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The road toward a physiological control of artificial respiration: the role of bio-inspired neuronal networks. [PDF]
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Three-factor learning in spiking neural networks: An overview of methods and trends from a machine learning perspective. [PDF]
Patterns (N Y)Mazurek S +3 more
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Decoding spikes in a spiking neuronal network
Journal of Physics A: Mathematical and General, 2004Summary: We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It
Feng, Jianfeng, Ding, Mingzhou
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Spiking Neural Networks for Cortical Neuronal Spike Train Decoding
Neural Computation, 2010Recent investigation of cortical coding and computation indicates that temporal coding is probably a more biologically plausible scheme used by neurons than the rate coding used commonly in most published work. We propose and demonstrate in this letter that spiking neural networks (SNN), consisting of spiking neurons that propagate information by the ...
Fang, Huijuan, Wang, Yongji, He, Jiping
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Image Segmentation by Networks of Spiking Neurons
Neural Computation, 2005A network of leaky integrate-and-fire (IAF) neurons is proposed to segment gray-scale images. The network architecture with local competition between neurons that encode segment assignments of image blocks is motivated by a histogram clustering approach to image segmentation. Lateral excitatory connections between neighboring image sites yield a local
Buhmann, Joachim M. +2 more
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Neuronal avalanches in Watts-Strogatz networks of stochastic spiking neurons
Physical Review E, 2021Networks of stochastic leaky integrate-and-fire neurons, both at the mean-field level and in square lattices, present a continuous absorbing phase transition with power-law neuronal avalanches at the critical point. Here we complement these results showing that small-world Watts-Strogatz networks have mean-field critical exponents for any rewiring ...
Renata Pazzini +2 more
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Fast Sigmoidal Networks via Spiking Neurons
Neural Computation, 1997We show that networks of relatively realistic mathematical models for biological neurons in principle can simulate arbitrary feedforward sigmoidal neural nets in a way that has previously not been considered. This new approach is based on temporal coding by single spikes (respectively by the timing of synchronous firing in pools of neurons) rather ...
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Associative memory in networks of spiking neurons
Neural Networks, 2001Here, we develop and investigate a computational model of a network of cortical neurons on the base of biophysically well constrained and tested two-compartmental neurons developed by Pinsky and Rinzel [Pinsky, P. F., & Rinzel, J. (1994). Intrinsic and network rhythmogenesis in a reduced Traub model for CA3 neurons.
F T, Sommer, T, Wennekers
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Spiking Neuron-Astrocyte Networks for Image Recognition
Neural ComputationAbstract From biological and artificial network perspectives, researchers have started acknowledging astrocytes as computational units mediating neural processes. Here, we propose a novel biologically inspired neuron-astrocyte network model for image recognition, one of the first attempts at implementing astrocytes in spiking neuron ...
Lorenzo, Jhunlyn +3 more
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