Researchers have worked for years to understand the relationship between brain structure, functional connectivity and intelligence. A recent study provides the most comprehensive understanding to date of how different brain regions and neural networks contribute to a person’s problem-solving ability in different contexts, a trait known as general intelligence.
The researchers recently published their findings in the journal Mapping human brains.
The research, led by Aron Barbey, a professor of psychology, bioengineering and neuroscience at the University of Illinois Urbana-Champaign, and first author Evan Anderson, a researcher for Ball Aerospace and Technologies Corp. the technique of “connectome-based predictive modeling” to evaluate five theories of how the brain leads to intelligence.
“To understand the remarkable cognitive abilities that underlie intelligence, neuroscientists look at their biological basis in the brain,” Barbey said. “Modern theories try to explain how our ability to solve problems is enabled by the information processing architecture of the brain.”
A biological understanding of these cognitive abilities requires “characterization of 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. More recent theories emphasize specific brain networks, while others explore 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 stems from the brain’s global architecture, including both strong and weak connections.
“Strong connections refer to highly connected hubs of information processing that emerge as we learn about the world and become adept at solving familiar problems,” Anderson said. “Weak connections have fewer neural links, but allow for flexibility and adaptive problem solving.” Together, these connections form “the network architecture necessary to solve the diverse problems we encounter in life.”
To test their ideas, the team recruited a demographically diverse pool of 297 undergraduate students, requiring each participant to first undergo a comprehensive battery of tests designed to measure problem-solving skills and adaptability in a variety of contexts. These and similar miscellaneous tests are routinely used to measure general intelligence, Barbey said.
The researchers then collected resting functional MRI scans 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 frontoparietal network, which facilitates cognitive control and goal-directed decision-making; the dorsal attentional network, which aids in visual and spatial awareness; and the salience network, which focuses attention on 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 paying attention to external events “reliably predicts our cognitive skills and abilities,” Barbey said.
The cognitive tests and fMRI data allowed the researchers to evaluate which theories best predicted how participants performed on the intelligence tests.
“We can systematically examine how well a theory predicts general intelligence based on the connectivity of brain regions or networks that the theory entails,” Anderson said. “This approach allowed us to directly compare evidence for the neuroscientific predictions of current theories.”
The researchers found that taking into account the characteristics of the whole brain yielded the most accurate predictions of a person’s problem-solving and adaptive abilities. This was 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 a number of ways.
The findings reveal that “global information processing” in the brain is fundamental to how well an individual overcomes cognitive challenges, Barbey said.
“Rather than emanating from a specific region or network, intelligence appears to emerge from the brain’s global architecture and reflect the efficiency and flexibility of system-wide network functions,” he said.
Reference: “Exploring Cognitive Neuroscientific Theories of Human Intelligence: A Connectome-Based Predictive Modeling Approach” By Evan D. Anderson and Aron K. Barbey, December 20, 2022, Mapping human brains.
The study was funded by the Office of the Director of National Intelligence, the Intelligence Advanced Research Projects Activity and the Department of Defense, Defense Advanced Research Projects Activity.