HomeostaticPlasticity

Some simple models for plasticity imply that a rich-get-richer dynamic will hold, driving synaptic strengths either to 0 or to infinity. This is undesirable. To combat this, various theoretical normalization schemes have been proposed. Experimental evidence is now being found that some “normalization schemes” actually appear in the brain.

Pages in this section:

• SynapticScaling (some general mechanisms also might be buried in that page)
• IntrinsicPlasticity
• HeterosynapticPlasticity
• STDPAsHomeostaticPlasticity

Theoretical Normalization Schemes

• SubtractiveNormalization?
• MultiplicativeNormalization?

Review papers

• Abbott and Nelson ‘00: Synaptic plasticity: taming the beast
• Burrone and Murthy ‘03: Synaptic gain control and homeostasis.

Mechanisms

• BrainDerivedNeurotrophicFactor has been implicated in SynapticScaling. See BrainDerivedNeurotrophicFactor.

Other kinds of homeostatic plasticity

• Stemmler and Koch ‘99: How voltage-dependent conductances can adapt to maximize the information encoded by neuronal firing rate
  • Spitzer ‘99: New dimensions of neuronal plasticity. Nat Neurosci. 1999 Jun;2(6):489-91. review of Stemmler and Koch ‘99

Refs

• Abbott LF, Nelson SB. Synaptic plasticity: taming the beast. Nat Neurosci. 2000 Nov;3 Suppl:1178-83. (2000)
• Juan Burrone and Venkatesh N Murthy. Synaptic gain control and homeostasis. Current Opinion in Neurobiology, Volume 13, Issue 5, October 2003, Pages 560-567.
• Spitzer NC. New dimensions of neuronal plasticity. Nat Neurosci. 1999 Jun;2(6):489-91.
• Stemmler M, Koch C. How voltage-dependent conductances can adapt to maximize the information encoded by neuronal firing rate. Nat Neurosci. 1999 Jun;2(6):521-7. (1999)

CategoryPlasticity