Sensitivity of Firing Rate to Input Fluctuations Depends on Time Scale Separation Between Fast and Slow Variables in Single Neurons

J Comput Neurosci. 2009 Oct;27(2):277-90. doi: 10.1007/s10827-009-0142-x. Epub 2009 Apr 8.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Action Potentials / physiology
  • Algorithms
  • Animals
  • Cell Membrane / physiology
  • Central Nervous System / physiology*
  • Computer Simulation
  • Humans
  • Membrane Potentials / physiology
  • Nerve Net / physiology*
  • Neurons / physiology*
  • Time Factors