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

Karen Safaryan, Reinoud Maex, Neil Davey, Roderick Adams, Volker Steuber

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
143 Downloads (Pure)

Abstract

Many forms of synaptic plasticity require the local production of volatile or rapidly diffusing substances such as nitric oxide. The nonspecific plasticity these
neuromodulators may induce at neighboring non-active synapses is thought to be detrimental for the specificity of memory storage. We show here that memory
retrieval 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.
Original languageEnglish
Article number46550
Number of pages14
JournalScientific Reports
Volume7
DOIs
Publication statusPublished - 20 Apr 2017

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