Functional roles of background noise in detecting signals on auditory in formation processing

背景噪声在形成处理中检测听觉信号中的功能作用

• 批准号: 12480086
• 负责人: TATENO Takashi
• 金额: $ 7.87万
• 依托单位: Osaka University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 2000
• 资助国家: 日本
• 起止时间: 2000 至 2001
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-12480086/
• 关键词: Neuroscience; signal detection; information processing; background noise; auditory system; 神経回路網; 多点計測システム; ランダムダイナミカルシステム; 神経モデル

In the sound environment surrounding us, sound information is changing every moment and there exist various kinds of the sound information which is not necessary for us. In the past auditory studies, however, there is little knowledge that background noise plays a constructive role in detecting signals from the real sound environment rather than a distractive one. The main aim of this study is to reveal background-noise effects on biological information processing and information transmission of sensory nervous systems. To this end, at the first step, we concentrate on single neurons and a small network of the neurons, because those neurons and the network are basic elements of the nervous systems. We used neural models and investigated response characteristics of the models derived by an external current in the presence of noise. To analyze the response characteristics of the models, we also used a method of the random dynamical theory, which has been recently developed intensively. In the result, the analysis revealed that background noise increases sensibility of neurons in detecting weak external signals. Thus, one of the future subjects is to understand functional roles of this noise phenomenon in the level of larger neural networks and higher perceptional processing in the brain.

在我们周围的声音环境中，声音信息每时每刻都在变化，存在着各种我们不需要的声音信息。然而，在过去的听觉研究中，很少有人知道背景噪声在检测来自真实声音环境的信号方面发挥了建设性的作用，而不是分散了注意力。本研究的主要目的是揭示背景噪声对生物信息处理和感觉神经系统信息传递的影响。为此，在第一步，我们集中在单个神经元和一个小的神经元网络，因为这些神经元和网络是神经系统的基本元素。我们使用了神经模型，并研究了在存在噪声的情况下，由外部电流导出的模型的响应特性。为了分析模型的响应特性，我们还使用了最近发展起来的随机动力学理论的方法。分析结果表明，背景噪声提高了神经元对微弱外部信号的检测灵敏度。因此，未来的课题之一是在更大的神经网络和大脑中更高的知觉处理水平上理解这种噪声现象的功能作用。

项目成果

T.Tateno: "Analytical characterization of spontaneous firing in networks of developing rat cultured cortical neurons"Physical Review E. (in press). (2002)

T.Tateno：“发育中的大鼠培养皮质神经元网络中自发放电的分析特征”Physical Review E.（出版中）。

T.Tateno: "Noise-induced effects on period-doubling bifurcation for integrate-and-fire oscillators"Physical Review E. 65. 021901-1-021901-10 (2002)

T.Tateno：“积分和激发振荡器的倍周期分岔的噪声引起的影响”物理评论 E. 65. 021901-1-021901-10 (2002)

T.Tateno, A.Kawana, Y.Jimbo: "Analytical characterization of spontaneous firing in networks of developing rat cultured cortical neurons"Physical Review E. (in press). (2002)

T.Tateno、A.Kawana、Y.Jimbo：“发育中的大鼠培养皮质神经元网络中自发放电的分析特征”Physical Review E.（出版中）。

Tateno Takashi: "Noise-induced effects on period-doubling bifurcation for integrate-and-fire oscillators"Physical Review E. (印刷中). (2001)

Tateno Takashi：“积分和发射振荡器的倍周期分岔的噪声引起的影响”物理评论 E.（出版中）。

T.Tateno: "Stochastic mode-locking for a noisy integrate-and-fire oscillator"Physics Letters A. 271. 227-236 (2000)

T.Tateno：“噪声集成发射振荡器的随机锁模”《物理快报》A. 271. 227-236 (2000)