistic stimuli. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Manhardt, F. (2021). A tale of two modalities. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Meyer, A. S. (1988). Phonological encoding in language production: A priming study. PhD Thesis, Katholieke Universiteit Nijmegen.
  • Mickan, A. (2021). What was that Spanish word again? Investigations into the cognitive mechanisms underlying foreign language attrition. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Piai, V. (2014). Choosing our words: Lexical competition and the involvement of attention in spoken word production. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Postema, M. (2021). Left-right asymmetry of the human brain: Associations with neurodevelopmental disorders and genetic factors. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Redl, T. (2021). Masculine generic pronouns: Investigating the processing of an unintended gender cue. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Reifegerste, J. (2014). Morphological processing in younger and older people: Evidence for flexible dual-route access. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Rojas-Berscia, L. M. (2014). A Heritage Reference Grammar of Selk’nam. Master Thesis, Radboud University, Nijmegen.
  • Schubotz, L. (2021). Effects of aging and cognitive abilities on multimodal language production and comprehension in context. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Simanova, I. (2014). In search of conceptual representations in the brain: Towards mind-reading. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Snijders Blok, L. (2021). Let the genes speak! De novo variants in developmental disorders with speech and language impairment. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Thorgrimsson, G. (2014). Infants' understanding of communication as participants and observers. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Todorova, L. (2021). Language bias in visually driven decisions: Computational neurophysiological mechanisms. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Trompenaars, T. (2021). Bringing stories to life: Animacy in narrative and processing. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Tsoukala, C. (2021). Bilingual sentence production and code-switching: Neural network simulations. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Tsuji, S. (2014). The road to native listening. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Turco, G. (2014). Contrasting opposite polarity in Germanic and Romance languages: Verum focus and affirmative particles in native speakers and advanced L2 learners. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Van Dijk, C. N. (2021). Cross-linguistic influence during real-time sentence processing in bilingual children and adults. PhD Thesis, Raboud University Nijmegen, Nijmegen.
  • van der Burght, C. L. (2021). The central contribution of prosody to sentence processing: Evidence from behavioural and neuroimaging studies. PhD Thesis, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig.
  • Van Paridon, J. (2021). Speaking while listening: Language processing in speech shadowing and translation. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Van Putten, S. (2014). Information structure in Avatime. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Veenstra, A. (2014). Semantic and syntactic constraints on the production of subject-verb agreement. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Verhoef, E. (2021). Why do we change how we speak? Multivariate genetic analyses of language and related traits across development and disorder. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Verkerk, A. (2014). The evolutionary dynamics of motion event encoding. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Vernes, S. C., Janik, V. M., Fitch, W. T., & Slater, P. J. B. (Eds.). (2021). Vocal learning in animals and humans [Special Issue]. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 376.

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