Proceedings of the Annual Meeting of the Cognitive Science Society

The optimal perceptual decision making strategy for weighting serially presented information depends on the degreeof sample dependence. Uniform weighting produces optimal estimates from independent samples, but increases in autocorre-lation should be matched by increasing and symmetric overweighting of early and late samples in order to maintain optimalperformance.In the current experiment, participants (N = 30) observed briefly presented sequences of eight dots and were asked to estimatetheir center of mass by dragging the cursor. The autocorrelation of the series was manipulated in two distinct blocks (either 0or .7). Preliminary results show that the weight assignment to uncorrelated inputs did not differ significantly from the optimaluniform allocation. In contrast, in the high-dependence block participants used different weighting profiles - overweightingthe first and/or last samples of the sequence. This suggests that humans flexibly adapt to changes in statistical structure in thepredicted direction of optimality.