How Working Memory Provides Representational Change During Insight Problem Solving

Abstract

Numerous studies of insight problem solving are focused on both the control and storage systems of working memory. We obtained contradictory data about how working memory systems are involved in insight problem solving process. We argue that measuring the dynamics of the control system and storage systems through the course of problem solving can provide a more refined view on the processes involved, as a whole, and explain the existing controversies. We theorize that specific insight mechanisms require varying working memory capacities at different stages of the problem solving process. Our study employed a dual task paradigm to track the dynamics of working memory systems load during problem solving by measuring the reaction time in a secondary probe-task during different stages of problem solving. We varied the modality (verbal, visual) and the complexity of the probe-task during insight and non-insight problem solving. The results indicated that the dynamics of working memory load in insight problems differs from those in non-insight problems. Our first experiment shows that the complexity of the probe-task affects overall probe-task reaction times in both insight and non-insight problem solving. Our second experiment demonstrates that the solution of a non-insight problem is primarily associated with the working memory control system, while insight problems rely on relevant storage systems. Our results confirm that insight process requires access to various systems of working memory throughout the solution. We found that working memory load in non-insight problems increases from stage to stage due to allocation of the attentional control resources to interim calculations. The nature of the dynamics of working memory load in insight problems remains debatable. We claim that insight problem solving demands working memory storage during the entire problem solving process and that control system plays an important role just prior to the solution.

Aha! under pressure: Is the Aha! experience constrained by cognitive load

“…Given the lack of previous studies using a dual-task paradigm with the CRAT to study insight and using generalized linear mixed models analyses, we used the average effect size found in previous dual-task studies on insight to make a well-informed estimate of our required sample size. In previous dual-task studies, an average cohen's d effect size has been reported of .68 for solution time on the secondary task and .62 for the number of correctly solved problems as a function of solution type and working memory load (Korovkin et al, 2018;Lavric et al, 2000). Regarding solution accuracy and solution confidence, we could not extract cohen's d effect sizes due to a lack of previous data.…”

“…Recent insight theorists (Bowden & Grunewald, 2018;Weisberg, 2015) have argued that each solution type involves both processes (Type 1 and 2) to some extent. Therefore, implementing a more demanding WM load may unravel if both solution types can be affected by WM load, albeit to a different extent (insight potentially less than non-insight; see Korovkin et al, 2018, for an example).…”

Without insight accompanied with deteriorated brain functional alterations in healthy individuals with auditory verbal hallucinations: a pilot study

“…Compared to the Hi-AVH group with insight, the Hi-AVH group without insight showed greater disturbance within these networks, and also within components of mood regulation circuitry. Previous studies have reported that functional alterations in these circuits are not only related to AVH but also to insight (Webb et al 2016 ; Korovkin et al 2018 ; Hill and Kemp 2018 ; Belvederi Murri et al 2016 ; Tik et al 2018 ; Sapara et al 2016 ).…”

Working Memory Capacity and Mathematics Anxiety of Mathematics Undergraduate Students and Its Effect on Mathematics Achievement

“…Frisco, Sanne, Kroesbergen, & Johannes (2013) conducted a research in elementary school and found that all components of working memory were related to mathematical performance, especially verbal updating. Korovkin (2018) investigated the dynamics of working memory systems during problem solving. He stated that the functioning memory storage was needed when solving a problem and just before finding the solution the control system played an important role.…”