Intelligence is the ability to acquire, understand and apply knowledge and skills in order to adapt to new situations and solve problems. It is a complex trait that is influenced by both genetic and environmental factors and can manifest itself in a variety of ways, such as in reasoning, problem-solving, creativity and learning.
Researchers have been working for many years to understand the relationship between brain structure, functional connectivity, and intelligence. A recent study provides the most comprehensive understanding yet of how different regions of the brain and neural networks contribute to a person’s ability to solve problems in a variety of contexts, a trait known as general intelligence.
The researchers recently published their findings in the journal Mapping the human brain.
The research was led by Aaron Barbie, professor of psychology, bioengineering, and neuroscience at the University of Michigan University of Illinois Urbana-Champaignand first author Evan Anderson, a researcher at Ball Aerospace and Technologies Corp. who works at the Air Force Research Laboratory, used “neural network-based predictive modeling” technology to evaluate five theories about how the brain drives intelligence.
University professor Aaron Barbey, pictured, and co-author Evan Anderson, found that taking into account features of the entire brain — rather than focusing on individual regions or networks — allows for the most accurate predictions of intelligence. Credit: Fred Zwicky
“To understand the remarkable cognitive abilities that underlie intelligence, neuroscientists look to their biological underpinnings in the brain,” Barbie said. “Recent theories attempt to explain how our ability to solve problems is enabled by the structure of information processing in the brain.”
Lead study author Evan Anderson. credit: l. Brian Stauffer
Anderson said that a biological understanding of these cognitive abilities requires “a characterization of how individual differences in intelligence and problem-solving ability relate to the underlying structure and neural mechanisms of brain networks.”
Historically, theories of intelligence have focused on local brain regions such as the prefrontal cortex, which plays 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 with one another, Barbie said. He and Anderson test these well-established theories against their own “network neuroscience theory,” which posits that intelligence arises from the global structure of the brain, including its strong and weak connections.
“Strong connections involve highly information-processing hubs that are created as 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 adaptability in problem-solving.” Together, these connections provide “the necessary network architecture to solve the diverse problems we face in life.”
To test their ideas, the team recruited a demographically diverse group of 297 undergraduate students and first asked each participant to undergo a comprehensive set of tests designed to measure problem-solving skills and adaptability in different contexts. Barbie said that these various similar tests are routinely used to measure general intelligence.
The researchers then combined resting-state fMRI scans for each participant.
“One of the really interesting characteristics of the human brain is how it embodies a rich constellation of active networks even when we are at rest,” Barbie said. “These networks create the biological infrastructure of the mind and are thought to be intrinsic properties of the brain.”
These include the fronto-parietal network, which enables cognitive control and goal-directed decision-making; the dorsal attention network which aids in visual and spatial awareness; and the salient network, which directs attention to the most relevant stimuli. Barbie said 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.”
Through cognitive tests and fMRI data, the researchers were able to evaluate which theories best predicted how participants would perform on intelligence tests.
“We can investigate systematically 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 the evidence for the neuroscience predictions made by current theories.”
The researchers found that taking into account the features of the whole brain produces the most accurate predictions of a person’s ability to solve problems and their ability to adapt. This was true even when calculating the number of brain regions included in the analysis.
Other theories were also predictive of intelligence, the researchers said, but the network neuroscience theory outperformed that limited to local brain regions or networks in a number of respects.
Barbie said the findings reveal that “global information processing” in the brain is central to how an individual overcomes cognitive challenges.
“Rather than arising from a particular region or network, intelligence appears to emerge from the global architecture of the brain and reflects the efficiency and flexibility of network function at the system level,” he said.
Reference: “Investigating Cognitive Neuroscience Theories of Human Intelligence: A Neural Network-Based Predictive Modeling Approach” by Evan D. Anderson and Aaron K. Barbie, Dec. 20, 2022, Available here. Mapping the human brain.
DOI: 10.1002/hour per minute 26,164
The study was funded by the Office of the Director of National Intelligence, the Intelligence Advanced Research Projects Activity, and the Department of Defense, the Defense Advanced Research Projects Activity.