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A Leaky-Integrator Model as a Control Mechanism Underlying Flexible Decision Making during Task Switching

Overview of attention for article published in PLOS ONE, March 2013
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Title
A Leaky-Integrator Model as a Control Mechanism Underlying Flexible Decision Making during Task Switching
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0059670
Pubmed ID
Authors

Akinori Mitani, Ryo Sasaki, Masafumi Oizumi, Takanori Uka

Abstract

The ability to switch between tasks is critical for animals to behave according to context. Although the association between the prefrontal cortex and task switching has been well documented, the ultimate modulation of sensory-motor associations has yet to be determined. Here, we modeled the results of a previous study showing that task switching can be accomplished by communication from distinct populations of sensory neurons. We proposed a leaky-integrator model where relevant and irrelevant information were stored separately in two integrators and task switching was achieved by leaking information from the irrelevant integrator. The model successfully explained both the behavioral and neuronal data. Additionally, the leaky-integrator model showed better performance than an alternative model, where irrelevant information was discarded by decreasing the weight on irrelevant information, when animals initially failed to commit to a task. Overall, we propose that flexible switching is, in part, achieved by actively controlling the amount of leak of relevant and irrelevant information.

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The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 5%
United States 1 2%
Unknown 40 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 23%
Student > Ph. D. Student 9 21%
Student > Bachelor 9 21%
Professor 3 7%
Professor > Associate Professor 3 7%
Other 9 21%
Readers by discipline Count As %
Neuroscience 14 33%
Agricultural and Biological Sciences 7 16%
Engineering 6 14%
Psychology 6 14%
Medicine and Dentistry 5 12%
Other 5 12%