Serial dependence bias can predict the overall estimation error in visual perception

Abstract

Although visual feature estimations are accurate and precise, overall estimation errors (i.e., the difference between estimates and actual values) tend to show systematic patterns. For example, estimates of orientations are systematically biased away from horizontal and vertical orientations, showing an oblique illusion. Additionally, many recent studies have demonstrated that estimations of current visual features are systematically biased toward previously seen features, showing a serial dependence. However, no study examined whether the overall estimation errors were correlated with the serial dependence bias. To address this question, we enrolled three groups of participants to estimate orientation, motion speed, and point-light-walker direction. The results showed that the serial dependence bias explained over 20% of overall estimation errors in the three tasks, indicating that we could use the serial dependence bias to predict the overall estimation errors. The current study first demonstrated that the serial dependence bias was not independent from the overall estimation errors. This finding could inspire researchers to investigate the neural bases underlying the visual feature estimation and serial dependence.