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Multiplicative synaptic normalization and a nonlinear Hebb rule underlie a neurotrophic model of competitive synaptic plasticity

Multiplicative synaptic normalization and a nonlinear Hebb rule underlie a neurotrophic model of competitive synaptic plasticity
Multiplicative synaptic normalization and a nonlinear Hebb rule underlie a neurotrophic model of competitive synaptic plasticity
Synaptic normalization is used to enforce competitive dynamics in many models of developmental synaptic plasticity. In linear and semilinear Hebbian models, multiplicative synaptic normalization fails to segregate afferents whose activity patterns are positively correlated. To achieve this, the biologically problematic device of subtractive synaptic normalization must be used instead. Our own model of competition for neurotrophic support, which can segregate positively correlated afferents, was developed in part in an attempt to overcome these problems by removing the need for synaptic normalization altogether. However, we now show that the dynamics of our model decompose into two decoupled subspaces, with competitive dynamics being implemented in one of them through a nonlinear Hebb rule and multiplicative synaptic normalization. This normalization is "emergent" rather than imposed. We argue that these observations permit biologically plausible forms of synaptic normalization to be viewed as abstract and general descriptions of the underlying biology in certain scaleless models of synaptic plasticity.
1311-1322
Elliott, T.
b4262f0d-c295-4ea4-b5d8-3931470952f9
Shadbolt, N.R.
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Elliott, T.
b4262f0d-c295-4ea4-b5d8-3931470952f9
Shadbolt, N.R.
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7

Elliott, T. and Shadbolt, N.R. (2002) Multiplicative synaptic normalization and a nonlinear Hebb rule underlie a neurotrophic model of competitive synaptic plasticity. Neural Computation, 14 (6), 1311-1322.

Record type: Article

Abstract

Synaptic normalization is used to enforce competitive dynamics in many models of developmental synaptic plasticity. In linear and semilinear Hebbian models, multiplicative synaptic normalization fails to segregate afferents whose activity patterns are positively correlated. To achieve this, the biologically problematic device of subtractive synaptic normalization must be used instead. Our own model of competition for neurotrophic support, which can segregate positively correlated afferents, was developed in part in an attempt to overcome these problems by removing the need for synaptic normalization altogether. However, we now show that the dynamics of our model decompose into two decoupled subspaces, with competitive dynamics being implemented in one of them through a nonlinear Hebb rule and multiplicative synaptic normalization. This normalization is "emergent" rather than imposed. We argue that these observations permit biologically plausible forms of synaptic normalization to be viewed as abstract and general descriptions of the underlying biology in certain scaleless models of synaptic plasticity.

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Published date: June 2002
Organisations: Web & Internet Science

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Local EPrints ID: 260043
URI: https://eprints.soton.ac.uk/id/eprint/260043
PURE UUID: f27fa863-2ca5-4fe2-b15f-41009f485296

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Date deposited: 02 Mar 2005
Last modified: 18 Jul 2017 09:16

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Contributors

Author: T. Elliott
Author: N.R. Shadbolt

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