Optimal quantization for energy-efficient information transfer in a population of neuron-like devices

Mark D. McDonnell; Nigel G. Stocks; Charles E. M. Pearce; Derek Abbott

doi:10.1117/12.546934

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25 May 2004 Optimal quantization for energy-efficient information transfer in a population of neuron-like devices

Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, Derek Abbott

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Proceedings Volume 5471, Noise in Complex Systems and Stochastic Dynamics II; (2004) https://doi.org/10.1117/12.546934
Event: Second International Symposium on Fluctuations and Noise, 2004, Maspalomas, Gran Canaria Island, Spain

Abstract

Suprathreshold Stochastic Resonance (SSR) is a recently discovered form of stochastic resonance that occurs in populations of neuron-like devices. A key feature of SSR is that all devices in the population possess identical threshold nonlinearities. It has previously been shown that information transmission through such a system is optimized by nonzero internal noise. It is also clear that it is desirable for the brain to transfer information in an energy efficient manner. In this paper we discuss the energy efficient maximization of information transmission for the case of variable thresholds and constraints imposed on the energy available to the system, as well as minimization of energy for the case of a fixed information rate. We aim to demonstrate that under certain conditions, the SSR configuration of all devices having identical thresholds is optimal. The novel feature of this work is that optimization is performed by finding the optimal threshold settings for the population of devices, which is equivalent to solving a noisy optimal quantization problem.

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Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, and Derek Abbott "Optimal quantization for energy-efficient information transfer in a population of neuron-like devices", Proc. SPIE 5471, Noise in Complex Systems and Stochastic Dynamics II, (25 May 2004); https://doi.org/10.1117/12.546934

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