Different Levels of Ih Determine Distinct Temporal Integration in Bursting and Regular-Spiking Neurons in Rat Subiculum

J Physiol. 2006 Oct 1;576(Pt 1):203-14. doi: 10.1113/jphysiol.2006.113944. Epub 2006 Jun 29.

Abstract

Pyramidal neurons in the subiculum typically display either bursting or regular-spiking behaviour. Although this classification into two neuronal classes is well described, it is unknown how these two classes of neurons contribute to the integration of input to the subiculum. Here, we report that bursting neurons possess a hyperpolarization-activated cation current (I(h)) that is two-fold larger (conductance, 5.3 +/- 0.5 nS) than in regular-spiking neurons (2.2 +/- 0.6 nS), whereas I(h) exhibits similar voltage-dependent and kinetic properties in both classes of neurons. Bursting and regular-spiking neurons display similar morphology. The difference in I(h) between the two classes of neurons is not responsible for the distinct firing patterns, as neither pharmacological blockade of I(h) nor enhancement of I(h) using a dynamic clamp affects the qualitative firing patterns. Instead, the difference in I(h) between bursting and regular-spiking neurons determines the temporal integration of evoked synaptic input from the CA1 area. In response to stimulation at 50 Hz, bursting neurons, with a large I(h), show approximately 50% less temporal summation than regular-spiking neurons. The amount of temporal summation in both neuronal classes is equal after pharmacological blockade of I(h). A computer simulation model of a subicular neuron with the properties of either a bursting or a regular-spiking neuron confirmed the pivotal role of I(h) in temporal integration of synaptic input. These data suggest that in the subicular network, bursting neurons are better suited to discriminate the content of high-frequency input, such as that occurring during gamma oscillations, than regular-spiking neurons.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials / physiology*
  • Animals
  • Cations
  • Computer Simulation
  • Electrophysiology
  • Hippocampus / physiology*
  • Ion Channels / physiology*
  • Male
  • Mathematics
  • Membrane Potentials / physiology
  • Neurons / classification*
  • Neurons / physiology*
  • Patch-Clamp Techniques
  • Rats
  • Rats, Wistar
  • Synapses / physiology

Substances

  • Cations
  • Ion Channels