The ideal noisy environment for fast neural computation
Wu, Si, Feng, Jianfeng and Amari, Shun-ichi (2006) The ideal noisy environment for fast neural computation. In: 3rd International Symposium on Neural Networks (ISSN 2006), Chengdu, PEOPLES R CHINA, MAY 28-31, 2006. Published in: ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 1, 3971 (Part 1). pp. 1-6.Full text not available from this repository.
A central issue in computational neuroscience is to answer why neural systems can process information extremely fast. Here we investigate the effect of noise and the collaborative activity of a neural population on speeding up computation. We find that 1) when input noise is Poissonian, i.e., its variance is proportional to the mean, and 2) when the neural ensemble is initially at its stochastic equilibrium state, noise has the 'best' effect of accelerating computation, in the sense that the input strength is linearly encoded by the number of neurons firing in a short-time window, and that the neural system can use a simple strategy to read out the stimulus rapidly and accurately.
|Item Type:||Conference Item (UNSPECIFIED)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software|
|Divisions:||Faculty of Science > Centre for Scientific Computing
Faculty of Science > Computer Science
|Series Name:||LECTURE NOTES IN COMPUTER SCIENCE|
|Journal or Publication Title:||ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 1|
|Editor:||Wang, J and Yi, Z and Zurada, JM and Lu, BL and Yin, HJ|
|Number of Pages:||6|
|Page Range:||pp. 1-6|
|Title of Event:||3rd International Symposium on Neural Networks (ISSN 2006)|
|Location of Event:||Chengdu, PEOPLES R CHINA|
|Date(s) of Event:||MAY 28-31, 2006|
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