{
  "id": "cond-mat/0111546",
  "version": "v1",
  "published": "2001-11-29T00:49:27.000Z",
  "updated": "2001-11-29T00:49:27.000Z",
  "title": "Stochastic Resonance of Ensemble Neurons for Transient Spike Trains: A Wavelet Analysis",
  "authors": [
    "Hideo Hasegawa"
  ],
  "comment": "20 pages, 4 figures",
  "journal": "Phys. Rev. E 66 (2002) 21902",
  "doi": "10.1103/PhysRevE.66.021902",
  "categories": [
    "cond-mat.dis-nn",
    "q-bio.NC"
  ],
  "abstract": "By using the wavelet transformation (WT), we have analyzed the response of an ensemble of $N$ (=1, 10, 100 and 500) Hodgkin-Huxley (HH) neurons to {\\it transient} $M$-pulse spike trains ($M=1-3$) with independent Gaussian noises. The cross-correlation between the input and output signals is expressed in terms of the WT expansion coefficients. The signal-to-noise ratio (SNR) is evaluated by using the {\\it denoising} method within the WT, by which the noise contribution is extracted from output signals. Although the response of a single (N=1) neuron to sub-threshold transient signals with noises is quite unreliable, the transmission fidelity assessed by the cross-correlation and SNR is shown to be much improved by increasing the value of $N$: a population of neurons play an indispensable role in the stochastic resonance (SR) for transient spike inputs. It is also shown that in a large-scale ensemble, the transmission fidelity for supra-threshold transient spikes is not significantly degraded by a weak noise which is responsible to SR for sub-threshold inputs.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2001-11-29T00:49:27.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "transient spike trains",
      "stochastic resonance",
      "wavelet analysis",
      "ensemble neurons",
      "output signals"
    ],
    "tags": [
      "journal article"
    ],
    "publication": {
      "publisher": "APS",
      "journal": "Phys. Rev. E"
    },
    "note": {
      "typesetting": "TeX",
      "pages": 20,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}