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Neurophysiology / Neural networks / Computational neuroscience / Neurology / Synaptic plasticity / Synaptic scaling / Spike-timing-dependent plasticity / Synaptic weight / Chemical synapse / Biology / Neuroscience / Nervous system


Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections Kendra S. Burbank1, Gabriel Kreiman1,2,3* 1 Department of Neurology and Ophthalmology, Children’s Hospital Boston, Harva
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Document Date: 2012-03-15 12:57:00

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File Size: 1,14 MB

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City

Cambridge / Boston / /

Company

Pearson / Creative Commons / /

Country

United States / /

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Facility

University of Oxford / Children’s Hospital / rSTDP Stable / EW Stable / Stable Learning / Harvard University / /

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satisfactory solution / parameter search / recurrent networks / stable solution / analytical network / linear network / feedforward networks / /

Organization

Harvard Medical School / Swartz Center for Theoretical Neuroscience / Center for Brain Science / National Institute of Health / Harvard University / National Science Foundation / Department of Neurology and Ophthalmology / Whitehall Foundation / Children’s Hospital Boston / Department of Neurology / University of Oxford / /

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Spike / Tim Behrens / /

Position

Author / original author / Editor / Representative / /

Product

Kinyo MS-20 Speakers / Sigma DP2 Digital Camera / /

ProvinceOrState

Massachusetts / /

PublishedMedium

PLoS Computational Biology / /

Technology

Neuroscience / neural network / simulation / /

URL

www.ploscompbiol.org / /

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