Beyond Quick Thinking: Why Are Very Intelligent People Slower at Solving Complex Problems?

Intelligence tests show an interesting pattern when it comes to response time and accuracy. People who score high on these tests tend to respond quickly to simple questions, while their less intelligent counterparts lag behind. However, a different dynamic emerges as questions become more complex, writes IFLScience.

People with high intelligence are more likely to answer correctly, although they are not in a hurry. These findings defy conventional wisdom and may require changes in testing procedures. Additionally, these discoveries are supported by the use of brain network models (MMNs) that accurately reproduce people’s neural connections.

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Traditionally, the link between intelligence and quick thinking is generally accepted and supported by numerous studies. However, it is possible that these studies did not cover a sufficiently wide range of indicators.

Professor Petra Ritter of the Berlin Institute of Health der Charité is actively working to develop simulations that accurately mimic the characteristics of the individual human brain. To do this, Ritter and colleagues used data from the Human Connectome Project, which included 1,176 participants.

By observing patterns of activation of brain connections using functional magnetic resonance imaging (fMRI), both in the exercise state and at rest, they pursued the goal of creating a human brain that accurately reproduces (MMS).

The tests performed in the study involved presenting participants with a series of patterns and asking them to identify the rules that underlie them. The difficulty level increased gradually, starting with easy tasks and moving on to more difficult ones. Participants’ IQs were measured using conventional tests, and Ritter activation models explored the relationship between measured IQs and test scores.

According to Ritter, “it is the right excitation-inhibition balance of neurons that influences decision making and allows a person to more or less solve problems.”

Participants who exhibited higher intelligence and better brain synchronization were able to find solutions to simpler problems faster. But when the complexity of the tasks increased, their advantage was patience. They avoided making hasty decisions, giving all parts of the brain ample time to complete the necessary processing before coming to a conclusion.

The less synchronized brain tended to jump to conclusions, while the front circuits in the more synchronized brain held back. They avoided making decisions until the entire brain had completed the necessary processing. These results were confirmed by more detailed observations of a subgroup of 650 participants.

Prof Michael Schirner, lead author of the study, explained: “For complex problems, you need to store the preliminary progress in working memory as you explore other solutions and then integrate them together. This collection of evidence for a particular solution can sometimes take longer, but also leads to better results.

Ritter successfully reproduced these features of the human brain in artificial MMCs. “During the study, we found that this artificial brain behaved differently, but in the same way as its biological counterparts,” adds Ritter.

The researchers’ ultimate goal is to use these artificial brain simulations to identify targeted interventions on a case-by-case basis for people suffering from neurodegenerative diseases.

Previously Focus He wrote about a breakthrough in Alzheimer’s research: dogs’ sleep reveals the secret to recovery.

Important! This article is based on and does not contradict the latest scientific and medical research. The text is for informational purposes only and does not contain medical advice. Be sure to see a doctor for a diagnosis.