Lim, Hyungkwang Kornijcuk, Vladimir Seok, Jun Yeong Kim, Seong Keun Kim, Inho Hwang, Cheol Seong Jeong, Doo Seok 2024-01-20T07:02:55Z 2024-01-20T07:02:55Z 2021-09-04 2015-05-13 2045-2322 https://pubs.kist.re.kr/handle/201004/125449 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 Poisson-like 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. English NATURE PUBLISHING GROUP SYNAPTIC NOISE SPIKING DEVICE INFERENCE SYNAPSES SYSTEM BRAIN Reliability of neuronal information conveyed by unreliable neuristor-based leaky integrate-and-fire neurons: a model study Article 10.1038/srep09776 1 SCIENTIFIC REPORTS, v.5 SCIENTIFIC REPORTS 5 scie scopus 000355214700001 2-s2.0-84929376918 Multidisciplinary Sciences Science & Technology - Other Topics Article SYNAPTIC NOISE SPIKING DEVICE INFERENCE SYNAPSES SYSTEM BRAIN artificial neurons spiking neural network neuristor-based leaky integrate and fire neurons bayesian statistics population representation