interference component
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2021 ◽  
Author(s):  
Rafael Román-Caballero ◽  
Andrea Marotta ◽  
Juan Lupiáñez

Recent research has found that eye gaze and arrows yield opposite congruency effects in a spatial interference paradigm, arrows eliciting faster responses when their direction is congruent with their position (standard congruency effect), and gaze producing faster reaction times for incongruent conditions (reversed congruency effect). In addition, we observed by serendipity in a previous study that the standard effect with arrows was reduced when the target appeared within a complex background, presumably because of hindered figure-ground segregation. Under the same conditions, the reversed effect with gaze became more negative. To explain our previous results, we proposed and evaluated the coexistence of two opposite attentional effects with eye gaze: a standard spatial interference component being common to both arrows and gaze, and a larger social-specific dimension leading to the overall reversion of the effect for gaze. Both in Experiment 1 and 2, gaze or arrow targets were presented after or concurrently with an irrelevant background (synchronous and asynchronous conditions). Consistent with our preregistered hypotheses, the standard effect with arrows was only present in the asynchronous condition (automatic figure-ground segregation) but disappeared in synchronous condition (difficult figure-ground segregation). Correspondingly with the effect on arrows interference, eye gaze triggered a significant reversed effect in the synchronous condition that decreased in the asynchronous one. These results underline the importance of the figure-ground segregation processes as modulators of the spatial conflict triggered by peripheral targets, and support our two-effect model that gaze shares with non-social stimuli a domain-general orienting mechanism, but also triggers distinctive processes.


Measurement ◽  
2020 ◽  
Vol 160 ◽  
pp. 107841
Author(s):  
Hongfeng Pang ◽  
Mengchun Pan ◽  
Wei Qu ◽  
Lei Qiu ◽  
Jun Yang ◽  
...  

2018 ◽  
Author(s):  
Krzysztof Cipora ◽  
Philipp A. Schroeder ◽  
Mojtaba Soltanlou ◽  
Hans-Christoph Nuerk

Undoubtedly, tight links between space and number processing exist. Usually, findings of Spatial-Numerical Associations (SNA) are interpreted causally, i.e., that spatial capabilities aid or are even a fundamental cornerstone of mathematical skill. In this book chapter, we question this seemingly ubiquitous assumption.To start with, there is no robust and prevalent correlation between SNA in general and math abilities. After presenting an extended taxonomy for different SNA subtypes, we show that only some SNA subtypes correlate with math abilities, whereas others do not. We argue that these correlations are not conclusive for several reasons. (i) Their correlations vary (i.e., stronger SNA sometimes is related to better math ability, and sometimes to poorer math ability). (ii) The correlations might not show a genuine relation between space and number; rather mediator variables might explain the correlations. For instance, SNA tasks often involve an interference component tapping cognitive control functions (as in multi-digit number processing) or some relatively advanced reasoning skills or strategies. (iii) Finally, the direction of causality (if it exists) is far from resolved. While conventional theories suggest that spatial-numerical abilities underlie arithmetic skill, we argue that vice versa arithmetic abilities instead underlie performance in some spatial-numerical tasks used to assess spatial-numerical representations.On the other hand, benefits conferred by SNA trainings on math abilities seem to reinforce the claim that SNA underlies math abilities. We contend that tasks used in such trainings may tap several cognitive operations required in arithmetic, but not built-up fixed SNAs themselves. Therefore, we argue that using space is a powerful tool, especially for instructing and learning multi-digit numbers; however, this does not necessarily imply an internalized fixed mental number line.


2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Dragoş-Daniel Ţarălungă ◽  
Georgeta-Mihaela Ungureanu ◽  
Ilinca Gussi ◽  
Rodica Strungaru ◽  
Werner Wolf

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios), based on five quantitative performance indices.


2012 ◽  
Vol 246-247 ◽  
pp. 451-455
Author(s):  
Lin Jia Yang ◽  
Lei Rong ◽  
Bi Guang Hong ◽  
Xin Hui Wang

It is inevitable that the wake affects on the braking force of tugboat towing in the stern of a ship. In order to understand the effect of ship-tugboat interaction on the braking force of tugboat, we have to consider two interference components, namely on the tugboat’s braking force in ships wake and on ship’s hull resistance. First, the interference component on the tugboat’s braking force is predicted considering the scale effect of ship’s wake velocity distribution, and using the braking force coefficient of tugboat-self in the uniform flow[1]. Then the interference component on ship’s hull resistance is also estimated under an assumption, which this component in full scale ship is in proportion to Schlichting’s frictional resistance as the component obtained in scale model experiments being a constant. Finally, the effective braking force for full scale tugboats was predicted by using the experiment data and the assumptions mentioned above.


2009 ◽  
Vol 125 (4) ◽  
pp. 1919-1929 ◽  
Author(s):  
Natalie S. Grigorieva ◽  
Gregory M. Fridman ◽  
James A. Mercer ◽  
Rex K. Andrew ◽  
Michael A. Wolfson ◽  
...  

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