Abstract
Models based on population coding have provided a parsimonious account of empirical distributions of error in visual working memory (VWM) tasks. Inspired by electrophysiological observations of sensory neurons, these models account for VWM errors and the effects of set size based on two key properties of neural response functions, the tuning width and activity level, which can be directly related to variables of signal detection theory, including d-prime. A new perspective on this class of models has recently been presented in the form of the Target Competition Confusability (TCC) model (Schurgin et al., Nat Hum Behav, 2020). The core claim of TCC is that the distribution of recall errors on e.g. a colour wheel, can be accounted for by the perceptual similarity of values in that feature space, i.e. the perceptual similarity function takes on an equivalent role to population tuning, obviating the need to fit a tuning width parameter to the recall data. Here we set out to verify this claim by testing the correspondence between population coding and TCC components that predict the shape of VWM error distributions. Using four different visual feature spaces, we measured psychophysical similarity and working memory errors in the same participants. The results revealed no consistent relationship between perceptual similarity functions and VWM error distributions at individual or group levels. In contrast, we found strong evidence for a correlation between the variability of similarity judgements in the perceptual task and the activity level (signal-to-noise) in the population coding model fit to VWM errors. Our results suggest that perceptual similarity functions are not predictive of VWM errors, but that a common source of variability affects perceptual difference judgements and recall from VWM, perhaps related to broader cognitive ability.