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Taming fluctuations in a stochastic model of spike-timing-dependent plasticity

Taming fluctuations in a stochastic model of spike-timing-dependent plasticity
Taming fluctuations in a stochastic model of spike-timing-dependent plasticity
A stochastic model of spike-timing-dependent plasticity proposes that single synapses express fixed-amplitude jumps in strength, the amplitudes being independent of the spike time difference. However, the probability that a jump in strength occurs does depend on spike timing. Although the model has a number of desirable features, the stochasticity of response of a synapse introduces potentially large fluctuations into changes in synaptic strength. These can destabilize the segregated patterns of afferent connectivity characteristic of neuronal development. Previously we have taken these jumps to be small relative to overall synaptic strengths to control fluctuations, but doing so increases developmental times cales unacceptably. Here, we explore three alternative ways of taming fluctuations. First, a calculation of the variance for the change in synaptic strength shows that the mean change eventually dominates fluctuations, but on timescales that are too long. Second, it is possible that fluctuations in strength may cancel between synapses, but we show that correlations between synapses emasculate the law of large numbers. Finally, by separating plasticity induction and expression, we introduce a temporal window during which induction signals are low-pass-filtered before expression. In this way, fluctuations in strength are tamed, stabilizing segregated states of afferent connectivity.
3363-3407
Elliott, Terry
c5bbf1c0-4591-49ea-b390-700751585c1f
Lagogiannis, Konstantinos
b4e6ac18-a57c-4337-a590-9efa14501892
Elliott, Terry
c5bbf1c0-4591-49ea-b390-700751585c1f
Lagogiannis, Konstantinos
b4e6ac18-a57c-4337-a590-9efa14501892

Elliott, Terry and Lagogiannis, Konstantinos (2009) Taming fluctuations in a stochastic model of spike-timing-dependent plasticity. Neural Computation, 21 (12), 3363-3407.

Record type: Article

Abstract

A stochastic model of spike-timing-dependent plasticity proposes that single synapses express fixed-amplitude jumps in strength, the amplitudes being independent of the spike time difference. However, the probability that a jump in strength occurs does depend on spike timing. Although the model has a number of desirable features, the stochasticity of response of a synapse introduces potentially large fluctuations into changes in synaptic strength. These can destabilize the segregated patterns of afferent connectivity characteristic of neuronal development. Previously we have taken these jumps to be small relative to overall synaptic strengths to control fluctuations, but doing so increases developmental times cales unacceptably. Here, we explore three alternative ways of taming fluctuations. First, a calculation of the variance for the change in synaptic strength shows that the mean change eventually dominates fluctuations, but on timescales that are too long. Second, it is possible that fluctuations in strength may cancel between synapses, but we show that correlations between synapses emasculate the law of large numbers. Finally, by separating plasticity induction and expression, we introduce a temporal window during which induction signals are low-pass-filtered before expression. In this way, fluctuations in strength are tamed, stabilizing segregated states of afferent connectivity.

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Published date: 2009
Organisations: Electronics & Computer Science

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Local EPrints ID: 268802
URI: https://eprints.soton.ac.uk/id/eprint/268802
PURE UUID: c2925008-6ed7-458d-b80c-c64a7ec10446

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Date deposited: 01 Apr 2010 15:12
Last modified: 18 Jul 2017 06:51

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