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The dot-probe task to measure emotional attention: A suitable measure in comparative studies?

Overview of attention for article published in Psychonomic Bulletin & Review, January 2017
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Title
The dot-probe task to measure emotional attention: A suitable measure in comparative studies?
Published in
Psychonomic Bulletin & Review, January 2017
DOI 10.3758/s13423-016-1224-1
Pubmed ID
Authors

Rianne van Rooijen, Annemie Ploeger, Mariska E. Kret

Abstract

For social animals, attending to and recognizing the emotional expressions of other individuals is of crucial importance for their survival and likely has a deep evolutionary origin. Gaining insight into how emotional expressions evolved as adaptations over the course of evolution can be achieved by making direct cross-species comparisons. To that extent, experimental paradigms that are suitable for investigating emotional processing across species need to be developed and evaluated. The emotional dot-probe task, which measures attention allocation toward emotional stimuli, has this potential. The task is implicit, and subjects need minimal training to perform the task successfully. Findings in nonhuman primates, although scarce, show that they, like humans, have an attentional bias toward emotional stimuli. However, the wide literature on human studies has shown that different factors can have important moderating effects on the results. Due to the large heterogeneity of this literature, these moderating effects often remain unnoticed. We here review this literature and show that subject characteristics and differences in experimental designs affect the results of the dot-probe task. We conclude with specific recommendations regarding these issues that are particularly relevant to take into consideration when applying this paradigm to study animals.

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The data shown below were compiled from readership statistics for 257 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 257 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 20%
Student > Master 43 17%
Student > Bachelor 37 14%
Researcher 21 8%
Student > Doctoral Student 16 6%
Other 21 8%
Unknown 68 26%
Readers by discipline Count As %
Psychology 108 42%
Neuroscience 25 10%
Agricultural and Biological Sciences 11 4%
Engineering 5 2%
Social Sciences 5 2%
Other 22 9%
Unknown 81 32%