Matches in SemOpenAlex for { <https://semopenalex.org/work/W2055147716> ?p ?o ?g. }
- W2055147716 abstract "Signal transmission enhanced by noise has been recently investigated in detail on the single compartment, also referred to as single point, leaky integrate-and-fire model neuron under a subthreshold stimulation. In this paper we study how this phenomenon is influenced by taking into account the spatial characteristics of the neuron. A stochastic two-point leaky integrate-and-fire model, comprising a dendritic compartment and trigger zone, under periodic stimulation is studied. A method of how to measure synchronization between the signal and the output in both, experiments and models, is proposed. This method is based on a distance between the exact periodic spiking, as expected for sufficiently strong and noiseless stimulation, and neuronal activity evoked by a subthreshold signal corrupted by noise. It is shown that qualitatively the same phenomenon, phase-locking enhanced by the noise, as found in the spatially unstructured neuron is produced by the spatially complex neuron. However, quantitatively there are significant differences. Namely, the two-point model neuron is more robust against the noise and therefore its amplitude has to be higher to enhance the signal. Further, it is found that the range of the critical levels of noise is larger for the two-point model than for the single-point one. Finally, the enhancing effect at the optimal noise is more efficient in the single-point model and thus the firing patterns at their optimal noise levels are different in both models." @default.
- W2055147716 created "2016-06-24" @default.
- W2055147716 creator A5054713013 @default.
- W2055147716 creator A5060194983 @default.
- W2055147716 date "2000-12-01" @default.
- W2055147716 modified "2023-09-25" @default.
- W2055147716 title "Effect of spatial extension on noise-enhanced phase locking in a leaky integrate-and-fire model of a neuron" @default.
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- W2055147716 doi "https://doi.org/10.1103/physreve.62.8427" @default.
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