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Variations on the theme of synaptic filtering: a comparison of integrate-and-express models of synaptic plasticity for memory lifetimes

Variations on the theme of synaptic filtering: a comparison of integrate-and-express models of synaptic plasticity for memory lifetimes
Variations on the theme of synaptic filtering: a comparison of integrate-and-express models of synaptic plasticity for memory lifetimes
Integrate-and-express models of synaptic plasticity propose that synapses integrate plasticity induction signals before expressing synaptic plasticity. By discerning trends in their induction signals, synapses can control destabilizing fluctuations in synaptic strength. In a feedforward perceptron framework with binary-strength synapses for associative memory storage, we have previously shown that such a filter-based model outperforms other, nonintegrative, “cascade”-type models of memory storage in most regions of biologically relevant parameter space. Here, we consider some natural extensions of our earlier filter model, including one specifically tailored to binary-strength synapses and one that demands a fixed, consecutive number of same-type induction signals rather than merely an excess before expressing synaptic plasticity. With these extensions, we show that filter-based models outperform nonintegrative models in all regions of biologically relevant parameter space except for a small sliver in which all models encode memories only weakly. In this sliver, which model is superior depends on the metric used to gauge memory lifetimes (whether a signal-to-noise ratio or a mean first passage time). After comparing and contrasting these various filter models, we discuss the multiple mechanisms and timescales that underlie both synaptic plasticity and memory phenomena and suggest that multiple, different filtering mechanisms may operate at single synapses.
2393-2460
Elliott, Terry
b4262f0d-c295-4ea4-b5d8-3931470952f9
Elliott, Terry
b4262f0d-c295-4ea4-b5d8-3931470952f9

Elliott, Terry (2016) Variations on the theme of synaptic filtering: a comparison of integrate-and-express models of synaptic plasticity for memory lifetimes. Neural Computation, 28 (11), 2393-2460. (doi:10.1162/NECO_a_00889).

Record type: Article

Abstract

Integrate-and-express models of synaptic plasticity propose that synapses integrate plasticity induction signals before expressing synaptic plasticity. By discerning trends in their induction signals, synapses can control destabilizing fluctuations in synaptic strength. In a feedforward perceptron framework with binary-strength synapses for associative memory storage, we have previously shown that such a filter-based model outperforms other, nonintegrative, “cascade”-type models of memory storage in most regions of biologically relevant parameter space. Here, we consider some natural extensions of our earlier filter model, including one specifically tailored to binary-strength synapses and one that demands a fixed, consecutive number of same-type induction signals rather than merely an excess before expressing synaptic plasticity. With these extensions, we show that filter-based models outperform nonintegrative models in all regions of biologically relevant parameter space except for a small sliver in which all models encode memories only weakly. In this sliver, which model is superior depends on the metric used to gauge memory lifetimes (whether a signal-to-noise ratio or a mean first passage time). After comparing and contrasting these various filter models, we discuss the multiple mechanisms and timescales that underlie both synaptic plasticity and memory phenomena and suggest that multiple, different filtering mechanisms may operate at single synapses.

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Accepted/In Press date: 27 June 2016
e-pub ahead of print date: 14 September 2016
Published date: November 2016
Organisations: Vision, Learning and Control

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Local EPrints ID: 397433
URI: http://eprints.soton.ac.uk/id/eprint/397433
PURE UUID: 3c9992ae-33ff-4b72-afc5-4b9b06b69f3c

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Date deposited: 01 Jul 2016 09:13
Last modified: 07 Oct 2020 05:12

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