Literature DB >> 3711977

Quantification of membrane properties of trigeminal root ganglion neurons in guinea pigs.

E Puil, B Gimbarzevsky, R M Miura.   

Abstract

Passive and active (voltage- and time-dependent) membrane properties of trigeminal root ganglion neurons of decerebrate guinea pigs have been determined using frequency-domain analyses of small-amplitude perturbations of membrane voltage. The complex impedance functions of trigeminal ganglion neurons were computed from the ratios of the fast Fourier transforms of the intracellularly recorded voltage response from the neuron and of the input current, which had a defined oscillatory waveform. The impedance magnitude functions and corresponding impedance locus diagrams were fitted with various membrane models such that the passive and active properties were quantified. The complex impedances of less than one-quarter of the 105 neurons which were investigated extensively could be described by the complex impedance function for a simple RC-electrical circuit. In such neurons, the voltage responses to constant-current pulses, using conventional bridge-balance techniques, could be fitted with single exponential curves, also suggesting passive membrane behavior. A nonlinear least-squares fit of the complex impedance function for the simple model to the experimentally observed complex impedance yielded estimates of the resistance of the electrode, and of input capacitance (range, 56 to 490 pF) and input resistance (range, 0.8 to 30 M omega) of the neurons. The majority of trigeminal ganglion neurons were characterized by a resonance in the 50- to 250-Hz bandwidth of their impedance magnitude functions. Such neurons when injected with "large" hyperpolarizing current pulses using bridge-balance techniques showed membrane voltage responses that "sagged" (time-dependent rectification). Also, repetitive firing commonly occurred with depolarizing current pulses; this characteristic of neurons with resonance in their impedance magnitude functions was not observed in neurons with "purely" passive membrane behavior. A nonlinear least-squares fit of a five-parameter impedance fitting function based on a membrane model to the impedance locus diagram of a neuron with resonance yielded estimates of its membrane properties: input capacitance, the time-invariant part of the conductance, the conductance activated by the small oscillatory input current, and the relaxation time constant for this conductance. The ranges of the estimates for input capacitance and input resistance were comparable to the ranges of corresponding properties derived for neurons exhibiting "purely" passive behavior.(ABSTRACT TRUNCATED AT 400 WORDS)

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Year:  1986        PMID: 3711977     DOI: 10.1152/jn.1986.55.5.995

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  54 in total

1.  Electrical coupling and excitatory synaptic transmission between rhythmogenic respiratory neurons in the preBötzinger complex.

Authors:  J C Rekling; X M Shao; J L Feldman
Journal:  J Neurosci       Date:  2000-12-01       Impact factor: 6.167

2.  Distinct frequency preferences of different types of rat hippocampal neurones in response to oscillatory input currents.

Authors:  F G Pike; R S Goddard; J M Suckling; P Ganter; N Kasthuri; O Paulsen
Journal:  J Physiol       Date:  2000-11-15       Impact factor: 5.182

3.  Two forms of electrical resonance at theta frequencies, generated by M-current, h-current and persistent Na+ current in rat hippocampal pyramidal cells.

Authors:  Hua Hu; Koen Vervaeke; Johan F Storm
Journal:  J Physiol       Date:  2002-12-15       Impact factor: 5.182

4.  Membrane resonance and subthreshold membrane oscillations in mesencephalic V neurons: participants in burst generation.

Authors:  N Wu; C F Hsiao; S H Chandler
Journal:  J Neurosci       Date:  2001-06-01       Impact factor: 6.167

5.  Dynamics of rat entorhinal cortex layer II and III cells: characteristics of membrane potential resonance at rest predict oscillation properties near threshold.

Authors:  I Erchova; G Kreck; U Heinemann; A V M Herz
Journal:  J Physiol       Date:  2004-07-22       Impact factor: 5.182

6.  Properties and functional implications of I (h) in hippocampal area CA3 interneurons.

Authors:  Warren D Anderson; Emilio J Galván; Jocelyn C Mauna; Edda Thiels; Germán Barrionuevo
Journal:  Pflugers Arch       Date:  2011-09-21       Impact factor: 3.657

Review 7.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

8.  GAD67-GFP+ neurons in the Nucleus of Roller. II. Subthreshold and firing resonance properties.

Authors:  J F M van Brederode; A J Berger
Journal:  J Neurophysiol       Date:  2010-11-03       Impact factor: 2.714

Review 9.  Electrical resonance with voltage-gated ion channels: perspectives from biophysical mechanisms and neural electrophysiology.

Authors:  Lin Ge; Xiao-dong Liu
Journal:  Acta Pharmacol Sin       Date:  2016-01       Impact factor: 6.150

10.  Low-dimensional, morphologically accurate models of subthreshold membrane potential.

Authors:  Anthony R Kellems; Derrick Roos; Nan Xiao; Steven J Cox
Journal:  J Comput Neurosci       Date:  2009-01-27       Impact factor: 1.621

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