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Why Don't Men Understand Women? Altered Neural Networks for Reading the Language of Male and Female Eyes

Overview of attention for article published in PLOS ONE, April 2013
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Title
Why Don't Men Understand Women? Altered Neural Networks for Reading the Language of Male and Female Eyes
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0060278
Pubmed ID
Authors

Boris Schiffer, Christina Pawliczek, Bernhard W. Müller, Elke R. Gizewski, Henrik Walter

Abstract

Men are traditionally thought to have more problems in understanding women compared to understanding other men, though evidence supporting this assumption remains sparse. Recently, it has been shown, however, that meńs problems in recognizing women's emotions could be linked to difficulties in extracting the relevant information from the eye region, which remain one of the richest sources of social information for the attribution of mental states to others. To determine possible differences in the neural correlates underlying emotion recognition from female, as compared to male eyes, a modified version of the Reading the Mind in the Eyes Test in combination with functional magnetic resonance imaging (fMRI) was applied to a sample of 22 participants. We found that men actually had twice as many problems in recognizing emotions from female as compared to male eyes, and that these problems were particularly associated with a lack of activation in limbic regions of the brain (including the hippocampus and the rostral anterior cingulate cortex). Moreover, men revealed heightened activation of the right amygdala to male stimuli regardless of condition (sex vs. emotion recognition). Thus, our findings highlight the function of the amygdala in the affective component of theory of mind (ToM) and in empathy, and provide further evidence that men are substantially less able to infer mental states expressed by women, which may be accompanied by sex-specific differences in amygdala activity.

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Geographical breakdown

Country Count As %
United States 3 2%
Germany 3 2%
Hungary 1 <1%
Colombia 1 <1%
Uganda 1 <1%
Netherlands 1 <1%
Chile 1 <1%
Portugal 1 <1%
Sweden 1 <1%
Other 7 4%
Unknown 170 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 23%
Student > Bachelor 28 15%
Researcher 25 13%
Student > Master 24 13%
Professor > Associate Professor 12 6%
Other 41 22%
Unknown 17 9%
Readers by discipline Count As %
Psychology 57 30%
Agricultural and Biological Sciences 30 16%
Neuroscience 14 7%
Medicine and Dentistry 12 6%
Social Sciences 12 6%
Other 43 23%
Unknown 22 12%