Reliability of neuronal information conveyed by unreliable neuristorbased leaky integrate-and-fire neurons: a model study

Title
Reliability of neuronal information conveyed by unreliable neuristorbased leaky integrate-and-fire neurons: a model study
Authors
임형광블라디미르석준영김성근김인호황철성정두석
Keywords
artificial neurons; spiking neural network; neuristor-based leaky integrate and fire neurons; bayesian statistics; population representation
Issue Date
2015-05
Publisher
Scientific Reports
Citation
VOL 5, 9776-1-9776-15
Abstract
We conducted simulations on the neuronal behavior of neuristor-based leaky integrate-and-fire (NLIF) neurons. The phase-plane analysis on the NLIF neuron highlights its spiking dynamics – determined by two nullclines conditional on the variables on the plane. Particular emphasis was placed on the operational noise arising from the variability of the threshold switching behavior in the neuron on each switching event. As a consequence, we found that the NLIF neuron exhibits a Poisson-like noise in spiking, delimiting the reliability of the information conveyed by individual NLIF neurons. To highlight neuronal information coding at a higher level, a population of noisy NLIF neurons was analyzed in regard to probability of successful information decoding given the Poissonlike noise of each neuron. The result demonstrates highly probable success in decoding in spite of large variability – due to the variability of the threshold switching behavior – of individual neurons.
URI
https://pubs.kist.re.kr/handle/201004/49722
ISSN
20452322
Appears in Collections:
KIST Publication > Article
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