Detecting and estimating rectification of gap junction conductance based on simulations of dual-cell recordings from a pair and a network of coupled cells

J Theor Biol. 2010 Jul 21;265(2):104-14. doi: 10.1016/j.jtbi.2010.03.048. Epub 2010 Apr 10.

Abstract

Gap junctions can exhibit rectification of conductance. Some reports use inequality of coupling coefficients as the first sign of the possible existence of rectification (Devor and Yarom, 2002; Fan et al., 2005; Levavi-Sivan et al., 2005; Mann-Metzer and Yarom, 1999; Nolan et al., 1999; Szabadics et al., 2001). However, mathematical modeling and simulations of electrotonic coupling between an isolated pair of neurons showed conditions where the coupling coefficients were unreliable indicators of rectification. On the other hand, the transfer resistances were found to be reliable indicators of junctional rectification. The existing mathematical model of cell coupling (Bennett, 1966; Devor and Yarom, 2002; Verselis and Veenstra, 2000) was extended in order to measure rectification of the junctional conductances directly between dual-recorded neurons whether isolated or surrounded by a simulated 3-dimensional network of heterogeneous cells whose gap junctions offered parallel paths for current flow between the recorded neurons. The results showed that the transfer resistances could still detect rectification of the gap junction linking the dual-recorded neurons when embedded in a coupled cell network and that a mathematical model could estimate the conductances in both directions through this gap junction using only data that would be available from real dual-intracellular penetrations which allow electrophysiological recordings and intracellular staining. Rectification of gap junctions in unrecorded cells of a biologically realistic coupled cell network had negligible effects on the voltage responses of the dual-recorded neurons because of minimal current passing through these surrounding cells.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cells / metabolism*
  • Computer Simulation*
  • Electric Conductivity*
  • Electric Impedance
  • Electrophysiological Phenomena*
  • Gap Junctions / metabolism*
  • Models, Biological