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. 2012 Oct 25;8(10):e1002731. doi: 10.1371/journal.pcbi.1002731

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© 2012 Raviv 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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The parameters of the implicit memory model, the standard deviation of the noise, and the memory weight, were estimated for each of our experimental blocks to minimize the square error between the model and the observed behavior. These parameters were used to simulate the behavior of an implicit-memory participant in that block. The results of the simulation are presented in A and B, (same presentation as in Fig. 2A and 2B , respectively). Note the similarity between Figs. 4A and 2A and between Figs. 4B and 2B , indicating that the implicit-memory model can account for the contraction bias. C, Estimation of the recency effect in the implicit memory model. Same analysis as in Fig. 3 .

Inline graphic — The parameters of the implicit memory model, the standard deviation of the noise, and the memory weight, were estimated for each of our experimental blocks to minimize the square error between the model and the observed behavior. These parameters were used to simulate the behavior of an implicit-memory participant in that block. The results of the simulation are presented in A and B, (same presentation as in Fig. 2A and 2B , respectively). Note the similarity between Figs. 4A and 2A and between Figs. 4B and 2B , indicating that the implicit-memory model can account for the contraction bias. C, Estimation of the recency effect in the implicit memory model. Same analysis as in Fig. 3 .