Abstract. We explore the effects of spike-timing-dependent plasticity (STDP) on weak signal transmission in a noisy neural network. We first consider the network where an ensemble of independent neurons, which are subjected to a common weak signal, are connected in parallel to a single postsynaptic neuron via exci-tatory synapses. STDP can make the signal transmission more efficient, and this effect is more prominent when the presynaptic activities exhibit some correlations. We further consider a two-layer network where there are only couplings between two layers and find that postsynaptic neurons can fire synchronously un-der suitable conditions. Both the reliability and timing precision of neuronal firing in the output layer are remarkabl...
<div><p>The brain can learn and detect mixed input signals masked by various types of noise, and spi...
Spike-timing dependent plasticity (STDP), a synaptic modification depending on a relative timing of ...
International audienceSpiking neural networks (SNN) are biologically plausible networks. Compared to...
The influence of a weight-dependent spike-timing dependent plasticity (STDP) rule on the temporal ev...
textabstractExperimental studies have observed synaptic potentiation when a presynaptic neuron fires...
<div><p>We investigate the efficient transmission and processing of weak, subthreshold signals in a ...
Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly bef...
We investigate the efficient transmission and processing of weak, subthreshold signals in a realisti...
Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly bef...
Communication among neurons is the most promising technique for biocompatible nanonetworks. This nec...
We investigate the efficient transmission and processing of weak, subthreshold signals in a realisti...
Abstract — The computational function of neural networks is thought to depend primarily on the learn...
Abstract. Spike-timing-dependent plasticity (STDP) strengthens synapses that are activated immediate...
Spike-frequency adaptation is known to enhance the transmission of information in sensory spiking ne...
Spike-frequency adaptation is known to enhance the transmission of information in sensory spiking ne...
<div><p>The brain can learn and detect mixed input signals masked by various types of noise, and spi...
Spike-timing dependent plasticity (STDP), a synaptic modification depending on a relative timing of ...
International audienceSpiking neural networks (SNN) are biologically plausible networks. Compared to...
The influence of a weight-dependent spike-timing dependent plasticity (STDP) rule on the temporal ev...
textabstractExperimental studies have observed synaptic potentiation when a presynaptic neuron fires...
<div><p>We investigate the efficient transmission and processing of weak, subthreshold signals in a ...
Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly bef...
We investigate the efficient transmission and processing of weak, subthreshold signals in a realisti...
Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly bef...
Communication among neurons is the most promising technique for biocompatible nanonetworks. This nec...
We investigate the efficient transmission and processing of weak, subthreshold signals in a realisti...
Abstract — The computational function of neural networks is thought to depend primarily on the learn...
Abstract. Spike-timing-dependent plasticity (STDP) strengthens synapses that are activated immediate...
Spike-frequency adaptation is known to enhance the transmission of information in sensory spiking ne...
Spike-frequency adaptation is known to enhance the transmission of information in sensory spiking ne...
<div><p>The brain can learn and detect mixed input signals masked by various types of noise, and spi...
Spike-timing dependent plasticity (STDP), a synaptic modification depending on a relative timing of ...
International audienceSpiking neural networks (SNN) are biologically plausible networks. Compared to...