engleski

Perceptual similarity judgments predict the precision but not the distribution of errors in working memory

Models based on population coding have been shown to provide a parsimonious account of empirical distributions of error in visual working memory (VWM) tasks. Inspired by electrophysiological observations, these models account for VWM errors based on two key properties of neural response functions, the tuning width and activity level. A new perspective on this class of models has recently been presented in the form of the Target Competition Confusability (TCC) model. 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 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. In contrast, we found strong evidence for a correlation between the variability (noisiness) of similarity judgements 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.

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