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. 2011 Oct 7;6(10):e25339. doi: 10.1371/journal.pone.0025339

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Gilson, Fukai.

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: Resulting weight distribution for log-STDP (blue solid curve) with the saturation for LTD corresponding to in (6); mlt-STDP inspired by the model of van Rossum et al. [24] (pink solid curve) in (27); and add-STDP [1], [14] (gray dashed-dotted curve) in (26). Log-STDP and mlt-STDP are parameterized to obtain roughly the same equilibrium value for the mean weight (arrows); without noise and very slow learning, the resulting narrow distribution would be centered around the fixed point . The curves are evaluated using (1) and (5) with the same learning rate and noise level corresponding to in (3). B: Similar to A with log-scaled axes. C: Effect of the parameters in log-STDP. Comparison between the predicted weight distributions with the baseline parameters , and in (6) (medium blue curve in B) and two variants with the parameter change indicated in each plot (darker curves correspond to larger values).

Inline graphic — A: Resulting weight distribution for log-STDP (blue solid curve) with the saturation for LTD corresponding to in (6); mlt-STDP inspired by the model of van Rossum et al. [24] (pink solid curve) in (27); and add-STDP [1], [14] (gray dashed-dotted curve) in (26). Log-STDP and mlt-STDP are parameterized to obtain roughly the same equilibrium value for the mean weight (arrows); without noise and very slow learning, the resulting narrow distribution would be centered around the fixed point . The curves are evaluated using (1) and (5) with the same learning rate and noise level corresponding to in (3). B: Similar to A with log-scaled axes. C: Effect of the parameters in log-STDP. Comparison between the predicted weight distributions with the baseline parameters , and in (6) (medium blue curve in B) and two variants with the parameter change indicated in each plot (darker curves correspond to larger values).