{
  "annotation_id": "b3736f75-5b96-49d6-9c1e-37fba2d7b263",
  "date_created": "2026-03-02T18:00:28.958000Z",
  "date_modified": "2026-03-02T18:00:28.958000Z",
  "file_hash": "dd9fe786054378777c7d1e381db8267dfe1217debb3c473a0c89595803b82d44",
  "private": false,
  "record": {
    "abstract": "Noise aids the encoding of continuous signals into pulse sequences by way of\nstochastic resonance and endows the encoding device with a preferred frequency.\nWe study encoding by a threshold device based on the Ornstein-Uhlenbeck\nprocess, equivalent to the leaky integrate-and-fire neuron model. Preferred\nfrequency, optimum noise intensity, and optimum signal-to-noise ratio are shown\nto be linearly related to the AC amplitude of the input signal. The DC\ncomponent of the input tunes the device either into transmission (preferred\nfrequency nearly independent of signal amplitude) or selection mode (frequency\nrising with amplitude). We argue that this behavior may facilitate selective\nsignal processing in neurons.",
    "arxiv_id": "physics/0004019",
    "authors": [
      "Hans E. Plesser",
      "Theo Geisel"
    ],
    "categories": [
      "physics.bio-ph",
      "q-bio"
    ],
    "title": "Signal Selection Based on Stochastic Resonance",
    "url": "https://arxiv.org/abs/physics/0004019"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "f72e536a-e301-4fd5-91a1-db72dc248393",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}