Emergence of Resonances in Neural Systems: The Interplay between Adaptive Threshold and Short-Term Synaptic Plasticity
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Public Library of Science (PLOS)
DepressionMembrane potentialNeural networksNeuronsNeurotransmittersResonance frequencySignal processingSynapses
Mejias, J.F.; Torres, J.J. Emergence of Resonances in Neural Systems: The Interplay between Adaptive Threshold and Short-Term Synaptic Plasticity. Plos One, 6(3): e17255 (2011). [http://hdl.handle.net/10481/31020]
PatrocinadorThis work was supported by the MEyC-FEDER project FIS2009-08451 and the Junta de Andalucia projects P06–FQM–01505 and P07–FQM–02725.
In this work we study the detection of weak stimuli by spiking (integrate-and-fire) neurons in the presence of certain level of noisy background neural activity. Our study has focused in the realistic assumption that the synapses in the network present activity-dependent processes, such as short-term synaptic depression and facilitation. Employing mean-field techniques as well as numerical simulations, we found that there are two possible noise levels which optimize signal transmission. This new finding is in contrast with the classical theory of stochastic resonance which is able to predict only one optimal level of noise. We found that the complex interplay between adaptive neuron threshold and activity-dependent synaptic mechanisms is responsible for this new phenomenology. Our main results are confirmed by employing a more realistic FitzHugh-Nagumo neuron model, which displays threshold variability, as well as by considering more realistic stochastic synaptic models and realistic signals such as poissonian spike trains.