Summary: A study reveals how various brain regions and neural networks contribute to a person’s problem-solving abilities and general intelligence.
Source: University of Illinois
Scientists have worked for decades to understand how brain structure and functional connectivity fuel intelligence.
A new analysis offers the clearest picture yet of how various brain regions and neural networks contribute to a person’s problem-solving ability in various contexts, a trait known as general intelligence. , report the researchers.
They detail their findings in the journal Mapping of the human brain.
The study used “connectome-based predictive modeling” to compare five theories about how the brain gives rise to intelligence, said Aron Barbey, professor of psychology, bioengineering and neuroscience at the University of Illinois at Urbana-Champaign who led the new work with first author Evan Anderson, now a researcher for Ball Aerospace and Technologies Corp. working at the Air Force Research Laboratory.
“To understand the remarkable cognitive abilities that underlie intelligence, neuroscientists are turning to their biological underpinnings in the brain,” Barbey said. “Modern theories attempt to explain how our ability to solve problems is activated by the information processing architecture of the brain.”
A biological understanding of these cognitive abilities requires “characterizing how individual differences in intelligence and problem-solving ability relate to the underlying architecture and neural mechanisms of brain networks,” Anderson said.
Historically, intelligence theories have focused on localized brain regions such as the prefrontal cortex, which plays a key role in cognitive processes such as planning, problem solving, and decision making. Newer theories focus on specific brain networks, while others look at how different networks overlap and interact with each other, Barbey said.
He and Anderson tested these established theories against their own “network neuroscience theory,” which posits that intelligence emerges from the brain’s overall architecture, including strong and weak connections.
“Strong connections involve highly connected information processing centers that are established when we learn about the world and become adept at solving familiar problems,” Anderson said.
“Weak connections have fewer neural connections but allow for flexibility and adaptive problem solving.” Together, these connections “provide the network architecture needed to solve the various problems we encounter in life.”
To test their ideas, the team recruited a demographically diverse group of 297 undergraduate students, first asking each participant to undergo a comprehensive battery of tests designed to measure problem-solving skills and adaptability in various contexts. These and similar tests are commonly used to measure general intelligence, Barbey said.
The researchers then collected resting-state functional MRIs from each participant.
“One of the really interesting properties of the human brain is how it embodies a rich constellation of networks that are active even when we’re at rest,” Barbey said. “These networks create the biological infrastructure of the mind and are considered intrinsic properties of the brain.”
These include the fronto-parietal network, which enables cognitive control and goal-oriented decision-making; the dorsal attention network, which aids in visual and spatial awareness; and the salience network, which directs attention to the most relevant 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 not paying attention to external events “reliably predicts our cognitive skills and abilities. “, Barbey said.
With cognitive testing and fMRI data, researchers were able to assess which theories best predicted participants’ performance on intelligence tests.
“We can systematically study how well a theory predicts general intelligence based on the connectivity of brain regions or networks that the theory involves,” Anderson said. “This approach allowed us to directly compare evidence to neuroscientific predictions made by current theories.”
The researchers found that considering whole-brain characteristics yielded the most accurate predictions of a person’s problem-solving ability and adaptability. This was found to be true even when taking into account the number of brain regions included in the analysis.
The other theories were also predictive of intelligence, the researchers said, but the network neuroscience theory outperformed those limited to localized brain regions or networks in several respects.
The findings reveal that “global information processing” in the brain is fundamental to an individual’s ability to overcome cognitive challenges, Barbey said.
“Rather than arising from a specific region or network, intelligence appears to emerge from the overall architecture of the brain and reflect the efficiency and flexibility of system-wide network function,” said he declared.
Barbey is also a faculty member of the Beckman Institute for Advanced Science and Technology, the Carl R. Woese Institute for Genomic Biology, and Professor of Speech and Hearing Sciences and a member of the Neuroscience Program at U. of I.
Funding: Donors include the Office of the Director of National Intelligence; the Advanced Intelligence Research Projects activity; and the Department of Defense, Defense Advanced Research Projects Activity.
About this intelligence and neuroscience research news
Author: Diana Yates
Source: University of Illinois
Contact: Diana Yates – University of Illinois
Image: Image is in public domain
Original research: The findings will appear in Mapping of the human brain