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Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity
- Source :
- Scientific reports 3, 2926 (2013). doi:10.1038/srep02926, Scientific Reports
- Publication Year :
- 2013
- Publisher :
- Nature Publishing Group, 2013.
-
Abstract
- Intuitively one might expect independent noise to be a powerful tool for desynchronizing a population of synchronized neurons. We here show that, intriguingly, for oscillatory neural populations with adaptive synaptic weights governed by spike timing-dependent plasticity (STDP) the opposite is true. We found that the mean synaptic coupling in such systems increases dynamically in response to the increase of the noise intensity, and there is an optimal noise level, where the amount of synaptic coupling gets maximal in a resonance-like manner as found for the stochastic or coherence resonances, although the mechanism in our case is different. This constitutes a noise-induced self-organization of the synaptic connectivity, which effectively counteracts the desynchronizing impact of independent noise over a wide range of the noise intensity. Given the attempts to counteract neural synchrony underlying tinnitus with noisers and maskers, our results may be of clinical relevance.
- Subjects :
- Nerve net
Models, Neurological
Population
Action Potentials
Biology
Machine learning
computer.software_genre
Article
Neuroplasticity
medicine
Humans
education
Neurons
education.field_of_study
Neuronal Plasticity
Multidisciplinary
Synaptic scaling
Quantitative Biology::Neurons and Cognition
Spike-timing-dependent plasticity
business.industry
Noise
medicine.anatomical_structure
ddc:000
Spike (software development)
Artificial intelligence
Nerve Net
business
Neuroscience
computer
Algorithms
Coherence (physics)
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....84f3d7136a196d050161f255d4577892
- Full Text :
- https://doi.org/10.1038/srep02926