Making sense of discrepancies in working memory training experiments: a Monte Carlo simulation

INTRODUCTION The idea that working memory training can enhance general cognitive abilities has received a lot of attention in the last few years. Some studies have demonstrated far transfer to other cognitive abilities after training, whereas others have failed to replicate these findings (see Melby-Lervåg and Hulme, 2013, for a meta-analytic review). These setbacks have had unfortunate effects on the field of cognitive training, sometimes raising concerns regarding methodology and analyses in concurrent labs. Although constructive skepticism is often healthy in fields based on peer-review, the current dynamic has created a climate of hostility detrimental to the advancement of science. In this paper, I show that some of these differences can simply emerge from population parameters underlying cognitive growth curves. Based on a Monte Carlo simulation, I demonstrate that unbalanced samples are bound to arise by chance when individuals differ in their ability to learn, and propose a few remedies to circumvent this problem. Finally, I discuss the impact of cognitive training studies in refining theories of cognition and suggest directions for future research.