JN Fuel your research with LabChart
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


J Neurophysiol 89: 2430-2440, 2003; doi:10.1152/jn.01000.2002
0022-3077/03 $5.00
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via ISI Web of Science (1)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Jamieson, J.
Right arrow Articles by McLachlan, E. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Jamieson, J.
Right arrow Articles by McLachlan, E. M.

J Neurophysiol (May 1, 2003). 10.1152/jn.01000.2002
Submitted on Submitted 4 November 2002; accepted in final form 18 November 2002

Simulations to Derive Membrane Resistivity in Three Phenotypes of Guinea Pig Sympathetic Postganglionic Neuron

John Jamieson, Hugh D. Boyd, and Elspeth M. McLachlan

Prince of Wales Medical Research Institute, Randwick, New South Wales 2031; and the University of New South Wales, New South Wales 2052, Australia

Jamieson, John, Hugh D. Boyd, and Elspeth M. McLachlan. Simulations to Derive Membrane Resistivity in Three Phenotypes of Guinea Pig Sympathetic Postganglionic Neuron. J. Neurophysiol. 89: 2430-2440, 2003. The electrotonic behavior of three phenotypes of sympathetic postganglionic neuron has been analyzed to assess whether their distinct cell input capacitances simply reflect differences in morphology. Because the distribution of membrane properties over the soma and dendrites is unknown, compartmental models incorporating cell morphology were used to simulate hyperpolarizing responses to small current steps. Neurons were classified as phasic (Ph), tonic (T), or long-afterhyperpolarizing (LAH) by their discharge pattern to threshold depolarizing current steps and filled with biocytin to determine their morphology. Responses were simulated in models with the average morphology of each cell class using the program NEURON. Specific membrane resistivity, Rm, was derived in each model. Fits were acceptable when specific membrane capacitance, Cm, and specific resistivity of the axoplasm, Ri, were varied within realistic limits and when underestimation of membrane area due to surface irregularities was accounted for. In all models with uniform Rm, solutions for Rm that were the same for all classes could not be found unless Cm or Ri were different for each class, which seems unrealistic. Incorporation of a small somatic shunt conductance yielded values for Rm for each class close to those derived assuming isopotentiality (Rm approximately 40, 27, and 15 kOmega cm2 for T, Ph, and LAH neurons, respectively). It is concluded that Rm is distinct between neuron classes. Because Ph and LAH neurons relay selected preganglionic inputs directly, Rm generally affects function only in T neurons that integrate multiple subthreshold inputs and are modulated by peptidergic transmitters.







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Visit Other APS Journals Online