BvP neurons exhibit a larger variety in statistics of inter-spike intervals than LIF neurons

スポンサーリンク

概要

• 論文の詳細を見る

• Copyright(c)2006 The Physical Society of JapanIt was recently found that the leaky integrate-and-fire (LIF) model with the assumption of temporally uncorrelated inputs cannot account for the spiking characteristics of in vivo cortical neurons. Specifically, the inter-spike interval (ISI) distributions of some cortical neurons are known to exhibit relatively large skewness to variation, whereas the LIF model cannot realize such statistics with any combination of model parameters. In the present paper, we show that the Bonhoeffer-van del Pol (BvP) model incorporating the same assumption of uncorrelated inputs can, by contrast, exhibit large skewness values. In this case, the large values of the skewness coefficient are caused by the mixture of widely distributed ISIs and short-and-constant ISIs induced by a sub-threshold oscillation peculiar to Class II neurons, such as the BvP neuron.

• 社団法人日本物理学会の論文
• 2006-12-15

著者

• Sakai Yutaka

  Tamagawa Univ. Tokyo

• Yoshizawa Shuji

  Tamagawa University Research Institute

• Ikeguchi Tohru

  Graduate School Of Sci. And Eng. Saitama University

• HOSAKA Ryosuke

  Graduate School of Science and Engineering, Saitama University

• SAKAI Yutaka

  Faculty of Engineering, Tamagawa University

• Hosaka Ryosuke

  Graduate School Of Science And Engineering Saitama University:aihara Complexity Modelling Project Er

• Hosaka Ryosuke

  Graduate School Of Sci. And Eng. Saitama University

関連論文

• サロゲート法おける窓関数の効果(非線形回路とシステム,及び一般)
• サロゲート法おける窓関数の効果(非線形回路とシステム,及び一般)
• Self-Organizing Small-World Structure of Neural Networks by STDP Learning Rule
• Performance of Chaos and Burst Noises Injected to the Hopfield NN for Quadratic Assignment Problems(Neural Networks and Bioengineering)
• A-2-24 ローレンツプロットとポアンカレ断面に基づく引き延ばし・折り畳み構造の解析(A-2.非線形問題,一般講演)
• A-2-16 On Spike Timing Dependent Synaptic Plasticity and Neural Dynamics
• BvP neurons exhibit a larger variety in statistics of inter-spike intervals than LIF neurons
• A-2-17 時間相関入力を受けたsupercritical Hopf分岐型ニューロンのスパイク統計(A-2.非線形問題,一般講演)
• Chaotic motif sampler: detecting motifs from biological sequences by using chaotic neurodynamics
• AS-1-1 Efficient routing strategy using chaotic neural networks
• AS-1-1 A Routing Strategy for Complex Networks with Efficient Memory Information
• A-2-5 Neural Competition Reflects Conduction Delay Distribution in Oscillatory STDP Recurrent Networks
• AS-1-6 Relations between the method for transforming networks to time series and communities in a network

もっと見る 閉じる

スポンサーリンク