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. 2012 Dec 20;8(12):e1002836. doi: 10.1371/journal.pcbi.1002836

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© 2012 van Rossum et al

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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A) A neuron receives binary pattern inputs. At each time-step a new pattern is presented and the weights are updated according to the input value. The neuron's output equals the weighted sum of the inputs. B) The neuron has to remember the presented patterns. When tested, learned patterns lead to a larger output (solid curve) than lures (dashed curve). As the memory of the pattern ages and is overwritten by new patterns, the output of the neuron in response to the pattern becomes less distinct and the signal-to-noise ratio decays. The performance is measured by the signal-to-noise ratio, a measure of the distance between the two output distributions. C) The decay of the signal-to-noise ratio for soft-bound and hard-bound plasticity rules as a function of the age of the pattern. The synaptic updates were set so that both rules led to an initial SNR of 100 right after the pattern was presented (, ). For both plasticity rules the SNR decays, but it decays slower for soft-bound plasticity.

Inline graphic — A) A neuron receives binary pattern inputs. At each time-step a new pattern is presented and the weights are updated according to the input value. The neuron's output equals the weighted sum of the inputs. B) The neuron has to remember the presented patterns. When tested, learned patterns lead to a larger output (solid curve) than lures (dashed curve). As the memory of the pattern ages and is overwritten by new patterns, the output of the neuron in response to the pattern becomes less distinct and the signal-to-noise ratio decays. The performance is measured by the signal-to-noise ratio, a measure of the distance between the two output distributions. C) The decay of the signal-to-noise ratio for soft-bound and hard-bound plasticity rules as a function of the age of the pattern. The synaptic updates were set so that both rules led to an initial SNR of 100 right after the pattern was presented (, ). For both plasticity rules the SNR decays, but it decays slower for soft-bound plasticity.