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On Supertaskers and the Neural Basis of Efficient Multitasking

Overview of attention for article published in Psychonomic Bulletin & Review, September 2014
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Title
On Supertaskers and the Neural Basis of Efficient Multitasking
Published in
Psychonomic Bulletin & Review, September 2014
DOI 10.3758/s13423-014-0713-3
Pubmed ID
Authors

Nathan Medeiros-Ward, Jason M. Watson, David L. Strayer

Abstract

The present study used brain imaging to determine the neural basis of individual differences in multitasking, the ability to successfully perform at least two attention-demanding tasks at once. Multitasking is mentally taxing and, therefore, should recruit the prefrontal cortex to maintain task goals when coordinating attentional control and managing the cognitive load. To investigate this possibility, we used functional neuroimaging to assess neural activity in both extraordinary multitaskers (Supertaskers) and control subjects who were matched on working memory capacity. Participants performed a challenging dual N-back task in which auditory and visual stimuli were presented simultaneously, requiring independent and continuous maintenance, updating, and verification of the contents of verbal and spatial working memory. With the task requirements and considerable cognitive load that accompanied increasing N-back, relative to the controls, the multitasking of Supertaskers was characterized by more efficient recruitment of anterior cingulate and posterior frontopolar prefrontal cortices. Results are interpreted using neuropsychological and evolutionary perspectives on individual differences in multitasking ability and the neural correlates of attentional control.

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Geographical breakdown

Country Count As %
United States 3 3%
Canada 2 2%
Germany 1 <1%
Spain 1 <1%
Unknown 109 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 21%
Researcher 18 16%
Student > Master 16 14%
Student > Bachelor 10 9%
Student > Doctoral Student 9 8%
Other 22 19%
Unknown 17 15%
Readers by discipline Count As %
Psychology 48 41%
Neuroscience 12 10%
Engineering 6 5%
Medicine and Dentistry 5 4%
Business, Management and Accounting 4 3%
Other 15 13%
Unknown 26 22%