Modern neuroscience often describes the brain as a collection of specialized systems. Functions such as attention, perception, memory, language, and reasoning have each been linked to specific brain networks, and scientists have typically studied these systems separately.
This approach has produced major breakthroughs. However, it has not fully explained a central feature of human thinking: how all these separate systems come together to form a single, unified mind.
Researchers at the University of Notre Dame set out to address that question. Using advanced neuroimaging, they examined how the brain is organized overall and how that organization gives rise to intelligence.
“Neuroscience has been very successful at explaining what particular networks do, but much less successful at explaining how a single, coherent mind emerges from their interaction,” said Aron Barbey, the Andrew J. McKenna Family Professor of Psychology in Notre Dame’s Department of Psychology.
General Intelligence and Connected Cognitive Abilities
Psychologists have long observed that skills like attention, memory, perception, and language tend to be linked. People who perform well in one area often perform well in others. This pattern is known as “general intelligence.” It influences how effectively individuals learn, solve problems, and adapt across academic, professional, social, and health settings.
For more than a century, this pattern has suggested that human cognition is unified at a deep level. What scientists have lacked is a clear explanation for why that unity exists.
“The problem of intelligence is not one of functional localization,” said Barbey, who also directs the Notre Dame Human Neuroimaging Center and the Decision Neuroscience Laboratory. “Contemporary research often asks where general intelligence originates in the brain — focusing primarily on a specific network of regions within the frontal and parietal cortex. But the more fundamental question is how intelligence emerges from the principles that govern global brain function — how distributed networks communicate and collectively process information.”
To explore this broader perspective, Barbey and his team, including lead author and Notre Dame graduate student Ramsey Wilcox, tested a framework known as the Network Neuroscience Theory. Their findings were published in Nature Communications.
The Network Neuroscience Theory Explained
According to the researchers, general intelligence is not a specific ability or mental strategy. Instead, it reflects a pattern in which many cognitive skills are positively related. They propose that this pattern stems from how efficiently the brain’s networks are structured and how well they work together.
To evaluate this idea, the team analyzed brain imaging and cognitive performance data from 831 adults in the Human Connectome Project. They also examined an independent group of 145 adults in the INSIGHT Study, funded by the Intelligence Advanced Research Projects Activity’s SHARP program. By combining measures of brain structure and brain function, the researchers created a detailed picture of large-scale brain organization.
Rather than tying intelligence to a single brain region or function, the Network Neuroscience Theory views it as a property of the brain as a whole. Intelligence, in this framework, depends on how effectively networks coordinate and reorganize themselves to handle different challenges.
Barbey and Wilcox describe this as a major shift in perspective.
“We found evidence for system-wide coordination in the brain that is both robust and adaptable,” Wilcox said. “This coordination does not carry out cognition itself, but determines the range of cognitive operations the system can support.”
“Within this framework, the brain is modeled as a network whose behavior is constrained by global properties such as efficiency, flexibility and integration,” Wilcox said. “These properties are not tied to individual tasks or brain networks, but are characteristics of the system as a whole, shaping every cognitive operation without being reducible to any one of them.”
“Once the question shifts from where intelligence is to how the system is organized,” Wilcox noted, “the empirical targets change.”
Intelligence as Whole Brain Coordination
The findings supported four main predictions of the Network Neuroscience Theory.
First, intelligence does not reside in a single network. It arises from processing distributed across many networks. The brain must divide tasks among specialized systems and combine their outputs when necessary.
Second, successful coordination requires strong integration and long-distance communication. Barbey described “a large and complex system of connections that serve as ‘shortcuts’ linking distant brain regions and integrating information across the networks.” These connections allow far apart areas of the brain to exchange information efficiently, supporting unified processing.
Third, integration depends on regulatory regions that guide how information flows. These hubs help orchestrate activity across networks, selecting the right systems for the job. Whether someone is interpreting subtle clues, learning a new skill, or deciding between careful analysis and quick intuition, these regulatory areas help manage the process.
Finally, general intelligence depends on balancing local specialization with global integration. The brain performs best when tightly connected local clusters operate efficiently while still maintaining short communication paths to distant regions. This balance supports flexible and effective problem solving.
Across both groups studied, differences in general intelligence consistently matched these large-scale organizational features. No single brain area or traditional “intelligence network” explained the results.
“General intelligence becomes visible when cognition is coordinated,” Barbey noted, “when many processes must work together under system-level constraints.”
Implications for Artificial Intelligence and Brain Development
The implications extend beyond understanding human intelligence. By focusing on large-scale brain organization, the findings offer insight into why the mind functions as a unified system in the first place.
This perspective may also explain why intelligence tends to increase during childhood, decline with aging, and be especially vulnerable to widespread brain injury. In each situation, what changes most is large-scale coordination rather than isolated functions.
The results also contribute to debates about artificial intelligence. If human intelligence depends on system-level organization rather than a single general-purpose mechanism, then building artificial general intelligence may require more than simply scaling up specialized tools.
“This research can push us into thinking about how to use design characteristics of the human brain to motivate advances in human-centered, biologically inspired artificial intelligence,” Barbey said.
“Many AI systems can perform specific tasks very well, but they still struggle to apply what they know across different situations.” Barbey said. “Human intelligence is defined by this flexibility — and it reflects the unique organization of the human brain.”
The research was conducted with co-authors Babak Hemmatian and Lav Varshney of Stony Brook University.
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