Double coherence resonance in neuron models driven by discrete correlated noise

Details Double coherence resonance in neuron models driven by discrete correlated noise Double coherence resonance in neuron models driven by discrete correlated noise

2006-11-13

arxiv.org/abs/cond-mat/0611333v1

Phys. Rev. Lett. 97, 238101 (2006)

Physics

Condensed Matter

Disordered Systems and Neural Networks

4 pages, 3 figures in eps, to appear in Physical Review Letters

Scientific paper

10.1103/PhysRevLett.97.238101

We study the influence of correlations among discrete stochastic excitatory or inhibitory inputs on the response of the FitzHugh-Nagumo neuron model. For any level of correlation the emitted signal exhibits at some finite noise intensity a maximal degree of regularity, i.e., a coherence resonance. Furthermore, for either inhibitory or excitatory correlated stimuli a {\it Double Coherence Resonance} (DCR) is observable. DCR refers to a (absolute) maximum coherence in the output occurring for an optimal combination of noise variance and correlation. All these effects can be explained by taking advantage of the discrete nature of the correlated inputs.

Affiliated with

Also associated with

No associations

Rating

Double coherence resonance in neuron models driven by discrete correlated noise does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Double coherence resonance in neuron models driven by discrete correlated noise, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Double coherence resonance in neuron models driven by discrete correlated noise will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-669160