Publications

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  • Zheng, X., Roelofs, A., & Lemhöfer, K. (2018). Language selection errors in switching: language priming or cognitive control? Language, Cognition and Neuroscience, 33(2), 139-147. doi:10.1080/23273798.2017.1363401.

    Abstract

    Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. We examined the relative contribution of top-down cognitive control and bottom-up language priming to these errors. Unbalanced Dutch-English bilinguals named pictures and were cued to switch between languages under time pressure. We also manipulated the number of same-language trials before a switch (long vs. short runs). Results show that speakers made more language selection errors when switching from their second language (L2) to the first language (L1) than vice versa. Furthermore, they made more errors when switching to the L1 after a short compared to a long run of L2 trials. In the reverse switching direction (L1 to L2), run length had no effect. These findings are most compatible with an account of language selection errors that assigns a strong role to top-down processes of cognitive control.

    Additional information

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  • Zoefel, B., Ten Oever, S., & Sack, A. T. (2018). The involvement of endogenous neural oscillations in the processing of rhythmic input: More than a regular repetition of evoked neural responses. Frontiers in Neuroscience, 12: 95. doi:10.3389/fnins.2018.00095.

    Abstract

    It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature.
  • Zora, H., Rudner, M., & Montell Magnusson, A. (2020). Concurrent affective and linguistic prosody with the same emotional valence elicits a late positive ERP response. European Journal of Neuroscience, 51(11), 2236-2249. doi:10.1111/ejn.14658.

    Abstract

    Change in linguistic prosody generates a mismatch negativity response (MMN), indicating neural representation of linguistic prosody, while change in affective prosody generates a positive response (P3a), reflecting its motivational salience. However, the neural response to concurrent affective and linguistic prosody is unknown. The present paper investigates the integration of these two prosodic features in the brain by examining the neural response to separate and concurrent processing by electroencephalography (EEG). A spoken pair of Swedish words—[ˈfɑ́ːsɛn] phase and [ˈfɑ̀ːsɛn] damn—that differed in emotional semantics due to linguistic prosody was presented to 16 subjects in an angry and neutral affective prosody using a passive auditory oddball paradigm. Acoustically matched pseudowords—[ˈvɑ́ːsɛm] and [ˈvɑ̀ːsɛm]—were used as controls. Following the constructionist concept of emotions, accentuating the conceptualization of emotions based on language, it was hypothesized that concurrent affective and linguistic prosody with the same valence—angry [ˈfɑ̀ːsɛn] damn—would elicit a unique late EEG signature, reflecting the temporal integration of affective voice with emotional semantics of prosodic origin. In accordance, linguistic prosody elicited an MMN at 300–350 ms, and affective prosody evoked a P3a at 350–400 ms, irrespective of semantics. Beyond these responses, concurrent affective and linguistic prosody evoked a late positive component (LPC) at 820–870 ms in frontal areas, indicating the conceptualization of affective prosody based on linguistic prosody. This study provides evidence that the brain does not only distinguish between these two functions of prosody but also integrates them based on language and experience.
  • Zora, H., Schwarz, I.-C., & Heldner, M. (2015). Neural correlates of lexical stress: Mismatch negativity reflects fundamental frequency and intensity. NeuroReport, 26(13), 791-796. doi:10.1097/WNR.0000000000000426.

