Stochastic resonance can enhance information transmission of supra-threshold neural signals
| Autor: | Minato Kawaguchi, Dominique Durand, Keiko Momose, Hiroyuki Mino |
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| Rok vydání: | 2009 |
| Předmět: |
Stochastic resonance
Computer science Quantitative Biology::Tissues and Organs Monte Carlo method Population Hippocampus Membrane Potentials Background noise Entropy (classical thermodynamics) Electricity Neural Pathways Animals Entropy (information theory) Detection theory Entropy (energy dispersal) education Entropy (arrow of time) Neurons Stochastic Processes education.field_of_study Quantitative Biology::Neurons and Cognition Artificial neural network Stochastic process Entropy (statistical thermodynamics) business.industry Numerical analysis Stochastic resonance (sensory neurobiology) Mutual information Uncorrelated Rats Hodgkin–Huxley model Synaptic noise Amplitude Artificial intelligence Biological system business Signal Transduction Entropy (order and disorder) |
| Zdroj: | Scopus-Elsevier |
| DOI: | 10.1109/iembs.2009.5333973 |
| Popis: | Stochastic resonance (SR) has been shown to improve detection of sub-threshold signals with additive uncor-related background noise, not only in a single hippocampal CA1 neuron model, but in a population of hippocampal CA1 neuron models (Array-Enhanced Stochastic Resonance; AESR). However, most of the information in the CNS is transmitted through supra-threshold signals and the effect of stochastic resonance in neurons on these signals is unknown. Therefore, we investigate through computer simulations whether information transmission of supra-threshold input signal can be improved by uncorrelated noise in a population of hippocampal CA1 neuron models by supra-threshold stochastic resonance (SSR). The mutual information was estimated as an index of information transmission via total and noise entropies from the inter-spike interval (ISI) histograms of the spike trains generated by gathering each of spike trains in a population of hippocampal CA1 neuron models at N = 3D1, 2, 4, 10, 20 and 50. It was shown that the mutual information was maximized at a specific amplitude of uncorrelated noise, i.e., a typical curve of SR was observed when the number of neurons was greater than 10 with SSR. However, SSR did not affect the information transfer with a small number of neurons. In conclusion, SSR may play an important role in processing information such as memory formation in a population of hippocampal neurons. |
| Databáze: | OpenAIRE |
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