確率共振現象による海馬ニューロンネットワークモデルでの閾上刺激の情報伝送の改善

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  • カクリツ キョウシン ゲンショウ ニ ヨル カイバ ニューロンネットワークモデル デ ノ ヨクジョウ シゲキ ノ ジョウホウ デンソウ ノ カイゼン
  • カクリツ キョウシン ゲンショウ ニヨル カイバ ニューロン ネットワーク モデル デノ イキジョウ シゲキ ノ ジョウホウ デンソウ ノ カイゼン
  • Improvement of Information Transmission of Supra-threshold Neural Stimuli with Stochastic Resonance in Hippocampal Neuron Network Models

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Stochastic resonance(SR)has been observed to improve detection of subthreshold signals with additive noise(or fluctuations)in a single or an array of nonlinear threshold systems like neurons. However, it has been unclear how SR affects information transfer of supra-threshold neural stimuli in the central nervous system. The objective is to observe whether information transmission of supra-threshold stimuli can be improved by uncorrelated noise in an array of hippocampal CA1 neuron models through computer simulations. Mutual information was estimated as an index of information transmission from the population of spike trains. Results show that the mutual information was maximized at specific noise amplitude in the array of larger number of neuron models(N> 4)with supra-threshold SS(SSR). Moreover, it is shown that SSR could be observed at lower mean frequency(<20 Hz)of the input signals. In conclusion, SSR could play an important role in information processing such as memory formation in hippocampal neurons.

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