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Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise. / Safaryan, Karen; Maex, Reinoud; Davey, Neil; Adams, Roderick; Steuber, Volker.

In: Scientific Reports, Vol. 7, 46550 , 20.04.2017.

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Safaryan, Karen; Maex, Reinoud; Davey, Neil; Adams, Roderick; Steuber, Volker / Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise.

In: Scientific Reports, Vol. 7, 46550 , 20.04.2017.

Research output: Contribution to journalArticle

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@article{b25f333556724f42b812b0986b52e7d1,
title = "Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise",
author = "Karen Safaryan and Reinoud Maex and Neil Davey and Roderick Adams and Volker Steuber",
note = "Safaryan, K. et al. Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise. Sci. Rep. 7, 46550; doi: 10.1038/srep46550 (2017). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2017.",
year = "2017",
month = "4",
doi = "10.1038/srep46550",
volume = "7",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

RIS

TY - JOUR

T1 - Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise

AU - Safaryan,Karen

AU - Maex,Reinoud

AU - Davey,Neil

AU - Adams,Roderick

AU - Steuber,Volker

N1 - Safaryan, K. et al. Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise. Sci. Rep. 7, 46550; doi: 10.1038/srep46550 (2017). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2017.

PY - 2017/4/20

Y1 - 2017/4/20

N2 - Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide. The nonspecific plasticity theseneuromodulators may induce at neighboring non-active synapses is thought to be detrimental for the specificity of memory storage. We show here that memoryretrieval may benefit from this non-specific plasticity when the applied sparse binary input patterns are degraded by local noise. Simulations of a biophysically realistic model of a cerebellar Purkinje cell in a pattern recognition task show that, in the absence of noise, leakage of plasticity to adjacent synapses degrades the recognition of sparse static patterns. However, above a local noise level of 20 %, the model with nonspecific plasticity outperforms the standard, specific model. The gain in performance is greatest when the spatial distribution of noise in the input matches the range of diffusion-induced plasticity. Hence non-specific plasticity may offer a benefit in noisy environments or when the pressure to generalize is strong.

AB - Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide. The nonspecific plasticity theseneuromodulators may induce at neighboring non-active synapses is thought to be detrimental for the specificity of memory storage. We show here that memoryretrieval may benefit from this non-specific plasticity when the applied sparse binary input patterns are degraded by local noise. Simulations of a biophysically realistic model of a cerebellar Purkinje cell in a pattern recognition task show that, in the absence of noise, leakage of plasticity to adjacent synapses degrades the recognition of sparse static patterns. However, above a local noise level of 20 %, the model with nonspecific plasticity outperforms the standard, specific model. The gain in performance is greatest when the spatial distribution of noise in the input matches the range of diffusion-induced plasticity. Hence non-specific plasticity may offer a benefit in noisy environments or when the pressure to generalize is strong.

U2 - 10.1038/srep46550

DO - 10.1038/srep46550

M3 - Article

VL - 7

JO - Scientific Reports

T2 - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 46550

ER -