Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 13603740
- Type
- D - Journal article
- DOI
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10.1038/srep46550
- Title of journal
- Scientific Reports
- Article number
- 46550
- First page
- -
- Volume
- 7
- Issue
- -
- ISSN
- 2045-2322
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2017
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Result of an ongoing collaboration between colleagues at UH, Ecole Normale Superieure Paris and the University of California Los Angeles. The computer simulations and mathematical analyses that are described in the article show for the first time that non-specific synaptic plasticity at inactive inputs can improve associate memory performance by enhancing the robustness against local noise. This has implications for theories of associative memory in many neural systems with leakage of plasticity. Early versions of the work have led to an invited presentation at the Gordon Research Conference on the Cerebellum (New London, NH, USA, 2011).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -