Figure 3.

Contrasting forces in serial dependence. (A) Serial dependence is typically positive when the difference between the previous and present stimulus is small and slightly negative when the difference is large (Δ, here indicating the difference in orientation between the previous and present stimulus, data are from 48 subjects performing an orientation adjustment task with low spatial frequency Gabors; Ceylan et al., 2021). (B) The coexistence of these two opposite biases can be modeled as the additive effect of a weighting function narrowly tuned toward the recent past (the green distribution) and one more broadly tuned away (the brown negative distribution). If observers weigh the previous stimulus according to the two distributions, the resulting pattern resembles A. (C) Interindividual variability in the dominance of the positive and negative components of serial dependence. Typically, the positive bias dominates; some subjects, however, show no bias or only negative serial dependence. (D) Two curves with a difference of Gaussian fit depicting the pattern for the top five observers showing positive serial dependence (green, corresponding to the green square in C) and the top five observers showing only negative biases (brown, corresponding to the brown square in C). The proportion of subjects showing positive serial dependence in this data set is 70% with an effect size of d′ = 0.63 (Cohen's d).