Stability against fluctuations: Scaling, bifurcations and spontaneous symmetry breaking in stochastic models of synaptic plasticity
Stability against fluctuations: Scaling, bifurcations and spontaneous symmetry breaking in stochastic models of synaptic plasticity
In stochastic models of synaptic plasticity based on a random walk, the control of fluctuations is imperative. We have argued that synapses could act as low-pass filters, filtering plasticity induction steps before expressing a step change in synaptic strength. Earlier work showed, in simulation, that such a synaptic filter tames fluctuations very well, leading to patterns of synaptic connectivity that are stable for long periods of time. Here, we approach this problem analytically. We explicitly calculate the lifetime of meta-stable states of synaptic connectivity using a Fokker-Planck formalism in order to understand the dependence of this lifetime on both the plasticity step size and the filtering mechanism. We find that our analytical results agree very well with simulation results, despite having to make two approximations. Our analysis reveals, however, a deeper significance to the filtering mechanism and the plasticity step size. We show that a filter scales the step size into a smaller, effective step size. This scaling suggests that the step size may itself play the role of a temperature parameter, so that a filter cools the dynamics, thereby reducing the influence of fluctuations. Using the master equation, we explicitly demonstrate a bifurcation at a critical step size, confirming this interpretation. At this critical point, spontaneous symmetry breaking occurs in the class of stochastic models of synaptic plasticity that we consider.
674-734
Elliott, Terry
b4262f0d-c295-4ea4-b5d8-3931470952f9
March 2011
Elliott, Terry
b4262f0d-c295-4ea4-b5d8-3931470952f9
Elliott, Terry
(2011)
Stability against fluctuations: Scaling, bifurcations and spontaneous symmetry breaking in stochastic models of synaptic plasticity.
Neural Computation, 23 (3), .
(doi:10.1162/NECO_a_00088).
(PMID:21162665)
Abstract
In stochastic models of synaptic plasticity based on a random walk, the control of fluctuations is imperative. We have argued that synapses could act as low-pass filters, filtering plasticity induction steps before expressing a step change in synaptic strength. Earlier work showed, in simulation, that such a synaptic filter tames fluctuations very well, leading to patterns of synaptic connectivity that are stable for long periods of time. Here, we approach this problem analytically. We explicitly calculate the lifetime of meta-stable states of synaptic connectivity using a Fokker-Planck formalism in order to understand the dependence of this lifetime on both the plasticity step size and the filtering mechanism. We find that our analytical results agree very well with simulation results, despite having to make two approximations. Our analysis reveals, however, a deeper significance to the filtering mechanism and the plasticity step size. We show that a filter scales the step size into a smaller, effective step size. This scaling suggests that the step size may itself play the role of a temperature parameter, so that a filter cools the dynamics, thereby reducing the influence of fluctuations. Using the master equation, we explicitly demonstrate a bifurcation at a critical step size, confirming this interpretation. At this critical point, spontaneous symmetry breaking occurs in the class of stochastic models of synaptic plasticity that we consider.
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e-pub ahead of print date: 1 February 2011
Published date: March 2011
Organisations:
Web & Internet Science
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Local EPrints ID: 272302
URI: http://eprints.soton.ac.uk/id/eprint/272302
PURE UUID: 4268debb-6b68-411d-9e92-e4747eb7e25b
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Date deposited: 18 May 2011 12:46
Last modified: 14 Mar 2024 09:52
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Author:
Terry Elliott
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