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When Math Hurts: Math Anxiety Predicts Pain Network Activation in Anticipation of Doing Math

Overview of attention for article published in PLOS ONE, October 2012
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Title
When Math Hurts: Math Anxiety Predicts Pain Network Activation in Anticipation of Doing Math
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0048076
Pubmed ID
Authors

Ian M. Lyons, Sian L. Beilock

Abstract

Math can be difficult, and for those with high levels of mathematics-anxiety (HMAs), math is associated with tension, apprehension, and fear. But what underlies the feelings of dread effected by math anxiety? Are HMAs' feelings about math merely psychological epiphenomena, or is their anxiety grounded in simulation of a concrete, visceral sensation - such as pain - about which they have every right to feel anxious? We show that, when anticipating an upcoming math-task, the higher one's math anxiety, the more one increases activity in regions associated with visceral threat detection, and often the experience of pain itself (bilateral dorso-posterior insula). Interestingly, this relation was not seen during math performance, suggesting that it is not that math itself hurts; rather, the anticipation of math is painful. Our data suggest that pain network activation underlies the intuition that simply anticipating a dreaded event can feel painful. These results may also provide a potential neural mechanism to explain why HMAs tend to avoid math and math-related situations, which in turn can bias HMAs away from taking math classes or even entire math-related career paths.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 541 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 2%
United Kingdom 6 1%
Japan 3 <1%
Canada 2 <1%
Italy 2 <1%
South Africa 1 <1%
Turkey 1 <1%
Romania 1 <1%
Germany 1 <1%
Other 2 <1%
Unknown 510 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 111 21%
Student > Master 80 15%
Student > Bachelor 62 11%
Researcher 49 9%
Student > Doctoral Student 44 8%
Other 96 18%
Unknown 99 18%
Readers by discipline Count As %
Psychology 154 28%
Social Sciences 71 13%
Mathematics 54 10%
Agricultural and Biological Sciences 42 8%
Neuroscience 23 4%
Other 86 16%
Unknown 111 21%