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We address these aims by (a) modeling an example of insight problem solving and comparing it to empirical data, and (b) testing the model on a robot platform.
In this article, we discuss in detail the methodological challenges that brain research on insight poses and describe how we dealt with these challenges in our recent studies on insight problem solving.
To address this issue, we tested healthy young and old volunteers on an insight problem solving task, involving both explicit and implicit features, before and after a night of sleep or a comparable wakefulness period.
Importantly, the kind of insight problem solving paradigm we used (and, arguably, any insight problem solving) involves several neural networks.
We have proposed elsewhere that insight problem solving may require heuristic search by natural selection [52].
All of these participants were naïve to tDCS and had no prior experience with the matchstick insight problem solving task.
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Our intuitive understanding of this insight phenomenon or insightful problem solving seems to be quite distinct, but psychologists have not yet agreed upon a single definition of insight [4], [5], [6], [7], [8], [9], [10].
Yet in an authoritative review of the research, the psychologists Jonathan W. Schooler and Joseph Melcher concluded that the abilities most strongly correlated with insight problem-solving "were not significantly correlated" with solving analytical problems.
According to the latest study of mental capability, movement will guide insight in problem solving situations.
Overall, present findings demonstrate that a period of sleep does not significantly promote insight in problem solving in older adults.
Work through actual problems in order to share insight and problem solving strategies.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com