Review
Homeostatic plasticity in neuronal networks: the more things change, the more they stay the same

https://doi.org/10.1016/S0166-2236(98)01341-1Get rights and content

Abstract

During learning and development, neural circuitry is refined, in part, through changes in the number and strength of synapses. Most studies of long-term changes in synaptic strength have concentrated on Hebbian mechanisms, where these changes occur in a synapse-specific manner. While Hebbian mechanisms are important for modifying neuronal circuitry selectively, they might not be sufficient because they tend to destabilize the activity of neuronal networks. Recently, several forms of homeostatic plasticity that stabilize the properties of neural circuits have been identified. These include mechanisms that regulate neuronal excitability, stabilize total synaptic strength, and influence the rate and extent of synapse formation. These forms of homeostatic plasticity are likely to go ‘hand-in-glove’ with Hebbian mechanisms to allow experience to modify the properties of neuronal networks selectively.

Section snippets

Homeostasis of the intrinsic electrical properties of neurons

During the lifetime of a neuron, its electrical, morphological and synaptic properties fluctuate constantly. Neurons grow, change shape, lose and gain synapses, and there is a constant turnover of the ion channels that determine the neuron's electrical-firing properties. Yet despite this constant flux, neurons are able to maintain relatively constant firing properties over time. Much theoretical and experimental work suggests that neurons accomplish this by regulating the balance of ionic

Synaptic homeostasis at the Drosophila NMJ

At the Drosophila NMJ, there is a very restricted range of synaptic efficacies over which the muscle will function properly. Many muscle fibers are innervated by a single motoneuron and, if the strength of that connection is too high or too low, the muscle will either experience tetanus or will fail to contract. Recent work suggests that the strength of neuromuscular transmission in Drosophila is regulated precisely to preserve synaptic efficacy within a functional range. Genetic manipulations

Multiplicative scaling of cortical synaptic strengths

Maintaining activity within functional boundaries is a more difficult problem for neurons in the CNS than for muscles. These neurons receive thousands of synaptic inputs that can be excitatory, inhibitory or modulatory, and the neuron must usually integrate many inputs to cross the firing threshold. In addition, during learning and development, all of these inputs might be changing simultaneously in both number and strength. What are the rules for regulating synaptic strengths that allow

Neurotrophins and homeostasis in cortical networks

An important aspect of synaptic scaling in cultured cortical networks is that the direction of change of a synapse depends on both the nature of the synapse and the nature of the postsynaptic neuron35, 36, 37. Cortical pyramidal neurons are embedded in complex networks with extensive recurrent excitatory and inhibitory feedback. Pyramidal-neuron firing rates reflect not only excitatory drive, but also the balance between excitatory inputs from other pyramidal neurons and inhibitory inputs from

Activity-dependent stabilization of synaptic connections

Synaptogenesis is a complex process requiring that neurons extend their axons long distances and form selective contacts with their targets. Once contacts are made, a process of activity-dependent refinement occurs, in which appropriate connections are strengthened and stabilized, and inappropriate connections are lost3, 8, 55. This process is similar in many respects to Hebbian mechanisms of synaptic plasticity, in that stabilization requires correlated pre- and postsynaptic activity, is

Emerging themes in homeostatic plasticity

Investigations into the role of homeostatic plasticity in network function are relatively new, but several themes from a diverse set of systems are beginning to emerge. First, neurons can use their own activity as a feedback signal to modify intrinsic excitability and to maintain total synaptic strength at a roughly constant level. Several distinct mechanisms exist that can adjust synaptic efficacy, which include changes in neurotransmitter release probability at the Drosophila NMJ, and changes

Acknowledgements

The author thanks Sacha Nelson, Eve Marder, Larry Abbott and Hollis Cline for many insightful discussions and for comments on the manuscript. The author's research was supported by K02 NS01893 and R01 NS36853.

References (58)

  • C.J. Shatz

    Neuron

    (1990)
  • R.C. Malenka et al.

    Trends Neurosci.

    (1993)
  • H.T. Cline

    Trends Neurosci.

    (1991)
  • K.D. Miller

    Neuron

    (1996)
  • G.W. Davis et al.

    Curr. Opin. Neurobiol.

    (1998)
  • C.M. Schuster et al.

    Neuron

    (1996)
  • G.W. Davis et al.

    Neuron

    (1997)
  • G.W. Davis

    Neuron

    (1998)
  • S.A. Petersen

    Neuron

    (1997)
  • L.C. Rutherford et al.

    Neuron

    (1998)
  • H. Colman et al.

    Trends Neurosci.

    (1992)
  • P.J. Isackson

    Neuron

    (1991)
  • T. Bonhoeffer

    Curr. Opin. Neurobiol.

    (1996)
  • M. Constantine-Paton et al.

    Curr. Opin. Neurobiol.

    (1998)
  • D-J. Zou et al.

    Neuron

    (1996)
  • D.O. Hebb

    The Organization of Behavior: A Neurophysiological Theory

    (1949)
  • G.S. Stent

    Proc. Natl. Acad. Sci. U. S. A.

    (1973)
  • R.D. Hawkins et al.

    Annu. Rev. Neurosci.

    (1993)
  • D.J. Linden et al.

    Annu. Rev. Neurosci.

    (1995)
  • K.D. Miller
  • C. von der Malsburg

    Kybernetik

    (1973)
  • E.L. Bienenstock et al.

    J. Neurosci.

    (1982)
  • K.D. Miller et al.

    Neural Comput.

    (1994)
  • M.F. Bear

    Proc. Natl. Acad. Sci. U. S. A.

    (1996)
  • G. Le Masson et al.

    Science

    (1993)
  • G.G. Turrigiano et al.

    Science

    (1994)
  • G.G. Turrigiano et al.

    J. Neurosci.

    (1995)
  • Z. Liu

    J. Neurosci.

    (1998)
  • M. Thoby-Brison et al.

    J. Neurosci.

    (1998)
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