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The Journal of Neurophysiology Vol. 83 No. 2 February 2000, pp. 984-997
Copyright ©2000 by the American Physiological Society
1Howard Hughes Medical Institute, Computational Neurobiology Laboratory, The Salk Institute, La Jolla 92037; and 2Department of Physics, 3Neurobiology Unit, Scripps Institution of Oceanography, 4Department of Neuroscience, and 5Department of Biology, University of California, San Diego, La Jolla, California 92093
Moortgat, Katherine T.,
Theodore H. Bullock, and
Terrence J. Sejnowski.
Gap Junction Effects on Precision and Frequency of a Model
Pacemaker Network. J. Neurophysiol. 83: 984-997, 2000. We investigated the precision of spike timing in a
model of gap junction-coupled oscillatory neurons. The model
incorporated the known physiology, morphology, and connectivity of the
weakly electric fish's high-frequency and extremely precise pacemaker nucleus (Pn). Two neuron classes, pacemaker and relay cells, were each
modeled with two compartments containing Hodgkin-Huxley sodium and
potassium currents. Isolated pacemaker cells fired periodically, due to
a constant current injection; relay cells were silent but slightly
depolarized at rest. When coupled by gap junctions to other neurons, a
model neuron, like its biological correlate, spiked at frequencies and
amplitudes that were largely independent of current injections. The
phase distribution in the network was labile to intracellular current
injections and to gap junction conductance changes. The model predicts
a biologically plausible gap junction conductance of 4-5 nS (200-250
M
). This results in a coupling coefficient of ~0.02, as observed
in vitro. Network parameters were varied to test which could improve
the temporal precision of oscillations. Increased gap junction
conductances and larger numbers of cells (holding total junctional
conductance per cell constant) both substantially reduced the
coefficient of variation (CV = standard deviation/mean) of relay
cell spike times by 74-85% and more, and did so with lower gap
junction conductance when cells were contacted axonically compared with
somatically. Pacemaker cell CV was only reduced when the probability of
contact was increased, and then only moderately: a fivefold increase in the probability of contact reduced CV by 35%. We conclude that gap
junctions facilitate synchronization, can reduce CV, are most effective
between axons, and that pacemaker cells must have low intrinsic CV to
account for the low CV of cells in the biological network.
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