Noise-driven adaptation: In vitro and mathematical analysis

Liam Paninski, Brian Lau, Alex Reyes

Research output: Contribution to journalArticlepeer-review

Abstract

Variance adaptation processes have recently been examined in cells of the fly visual system and various vertebrate preparations. To better understand the contributions of somatic mechanisms to this kind of adaptation, we recorded intracellularly in vitro from neurons of rat sensorimotor cortex. The cells were stimulated with a noise current whose standard deviation was varied parametrically. We observed systematic variance-dependent adaptation (defined as a scaling of a nonlinear transfer function) similar in many respects to the effects observed in vivo. The fact that similar adaptive phenomena are seen in such different preparations led us to investigate a simple model of stochastic stimulus-driven neural activity. The simplest such model, the leaky integrate-and-fire (LIF) cell driven by noise current, permits us to analytically compute many quantities relevant to our observations on adaptation. We show that the LIF model displays "adaptive" behavior which is quite similar to the effects observed in vivo and in vitro.

Original languageEnglish (US)
Pages (from-to)877-883
Number of pages7
JournalNeurocomputing
Volume52-54
DOIs
StatePublished - Jun 2003

Keywords

  • Adaptation
  • Fokker-Planck
  • Integrate-and-fire
  • Noise

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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