“…Within the language domain, experiments have shown for example that objects that are likely to become relevant in the future are fixated upon earlier when the provided linguistic context (together with the visual environment) makes it possible to predict them (Kamide, Altmann, & Haywood, 2003) and words that can be anticipated are fixated shorter and skipped more often during natural reading (Ehrlich & Rayner, 1981; Rayner, Slattery, Drieghe, & Liversedge, 2011; Rayner & Well, 1996). Furthermore, predictable words are processed quicker (Traxler & Foss, 2000) and reanalysis is sped up in predictive contexts (Loerts, Stowe, & Schmid, 2013). Hence, words that are predictable appear to be processed more easily.…”
Do people predict specific word-forms during language comprehension? In an Event-Related Potential (ERP) study participants read German sentences with predictable (The goalkeeper claims that the slick ball was easy to CATCH.) and unpredictable (The kids boasted that the young horse was easy to SADDLE.) verbs. Verbs were either consistent with the expected word-form (catch/saddle) or inconsistent and therefore led to ungrammaticality (*catches/*saddles). ERPs within the N400 time-window were modulated by predictability but not by the surface-form of the verbs, suggesting that no exact word-forms were predicted. Based on our results we will argue that predictions included semantic rather than form-information. Furthermore, ungrammatical verbs led to a strong P600, probably due to task-saliency whereas correct unpredictable verbs elicited an anterior post-N400 positivity. Because the contexts were moderately constraining, this might reflect discourse revision processes rather than inhibition of a predicted word.
“…Within the language domain, experiments have shown for example that objects that are likely to become relevant in the future are fixated upon earlier when the provided linguistic context (together with the visual environment) makes it possible to predict them (Kamide, Altmann, & Haywood, 2003) and words that can be anticipated are fixated shorter and skipped more often during natural reading (Ehrlich & Rayner, 1981; Rayner, Slattery, Drieghe, & Liversedge, 2011; Rayner & Well, 1996). Furthermore, predictable words are processed quicker (Traxler & Foss, 2000) and reanalysis is sped up in predictive contexts (Loerts, Stowe, & Schmid, 2013). Hence, words that are predictable appear to be processed more easily.…”
Do people predict specific word-forms during language comprehension? In an Event-Related Potential (ERP) study participants read German sentences with predictable (The goalkeeper claims that the slick ball was easy to CATCH.) and unpredictable (The kids boasted that the young horse was easy to SADDLE.) verbs. Verbs were either consistent with the expected word-form (catch/saddle) or inconsistent and therefore led to ungrammaticality (*catches/*saddles). ERPs within the N400 time-window were modulated by predictability but not by the surface-form of the verbs, suggesting that no exact word-forms were predicted. Based on our results we will argue that predictions included semantic rather than form-information. Furthermore, ungrammatical verbs led to a strong P600, probably due to task-saliency whereas correct unpredictable verbs elicited an anterior post-N400 positivity. Because the contexts were moderately constraining, this might reflect discourse revision processes rather than inhibition of a predicted word.
“…Although most filter cutoffs are at or below 0.1 Hz, numerous reported studies from prominent labs in high profile journals use filter settings ranging from .25 Hz to .5 Hz, with some reports using cutoffs as high as 1 or 2 Hz, with no clear justification provided for these relatively high cutoff values. One possible justification is that higher cutoffs might more effectively remove skin potentials and therefore increase statistical power (Kappenman & Luck, ; see Loerts, Stowe, & Schmid, , for an example of this sort of justification). However, it is necessary to balance the improvement in statistical power with the possibility of introducing artifactual effects.…”
Although it is widely known that high-pass filters can reduce the amplitude of slow ERP components, these filters can also introduce artifactual peaks that lead to incorrect conclusions. To demonstrate this and provide evidence about optimal filter settings, we recorded ERPs in a typical language processing paradigm involving syntactic and semantic violations. Unfiltered results showed standard N400 and P600 effects in the semantic and syntactic violation conditions, respectively. However, high-pass filters with cutoffs at 0.3 Hz and above produced artifactual effects of opposite polarity before the true effect. That is, excessive high-pass filtering introduced a significant N400 effect preceding the P600 in the syntactic condition, and a significant P2 effect preceding the N400 in the semantic condition. Thus, inappropriate use of high-pass filters can lead to false conclusions about which components are influenced by a given manipulation. The present results also lead to practical recommendations for high-pass filter settings that maximize statistical power while minimizing filtering artifacts.
“…Presentation of the sentence stems was auditory (cf. Drake & Corley, 2014;Loerts, Stowe, & Schmidt, 2013); following each stem (e.g., when we want water we just turn on the . .…”
It has been suggested that the activation of speechmotor areas during speech comprehension may, in part, reflect the involvement of the speech production system in synthesizing upcoming material at an articulatorily specified level. In this study, we explored that suggestion through the use of articulatory imaging. We investigated whether, and how, predictions that emerge during speech comprehension influence articulatory realizations during picture naming. We elicited predictions by auditorily presenting high-cloze sentence stems to participants (e.g., When we want water we just turn on the . . .). Participants named a picture immediately following each sentence-stem presentation. The pictures either matched (e.g., TAP) or mismatched (e.g., CAP) the high-cloze sentence-stem target. Throughout each trial, participants' speech-motor movements were recorded via dynamic ultrasound imaging. This allowed us to compare articulations in the match and mismatch conditions to each other and to a control condition (simple picture naming). Articulations in the mismatch condition differed more from the control condition than did those in the match condition. This difference was reflected in a second analysis that showed greater frame-by-frame change in articulator positions for the mismatch than for the match condition around 300-500 ms before the onset of the picture name. Our findings indicate that comprehension-elicited prediction influences speech-motor production, suggesting that the speech production system is implicated in the representation of such predictions.
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