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A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Fig 6

Fitting an extended integration-to-bound (“Extended ITB”) model to data demonstrates that integration dynamics (negative α for confirmation bias, positive α for forgetting), rather than a bound, best accounts for data.

a) Illustration of Extended ITB model. As in classic drift-diffusion models with an absorbing bound, evidence is integrated to an internal bound, after which new evidence is ignored. Compared to perfect integration (α = 0), a positive leak (α > 0) decays information away and results in a recency bias, and a negative leak (α < 0) amplifies already integrated information, resulting in a primacy bias. Since α < 0 may also result in more bound crossings, both leak and bound together determine the shape of the temporal weights. b) Inferred values of the bound and leak parameters in each condition, shown as median±68% credible intervals. The classic ITB explanation of primacy effects corresponds to a non-negative leak and a small bound—illustrated here as a shaded green area. Note that the three observers near the ITB regime are points from the HSLC task—two still exhibit mild recency effects and one exhibits a mild primacy effect as predicted by ITB. c) Across both conditions, the temporal slopes (β) implied by the full model fits closely match the slopes in the data. β < 0 corresponds to primacy, and β > 0 to recency. Error bars indicate 68% confidence intervals from bootstrapping trials on βdata and from posterior samples on βfit. d) Median temporal biases implied by the full model (middle) and by the model with either zero leak (left) or infinite bound (right). Each line corresponds to a single observer. (LSHC condition only—HSLC condition in Fig L in S1 Text). d) Across the population, the negative leak (confirmation bias) accounted for 99% (68%CI = [93%, 106%]), and bounded integration accounted for 18% (68%CI = [13%, 23%]) of the primacy bias captured by the model. (Additional analyses in Fig L in S1 Text).

Fig 6

doi: https://doi.org/10.1371/journal.pcbi.1009517.g006