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Capacity-Speed Relationships in Prefrontal Cortex

Overview of attention for article published in PLOS ONE, November 2011
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Title
Capacity-Speed Relationships in Prefrontal Cortex
Published in
PLOS ONE, November 2011
DOI 10.1371/journal.pone.0027504
Pubmed ID
Authors

Vivek Prabhakaran, Bart Rypma, Nandakumar S. Narayanan, Timothy B. Meier, Benjamin P. Austin, Veena A. Nair, Lin Naing, Lisa E. Thomas, John D. E. Gabrieli

Abstract

Working memory (WM) capacity and WM processing speed are simple cognitive measures that underlie human performance in complex processes such as reasoning and language comprehension. These cognitive measures have shown to be interrelated in behavioral studies, yet the neural mechanism behind this interdependence has not been elucidated. We have carried out two functional MRI studies to separately identify brain regions involved in capacity and speed. Experiment 1, using a block-design WM verbal task, identified increased WM capacity with increased activity in right prefrontal regions, and Experiment 2, using a single-trial WM verbal task, identified increased WM processing speed with increased activity in similar regions. Our results suggest that right prefrontal areas may be a common region interlinking these two cognitive measures. Moreover, an overlap analysis with regions associated with binding or chunking suggest that this strategic memory consolidation process may be the mechanism interlinking WM capacity and WM speed.

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The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 7%
United Kingdom 1 2%
Colombia 1 2%
Unknown 54 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 25%
Student > Ph. D. Student 8 13%
Student > Doctoral Student 7 12%
Student > Master 6 10%
Professor > Associate Professor 5 8%
Other 12 20%
Unknown 7 12%
Readers by discipline Count As %
Psychology 21 35%
Neuroscience 13 22%
Medicine and Dentistry 5 8%
Agricultural and Biological Sciences 4 7%
Engineering 4 7%
Other 6 10%
Unknown 7 12%