Summary: The research shows how different brain regions and neural networks contribute to a person’s problem-solving skills and general intelligence.

Source: University of Illinois

Scientists have struggled for decades to understand how brain structure and functional connectivity drive intelligence.

A new analysis provides a clearer picture of how different brain regions and neural networks contribute to a person’s ability to solve problems in different situations, a trait known as general intelligence, researchers report.

They detailed their results in the journal A map of the human brain.

The study used “connection-based predictive modeling” to compare five theories of how the brain produces intelligence, said Aaron Barbey, professor of psychology, bioengineering and neuroscience at the University of Illinois at Urbana-Champaign, who led the new work. Author Evan Anderson, now a researcher at Ball Aerospace and Technologies Corp. at the Air Force Research Laboratory.

“To understand the amazing cognitive abilities in the brain, neuroscientists look at the biological foundations of the brain,” Barbey said. “Modern theories try to explain how our ability to solve problems is helped by the brain’s information processing architecture.”

A biological understanding of these cognitive abilities “requires identifying how individual differences in reasoning and problem-solving abilities relate to the underlying architecture and neural mechanisms of brain networks,” Anderson said.

Historically, theories of intelligence have focused on localized brain regions such as the prefrontal cortex, which play a key role in cognitive processes such as planning, problem solving, and decision making. Recent theories emphasize specific brain networks, while others examine how different networks overlap and interact, Barbey said.

He and Anderson tested these established theories against their own “network neuroscience theory,” which posits that intelligence emerges from a global brain architecture, including strong and weak connections.

“Strong connections involve highly connected information processing centers that form as we learn about the world and become skilled at solving common problems,” Anderson said.

“Weak connections have fewer neural connections but enable flexibility and problem-solving.” Together, these connections “provide the network architecture necessary to solve the various problems we face in life.”

To test their hypothesis, the team recruited a population of 297 undergraduate students and first asked each participant to take a comprehensive battery of tests designed to measure problem-solving skills and adaptability in a variety of situations. These and similar tests are routinely used to measure general intelligence, Barbey said.

The researchers then collected resting-state functional MRI scans of each participant.

“One of the fascinating features of the human brain is how it involves many constellations of networks that are active even when we are at rest,” Barbey said. “These networks form the biological infrastructure of the brain and are thought to be intrinsic properties of the brain.”

These include the frontoparietal network, which activates cognitive control and goal-oriented decision-making; the posterior attention network, which supports visual and spatial perception; and the salinity network, which directs attention to the most important stimuli.

Previous studies have shown that the activity of these and other networks when a person is awake but not engaged in a task or paying attention to external events “reliably predicts our cognitive abilities and abilities,” Barbey said.

Through cognitive tests and fMRI data, the researchers were able to assess which concepts were the best predictors.

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This shows the brain

“We can systematically examine how well a theory predicts general intelligence based on the connectivity of specific brain regions or concepts,” Anderson said. “This approach allowed us to directly compare the evidence to the neuroscience predictions made by existing theories.”

The researchers found that taking into account aspects of general intelligence was the most accurate predictor of a person’s problem-solving ability and adaptability. This is true even when considering the number of brain regions included in the analysis.

This shows a picture of the brain
A biological understanding of these cognitive abilities “requires identifying how individual differences in reasoning and problem-solving abilities relate to the underlying architecture and neural mechanisms of brain networks,” Anderson said. The image is in the public domain.

The other theories also predicted intelligence, the researchers said, but the network neuroscience theory outperformed those based on specific brain regions or networks in several respects.

The findings show that “global information processing” in the brain is fundamental to how well an individual overcomes cognitive challenges, Barbey said.

“Rather than being based on a specific region or network, intelligence appears to reflect the efficiency and flexibility of global brain architecture and systemic network function,” he said.

Barbey is a professor at the Beckman Institute for Advanced Science and Technology, the Carl R. Weiss Institute for Genomic Biology, and a professor of speech and hearing sciences and a member of the neuroscience program at the U.I.

Financial support Funders include the Office of the Director of National Intelligence; Intelligence Advanced Research Projects Activity; and Department of Defense, Defense Advanced Research Projects Agency.

So Intelligence and Neuroscience Research News

Author: Diana Yates
Source: University of Illinois
Contact: Diana Yates – University of Illinois
Image: The image is in the public domain.

Preliminary study: The findings are shown in A map of the human brain

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