    Abstract

    Neural correlates of lexical stress were studied using the mismatch negativity (MMN) component in event-related potentials. The MMN responses were expected to reveal the encoding of stress information into long-term memory and the contributions of prosodic features such as fundamental frequency (F0) and intensity toward lexical access. In a passive oddball paradigm, neural responses to changes in F0, intensity, and in both features together were recorded for words and pseudowords. The findings showed significant differences not only between words and pseudowords but also between prosodic features. Early processing of prosodic information in words was indexed by an intensity-related MMN and an F0-related P200. These effects were stable at right-anterior and mid-anterior regions. At a later latency, MMN responses were recorded for both words and pseudowords at the mid-anterior and posterior regions. The P200 effect observed for F0 at the early latency for words developed into an MMN response. Intensity elicited smaller MMN for pseudowords than for words. Moreover, a larger brain area was recruited for the processing of words than for the processing of pseudowords. These findings suggest earlier and higher sensitivity to prosodic changes in words than in pseudowords, reflecting a language-related process. The present study, therefore, not only establishes neural correlates of lexical stress but also confirms the presence of long-term memory traces for prosodic information in the brain.
  • De Zubicaray, G. I., Acheson, D. J., & Hartsuiker, R. J. (Eds.). (2013). Mind what you say - general and specific mechanisms for monitoring in speech production [Research topic] [Special Issue]. Frontiers in Human Neuroscience. Retrieved from http://www.frontiersin.org/human_neuroscience/researchtopics/mind_what_you_say_-_general_an/1197.

    Abstract

    Psycholinguistic research has typically portrayed speech production as a relatively automatic process. This is because when errors are made, they occur as seldom as one in every thousand words we utter. However, it has long been recognised that we need some form of control over what we are currently saying and what we plan to say. This capacity to both monitor our inner speech and self-correct our speech output has often been assumed to be a property of the language comprehension system. More recently, it has been demonstrated that speech production benefits from interfacing with more general cognitive processes such as selective attention, short-term memory (STM) and online response monitoring to resolve potential conflict and successfully produce the output of a verbal plan. The conditions and levels of representation according to which these more general planning, monitoring and control processes are engaged during speech production remain poorly understood. Moreover, there remains a paucity of information about their neural substrates, despite some of the first evidence of more general monitoring having come from electrophysiological studies of error related negativities (ERNs). While aphasic speech errors continue to be a rich source of information, there has been comparatively little research focus on instances of speech repair. The purpose of this Frontiers Research Topic is to provide a forum for researchers to contribute investigations employing behavioural, neuropsychological, electrophysiological, neuroimaging and virtual lesioning techniques. In addition, while the focus of the research topic is on novel findings, we welcome submission of computational simulations, review articles and methods papers.
  • Zuidema, W., French, R. M., Alhama, R. G., Ellis, K., O'Donnell, T. J. O., Sainburgh, T., & Gentner, T. Q. (2020). Five ways in which computational modeling can help advance cognitive science: Lessons from artificial grammar learning. Topics in Cognitive Science, 12(3), 925-941. doi:10.1111/tops.12474.

    Abstract

    There is a rich tradition of building computational models in cognitive science, but modeling, theoretical, and experimental research are not as tightly integrated as they could be. In this paper, we show that computational techniques—even simple ones that are straightforward to use—can greatly facilitate designing, implementing, and analyzing experiments, and generally help lift research to a new level. We focus on the domain of artificial grammar learning, and we give five concrete examples in this domain for (a) formalizing and clarifying theories, (b) generating stimuli, (c) visualization, (d) model selection, and (e) exploring the hypothesis space.
  • Zwitserlood, I. (2011). Gebruiksgemak van het eerste Nederlandse Gebarentaal woordenboek kan beter [Book review]. Levende Talen Magazine, 4, 46-47.

    Abstract

    Review: User friendliness of the first dictionary of Sign Language of the Netherlands can be improved
  • Zwitserlood, I. (2011). Gevraagd: medewerkers verzorgingshuis met een goede oog-handcoördinatie. Het meten van NGT-vaardigheid. Levende Talen Magazine, 1, 44-46.

    Abstract

    (Needed: staff for residential care home with good eye-hand coordination. Measuring NGT-skills.)
  • Zwitserlood, I. (2011). Het Corpus NGT en de dagelijkse lespraktijk. Levende Talen Magazine, 6, 46.

    Abstract

    (The Corpus NGT and the daily practice of language teaching)
  • Zwitserlood, I. (2011). Het Corpus NGT en de opleiding leraar/tolk NGT. Levende Talen Magazine, 1, 40-41.

    Abstract

    (The Corpus NGT and teacher NGT/interpreter NGT training)

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