Network Neuroscience Theory Best Predictor of Intelligence — ScienceDaily

For decades, scientists have worked to understand how brain structure and functional connectivity drive intelligence. A new analysis provides the clearest picture of how various brain regions and neural networks contribute to a person’s problem-solving ability in a variety of contexts, the researchers report.

They detail their findings in the journal Human Brain Mapping.

Aron Barbey, professor of psychology, bioengineering and neuroscience at the University of Illinois Urbana-Champaign, said the study used “connection-based predictive modeling” to compare five theories of how the brain elicits intelligence. author Evan Anderson is a researcher at Ball Aerospace and Technologies Corp., currently working at the Air Force Research Laboratory.

“To understand the extraordinary cognitive abilities that underlie intelligence, neuroscientists look at its biological underpinnings in the brain,” said Barbey. “Modern theories attempt to explain how our problem-solving capacity is enabled by the brain’s information processing architecture.”

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

Historically, theories of intelligence have focused on localized brain regions such as the prefrontal cortex, which play an important role in cognitive processes such as planning, problem solving, and decision making. Barbey said that while newer theories highlight specific brain networks, others examine how different networks overlap and interact with each other. He and Anderson tested these established theories against their own “network neuroscience theories,” which suggest that intelligence emerges from the brain’s global architecture, including both strong and weak connections.

“Strong connections include highly connected information processing centers that are established as we learn about the world and master solving familiar problems,” Anderson said. “Weak connections have fewer neural connections, but provide flexibility and adaptive problem solving.” Together, these connections “provide the network architecture necessary to solve the various problems we face in life.”

To test their ideas, the team gathered a pool of 297 demographically diverse undergraduates and first asked each participant to pass a comprehensive set of tests designed to measure their problem-solving skills and adaptability in a variety of contexts. Barbey said this and various similar tests are routinely used to measure general intelligence.

The researchers then collected functional MRI scans of each participant at rest.

“One of the really interesting features of the human brain is how it embodies a rich network constellation that is active even at rest,” Barbey said. Said. “These networks form the biological infrastructure of the mind and are thought to be intrinsic properties of the brain.”

These include the frontoparietal network, which enables cognitive control and goal-directed decision making; dorsal attention network that aids visual and spatial awareness; and the salience network that directs attention to the most relevant stimuli. Previous research has shown that the activity of these and other networks “reliably predicts our cognitive skills and abilities” when a person is awake but not busy with a task or paying attention to outside events, Barbey said.

With cognitive tests and fMRI data, the researchers were able to assess which theories best predicted how participants performed on intelligence tests.

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

The researchers found that taking into account the characteristics of the whole brain produces the most accurate predictions about a person’s problem-solving ability and adaptability. This was true even when accounting for the number of brain regions included in the analysis.

Other theories also predict intelligence, the researchers said, but the network neuroscience theory outperformed those limited to local brain regions or networks in several respects.

Barbey said the findings reveal that “global information processing” in the brain is essential in overcoming an individual’s cognitive challenges.

“Rather than originating in a specific region or network, intelligence appears to emerge from the global architecture of the brain and reflect the efficiency and flexibility of system-wide network function,” he said.

Barbey is also a faculty member at the Beckman Institute for Advanced Science and Technology, the Carl R. Woese Institute for Genomic Biology, and a professor of speech and auditory science at the U. of I. and a member of the neuroscience program.

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

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