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Disentangling perceptual and psycholinguistic factors in syntactic processing: Tone monitoring via ERPs

Overview of attention for article published in Behavior Research Methods, July 2017
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Title
Disentangling perceptual and psycholinguistic factors in syntactic processing: Tone monitoring via ERPs
Published in
Behavior Research Methods, July 2017
DOI 10.3758/s13428-017-0932-4
Pubmed ID
Authors

David J. Lobina, Josep Demestre, José E. García-Albea

Abstract

Franco, Gaillard, Cleeremans, and Destrebecqz (Behavior Research Methods, 47, 1393-1403, 2015), in a study on statistical learning employing the click-detection paradigm, conclude that more needs to be known about how this paradigm interacts with statistical learning and speech perception. Past results with this monitoring technique have pointed to an end-of-clause effect in parsing-a structural effect-but we here show that the issues are a bit more nuanced. Firstly, we report two Experiments (1a and 1b), which show that reaction times (RTs) are affected by two factors: (a) processing load, resulting in a tendency for RTs to decrease across a sentence, and (b) a perceptual effect which adds to this tendency and moreover helps neutralize differences between sentences with slightly different structures. These two factors are then successfully discriminated by registering event-related brain potentials (ERPs) during a monitoring task, with Experiment 2 establishing that the amplitudes of the N1 and P3 components-the first associated with temporal uncertainty, the second with processing load in dual tasks-correlate with RTs. Finally, Experiment 3 behaviorally segregates the two factors by placing the last tone at the end of sentences, activating a wrap-up operation and thereby both disrupting the decreasing tendency and highlighting structural effects. Our overall results suggest that much care needs to be employed in designing click-detection tasks if structural effects are sought, and some of the now-classic data need to be reconsidered.

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 17%
Student > Bachelor 2 17%
Student > Master 2 17%
Professor > Associate Professor 2 17%
Researcher 1 8%
Other 0 0%
Unknown 3 25%
Readers by discipline Count As %
Psychology 3 25%
Neuroscience 2 17%
Computer Science 1 8%
Business, Management and Accounting 1 8%
Economics, Econometrics and Finance 1 8%
Other 1 8%
Unknown 3 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 July 2017.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from Behavior Research Methods
#1,896
of 2,526 outputs
Outputs of similar age
#235,963
of 324,713 outputs
Outputs of similar age from Behavior Research Methods
#35
of 44 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
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