Assessing the evidence for a cue-induced trade-off between capacity and precision in visual working memory using mixture modelling and Bayesian model comparison

Abstract

There is considerable debate regarding the ability to trade mnemonic precision for capacity in working memory (WM), with some studies reporting evidence consistent with such a trade-off and others suggesting it may not be possible. The majority of studies addressing this question have utilized a standard approach to analyzing continuous recall data in which individual-subject data from each experimental condition is fitted with a probabilistic model of choice. Estimated parameter values related to different aspects of WM (e.g., the capacity and precision of stored items) are then compared using statistical tests to determine the presence of hypothesized differences between experimental conditions. However, recent research has suggested that the standard approach is flawed in several respects. In this study, we adapted the methods of Roggeman et al. (2014) and analyzed the data using the standard analytical approach and a more rigorous Bayesian model comparison (BMC) approach. The second approach involved generating a set of probabilistic models whose priors reflect different hypotheses regarding the effect of our key experimental manipulations on behavior. Our results demonstrate that these two approaches can produce notably different results. More specifically, the standard analysis revealed that a high- versus a low-load cue resulted in higher capacity and lower precision parameter estimates, suggesting the presence of a trade-off between capacity and precision. However, the more rigorous BMC analysis revealed that it was very unlikely that participants employed a behavioral strategy in which they sacrificed mnemonic precision to achieve higher storage capacity. In light of these differences, we advocate for a more stringent approach to model selection and hypothesis testing in studies implementing mixture modeling.

Working memory capacity affects trade-off between quality and quantity only when stimulus exposure duration is sufficient: Evidence for the two-phase model

“…In the present study, we not only reported the results of the population level analysis on the memory precision and number index respectively as previous studies 21,23,25,26,28 , but also the results of the individual level analysis by merging precision and number index. The population level analysis for the precision index did not reach significance in a between-experiment analysis (i.e., the three-way interaction of precision condition × capacity group × experiment on the precision index).…”

“…In previous studies about the voluntary trade-off between VWM precision and number, many studies supported the voluntary trade-off used the orientation as the stimulus 19–26 , but most of the studies using colour materials failed to find evidence that participants could trade off voluntarily 22,23,25 . Therefore, one might think that the stimulus property (orientation vs colour) might be the determining factor for the patterns of the results.…”

“…It is worth noting that although there have been many studies on trade-off using a mixture model (or other models) fitting 21,23,25,26,28 , according to our knowledge, all of them analysed the precision and number index respectively. In the present study, we used GT as a measure to merge the precision and number index to quantify the magnitude of voluntary trade-off.…”

“…26 Experiment 118RecallColour51200 ms240 ms/itemYesYesSupplementary experiment18RecallColour5200 ms40 ms/itemYesNoExperiment 218RecallColour51200 ms240 ms/itemYesYesBocincova et al . 25 60RecallColour2, 4150 ms37.5–75 ms/itemNoYesYe et al . 21 Experiment 147RecallOrientation4200 ms50 ms/itemNoYesExperiment 250RecallOrientation2200 ms100 ms/itemYesYesExperiment 347RecallOrientation4500 ms125 ms/itemYesYesRamaty and Luria 28 Experiment 120RecallColour51200 ms240 ms/itemYesYesExperiment 220RecallColour5300 ms60 ms/itemNoYesExperiment 320RecallColour51200 ms240 ms/itemNoNo…”

Visual Working Memory Cannot Trade Quantity for Quality

“…In the third experiment, monetary rewards were provided, encouraging participants to reduce precision and to encode more items in WM. Interestingly, all three experiments failed to observe a trade-off between quantity and quality ( Bocincova et al, 2016 ), and Zhang and Luck argued that these results support the slots theory of WM capacity allocation. However, the failure to find a trade-off could also be interpreted as indicating a weak manipulation power.…”