Direct precision manipulations of mental representations in visual working memory drive serial dependence

Our behavior is heavily influenced by previous information. Work in the field of serial dependence has investigated how the combination of past and present information affects perception and cognition. These studies revealed strong attractive biases towards previously seen stimuli, especially when stimuli are uncertain. Here, for the first time we directly manipulated the uncertainty of mental presentations instead of the uncertainty in the stimulus, through an intermediate task that observers conducted during the retention interval. Participants were presented with differently oriented Gabors and had to reproduce their orientation. While memorizing the orientation, they judged whether two stimuli were identical. This intermediate task varied in the type of stimuli observers were presented with: They compared the size of circles (that contain no orientation information), the length of differently oriented lines or the orientation of lines, and a control condition was added with no intermediate task. These manipulations allowed for a detailed assessment of the role of load and inter-item competition in memory on the precision of the encoded Gabor and subsequently, on the strength of serial dependence. In line with the variable-precision model the mere presence of an intermediate task decreased the precision of the memorized Gabor orientation, enhancing the attractive bias towards past information. Inter-item similarity between the memorized Gabor and the stimuli from the inter-item task further influenced serial dependence: If the intermediate task also required the memorization of orientation, serial dependence was even stronger than for stimuli that contained no orientation information. These results provide novel evidence of the role of working memory on serial dependence. As the precision of individual representations in memory degrades, a greater weight is placed on previous information to make the correct inferences. Moreover, inter-item similarity also leads to a decrease in precision and as a result to an increase in serial dependence.