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Extending transfer entropy improves identification of effective connectivity in a spiking cortical network model.

Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to...

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Збережено в:
Бібліографічні деталі
Автори: Shinya Ito, Michael E Hansen, Randy Heiland, Andrew Lumsdaine, Alan M Litke, John M Beggs
Формат: Artigo
Мова:Inglês
Опубліковано: Public Library of Science (PLoS) 2011-01-01
Серія:PLoS ONE
Онлайн доступ:http://europepmc.org/articles/PMC3216957?pdf=render
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