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On the Origins of Suboptimality in Human Probabilistic Inference

Figure 4

Response slopes for the training session.

Response slope as a function of the SD of the Gaussian prior distribution, , plotted respectively for trials with low noise (‘short’ cues, red line) and high noise (‘long’ cues, blue line). The response slope is equivalent to the linear weight assigned to the position of the cue (Eq. 1). Dashed lines represent the Bayes optimal strategy given the generative model of the task in the two noise conditions. Top: Slopes for a representative subject in the training session (slope SE). Bottom: Average slopes across all subjects in the training session (, mean SE across subjects).

Figure 4

doi: https://doi.org/10.1371/journal.pcbi.1003661.g004