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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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To estimate the effect of stimuli administered in previous trials on decision in a trial, we fitted a linear non-linear model that relates the outcome of each trial to a linear combination of present and past stimuli (Eq. 1). The parameters that minimize the square error between the prediction of the model and participants' responses are presented. Green - , Dark blue - , Black - . Error bars are 68% confidence intervals (equivalent to one standard deviation in a normal distribution) and we assumed that , which means that the model had 9 free parameters ( and ), and was fitted using 16,380 trials (65 trials in 252 blocks).

Inline graphic — To estimate the effect of stimuli administered in previous trials on decision in a trial, we fitted a linear non-linear model that relates the outcome of each trial to a linear combination of present and past stimuli (Eq. 1). The parameters that minimize the square error between the prediction of the model and participants' responses are presented. Green - , Dark blue - , Black - . Error bars are 68% confidence intervals (equivalent to one standard deviation in a normal distribution) and we assumed that , which means that the model had 9 free parameters ( and ), and was fitted using 16,380 trials (65 trials in 252 blocks).