Sensitivity of firing rate to input fluctuations depends on time scale separation between fast and slow variables in single neurons

Brian Nils Lundstrom, Michael Famulare, Larry B. Sorensen, William J. Spain, Adrienne L. Fairhall

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f-I curve. We introduce a novel classification of neurons into Types A, B-, and B+ according to how f-I curves are modulated by input fluctuations. In Type A neurons, the f-I curves display little sensitivity to input fluctuations when the mean current is large. In contrast, Type B neurons display sensitivity to fluctuations throughout the entire range of input means. Type B- neurons do not fire repetitively for any constant input, whereas Type B+ neurons do. We show that Type B+ behavior results from a separation of time scales between a slow and fast variable. A voltage-dependent time constant for the recovery variable can facilitate sensitivity to input fluctuations. Type B+ firing rates can be approximated using a simple "energy barrier" model.

Original languageEnglish (US)
Pages (from-to)277-290
Number of pages14
JournalJournal of Computational Neuroscience
Volume27
Issue number2
DOIs
StatePublished - 2009

Keywords

  • Dynamical systems
  • Gain
  • Hodgkin-Huxley
  • Noise
  • Phase portrait
  • Single neuron
  • Slow AHP
  • Slowad aptation
  • Stimulus fluctuations
  • Time scales
  • f-I curve

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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