A new analysis published today provides the most comprehensive understanding to date of how different brain regions and neural networks contribute to a person’s problem-solving abilities across various contexts, a trait known as general intelligence.
Decades of research have been devoted to determining how brain anatomy and functional connections influence intelligence. Researchers say that a new analysis gives the clearest picture yet of how different parts of the brain and neural networks contribute to a person’s general intelligence, or ability to solve problems in different situations.
They published an in-depth analysis of their results in the peer-reviewed journal Human Brain Mapping.
Aron Barbey, a professor of psychology, bioengineering, and neuroscience at the University of Illinois Urbana-Champaign who led the new work with Evan Anderson, a scientist for Ball Aerospace and Technologies Corp. working at the Air Force Research Laboratory, said that the study used “connectome-based predictive modeling” to evaluate five theories about how the brain gives rise to intelligence.
“To understand the remarkable cognitive abilities that underlie intelligence, neuroscientists look to their biological foundations in the brain,” Barbey adds. “Modern theories attempt to explain how our capacity for problem-solving is enabled by the brain’s information-processing architecture.”
According to Anderson, defining how individual variations in intelligence and problem-solving ability connect to the underlying architecture and neural processes of brain networks is necessary for a scientific explanation of these cognitive abilities.
Theories of intelligence have historically concentrated on specific areas of the brain, such as the prefrontal cortex, which is important for cognitive functions including planning, problem-solving, and decision-making. According to Barbey, more recent theories focus more on certain brain networks, while others look at how diverse networks interact and overlap. He and Anderson compared their own “network neuroscience theory,” which maintains that intelligence originates from the whole structure of the brain, including both strong and weak connections, to these well-established hypotheses.
“Strong connections involve highly connected hubs of information-processing that are established when we learn about the world and become adept at solving familiar problems,” explains Anderson. “Weak connections have fewer neural linkages but enable flexibility and adaptive problem-solving.”
All these links create the network architecture that is essential for tackling the many difficulties we experience in life, according to the author.
The researchers put their hypotheses to the test on a sample of 297 undergraduates from a wide range of demographics by having them take a battery of tests meant to gauge their problem-solving and general adaptability. According to Barbey, these and other equally varied tests are often used to gauge a person’s IQ.
After that, the researchers obtained functional MRI scans of each subject when they were in a resting condition.
“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 are at rest,” Barbey adds. “These networks create the biological infrastructure of the mind and are thought to be intrinsic properties of the brain.”
The frontoparietal network is responsible for executive functions including attention and goal-directed decision-making; the dorsal attention network helps with visual and spatial awareness, and the salience network helps focus on what’s most important. The activity of these and other networks, while a person is awake but not focused on a task or paying attention to outside events, has already been demonstrated to “reliably predict our cognitive skills and abilities,” according to Barbey.
The fMRI data and cognitive tests helped the researchers determine which hypotheses were most predictive of individuals’ scores on the IQ tests.
“We can systematically investigate how well a theory predicts general intelligence based on the connectivity of brain regions or networks that theory entails,” Anderson adds. “This approach allowed us to directly compare evidence for the neuroscience predictions made by current theories.”
The researchers discovered that considering the characteristics of the entire brain led to the most accurate predictions of a person’s problem-solving ability and adaptability. This was true even when accounting for the number of brain regions included in the analysis.
The researchers found that the other theories were also able to predict intelligence to some degree, but the network neuroscience theory outperformed those that focused on specific brain regions or networks in several ways.
According to Barbey, the results demonstrate the importance of “global information processing” in the brain when it comes to a person’s ability to solve cognitive problems.
“Rather than originate from a specific region or network, intelligence appears to emerge from the global architecture of the brain and to reflect the efficiency and flexibility of systemwide network function,” he adds.
Source: 10.1002/hbm.26164
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