18 research outputs found

    The Interplay between Prosody and Syntax in Sentence Processing: The case of subject-control versus object-control verbs

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    Contains fulltext : 90630.pdf (publisher's version ) (Open Access)This study addresses the question whether prosodic information can affect the choice for a syntactic analysis in auditory sentence processing. We manipulated the prosody (in the form of a prosodic break; PB) of locally ambiguous Dutch sentences to favor one of two interpretations. The experimental items contained two different types of so-called control verbs (subject and object control) in the matrix clause and were syntactically disambiguated by a transitive or by an intransitive verb. In Experiment 1, we established the default off-line preference of the items for a transitive or an intransitive disambiguating verb with a visual and an auditory fragment completion test. The results suggested that subject- and object-control verbs differently affect the syntactic structure that listeners expect. In Experiment 2, we investigated these two types of verbs separately in an on-line ERP study. Consistent with the literature, the PB elicited a closure positive shift. Furthermore, in subject-control items, an N400 effect for intransitive relative to transitive disambiguating verbs was found, both for sentences with and for sentences without a PB. This result suggests that the default preference for subject-control verbs goes in the same direction as the effect of the PB. In object-control items, an N400 effect for intransitive relative to transitive disambiguating verbs was found for sentences with a PB but no effect in the absence of a PB. This indicates that a PB can affect the syntactic analysis that listeners pursue

    Contributions of emotional state and attention to the processing of syntactic agreement errors: Evidence from P600

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    © 2015 Verhees, Chwilla, Tromp and Vissers. The classic account of language is that language processing occurs in isolation from other cognitive systems, like perception, motor action and emotion. The central theme of this paper is the relationship between a participant's emotional state and language comprehension. Does emotional context affect how we process neutral words? Recent studies showed that processing of word meaning - traditionally conceived as an automatic process - is affected by emotional state. The influence of emotional state on syntactic processing is less clear. One study reported a mood-related P600 modulation, while another study did not observe an effect of mood on syntactic processing. The goals of this study were: First, to clarify whether and if so how mood affects syntactic processing. Second, to shed light on the underlying mechanisms by separating possible effects of mood from those of attention on syntactic processing. ERPs were recorded while participants read syntactically correct or incorrect sentences. Mood (happy vs. sad) was manipulated by presenting film clips. Attention was manipulated by directing attention to syntactic features vs. physical features. The mood induction was effective. Interactions between mood, attention and syntactic correctness were obtained, showing that mood and attention modulated P600. The mood manipulation led to a reduction in P600 for sad as compared to happy mood when attention was directed at syntactic features. The attention manipulation led to a reduction in P600 when attention was directed at physical features compared to syntactic features for happy mood. From this we draw two conclusions: First, emotional state does affect syntactic processing. We propose mood-related differences in the reliance on heuristics as the underlying mechanism. Second, attention can contribute to emotion-related ERP effects in syntactic language processing. Therefore, future studies on the relation between language and emotion will have to control for effects of attention.status: publishe

    Early utterance time-window.

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    <p>A) Grand-averaged ERPs time-locked to the onset of the first word. Representative electrodes showing the relevant effects are highlighted in dashed boxes. B) Scalp distribution of the ERP effects in the early utterance time-window. All waveforms were low-pass filtered (10 Hz) for illustration purposes only. Negativity is plotted upwards.</p

    Timeline.

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    <p>Mean onset of the first word, verb and final word in target utterances and a rough timeline for the early and late utterance time-windows.</p

    Behavioural results.

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    <p>Mean accuracy (and standard deviation) in the categorization task for all items (overall) and for each stimulus Set.</p><p>Behavioural results.</p

    Regions used for analyses of EEG data.

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    <p>Regions used for analyses of EEG data.</p

    Late utterance time-window.

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    <p>A) Grand-averaged ERPs time-locked to the onset of the final word. Representative electrodes showing the relevant effects are highlighted in dashed boxes. B) Scalp distribution of the ERP effects in the late utterance time-window.</p
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