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The Journal of Neurophysiology Vol. 83 No. 2 February 2000, pp. 808-827
Copyright ©2000 by the American Physiological Society
1Department of Neurobiology, University of California at Los Angeles, Los Angeles, California 90095; 2Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health; and 3Laboratory of Developmental Neurobiology, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892
Latham, P. E.,
B. J. Richmond,
P. G. Nelson, and
S. Nirenberg.
Intrinsic Dynamics in Neuronal Networks. I. Theory. J. Neurophysiol. 83: 808-827, 2000. Many
networks in the mammalian nervous system remain active in the absence
of stimuli. This activity falls into two main patterns: steady firing
at low rates and rhythmic bursting. How are these firing patterns
generated? Specifically, how do dynamic interactions between excitatory
and inhibitory neurons produce these firing patterns, and how do
networks switch from one firing pattern to the other? We investigated
these questions theoretically by examining the intrinsic dynamics of
large networks of neurons. Using both a semianalytic model based on
mean firing rate dynamics and simulations with large neuronal networks,
we found that the dynamics, and thus the firing patterns, are
controlled largely by one parameter, the fraction of endogenously
active cells. When no endogenously active cells are present, networks
are either silent or fire at a high rate; as the number of endogenously
active cells increases, there is a transition to bursting; and, with a
further increase, there is a second transition to steady firing at a
low rate. A secondary role is played by network connectivity, which
determines whether activity occurs at a constant mean firing rate or
oscillates around that mean. These conclusions require only
conventional assumptions: excitatory input to a neuron increases its
firing rate, inhibitory input decreases it, and neurons exhibit
spike-frequency adaptation. These conclusions also lead to two
experimentally testable predictions: 1) isolated networks
that fire at low rates must contain endogenously active cells and
2) a reduction in the fraction of endogenously active cells
in such networks must lead to bursting.
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