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Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model

Overview of attention for article published in PLoS Computational Biology, August 2013
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Title
Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model
Published in
PLoS Computational Biology, August 2013
DOI 10.1371/journal.pcbi.1003164
Pubmed ID
Authors

Jung H. Lee, Miles A. Whittington, Nancy J. Kopell

Abstract

Cortical rhythms have been thought to play crucial roles in our cognitive abilities. Rhythmic activity in the beta frequency band, around 20 Hz, has been reported in recent studies that focused on neural correlates of attention, indicating that top-down beta rhythms, generated in higher cognitive areas and delivered to earlier sensory areas, can support attentional gain modulation. To elucidate functional roles of beta rhythms and underlying mechanisms, we built a computational model of sensory cortical areas. Our simulation results show that top-down beta rhythms can activate ascending synaptic projections from L5 to L4 and L2/3, responsible for biased competition in superficial layers. In the simulation, slow-inhibitory interneurons are shown to resonate to the 20 Hz input and modulate the activity in superficial layers in an attention-related manner. The predicted critical roles of these cells in attentional gain provide a potential mechanism by which cholinergic drive can support selective attention.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 256 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Germany 4 2%
Switzerland 2 <1%
France 2 <1%
United Kingdom 2 <1%
Netherlands 1 <1%
Estonia 1 <1%
Belarus 1 <1%
Unknown 237 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 94 37%
Researcher 57 22%
Student > Master 19 7%
Student > Bachelor 14 5%
Professor 8 3%
Other 32 13%
Unknown 32 13%
Readers by discipline Count As %
Neuroscience 69 27%
Agricultural and Biological Sciences 45 18%
Psychology 33 13%
Engineering 14 5%
Medicine and Dentistry 14 5%
Other 34 13%
Unknown 47 18%