Results 261 to 269 of about 52,867 (269)
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Synchrony in Heterogeneous Networks of Spiking Neurons

Neural Computation, 2000
The emergence of synchrony in the activity of large, heterogeneous networks of spiking neurons is investigated. We define the robustness of synchrony by the critical disorder at which the asynchronous state becomes linearly unstable. We show that at low firing rates, synchrony is more robust in excitatory networks than in inhibitory networks, but ...
Neltner, L.   +3 more
openaire   +2 more sources

Network inference for spike-count neurons

2022
Bernstein Conference 2022 abstract.
Kühn, Tobias, Ferrari, Ulisse
openaire   +1 more source

Temporal Correlations in Stochastic Networks of Spiking Neurons

Neural Computation, 2002
The determination of temporal and spatial correlations in neuronal activity is one of the most important neurophysiological tools to gain insight into the mechanisms of information processing in the brain. Its interpretation is complicated by the difficulty of disambiguating the effects of architecture, single-neuron properties, and network dynamics ...
Meyer, Carsten, van Vreeswijk, Carl
openaire   +2 more sources

Complex Spike Patterns in Olfactory Bulb Neuronal Networks

Journal of Neuroscience Methods, 2015
T-pattern analysis is a procedure developed for detecting non-randomly recurring hierarchical and multiordinal real-time sequential patterns (T-patterns).We have inquired whether such patterns of action potentials (spikes) can be extracted from extracellular activity sampled simultaneously from many neurons across the mitral cell layer of the olfactory
Alister U. Nicol   +2 more
openaire   +2 more sources

Synchronized Interactions in Spiked Neuronal Networks

The Computer Journal, 2008
The study of artificial neural networks has originally been inspired by neurophysiology and cognitive science. It has resulted in a rich and diverse methodology and in numerous applications to machine intelligence, computer vision, pattern recognition and other applications. The random neural network (RNN) is a probabilistic model which was inspired by
E. Gelenbe, S. Timotheou
openaire   +1 more source

Photonic spiking neurons and spiking neural networks

Semiconductor Lasers and Laser Dynamics XI
Dafydd Owen-Newns   +5 more
openaire   +1 more source

Neuromorphic Networks of Spiking Neurons

2018
Giacomo Indiveri, Rodney Douglas
openaire   +1 more source

Supercomputer simulations of spiking neuronal networks

2014
Kunkel, Susanne   +3 more
openaire   +1 more source

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