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by codethief 1118 days ago
* and the solution they come up with is correct more often.

The article title refers to something that's been long known even in pop science since Daniel Kahnemann's "Thinking Fast and Slow". In fact, the original paper[0] even cites Daniel Kahnemann's work:

> Simulation results indicate that decision-making speed is traded with accuracy, resembling influential theories from the fields of economy and psychology on fast and slow thinking.

Kahnemann's work might be summarized (very roughly) as follows: "System 1" often quickly suggests an intuitive (and frequently wrong) answer, whereas "System 2" is the part that does the slower, more rational, and conscious thinking. "Intelligent" people tend to be those who control their System 1 and thus their urge for intuitive answers more effectively.

And indeed this is what the article says, too:

> Resting-state functional MRI scans showed that slower solvers had higher average functional connectivity, or temporal synchrony, between their brain regions. In personalized brain simulations of the 650 participants, the researchers could determine that brains with reduced functional connectivity literally “jump to conclusions” when making decisions, rather than waiting until upstream brain regions could complete the processing steps needed to solve the problem.

> “In more challenging tasks, you have to store previous progress in working memory while you explore other solution paths and then integrate these into each other. This gathering of evidence for a particular solution may sometimes takes longer, but it also leads to better results.

However, if I understand correctly, the thing about the research here that's actually novel is that they now have a better understanding of the neural processes underlying System 1 vs. System 2 ("we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance") and that they in fact simulated the brain digitally, see my other comment.

[0]: https://doi.org/10.1038/s41467-023-38626-y