Modern neuroscience often describes the brain as a collection of specialized systems, each responsible for functions such as attention, perception, memory, language, and reasoning. Traditionally, scientists have studied these systems separately, leading to significant breakthroughs. However, this approach has not fully explained a central feature of human thinking: how these separate systems come together to form a unified mind.
Researchers at the University of Notre Dame have set out to address this 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 at Notre Dame.
General Intelligence and Connected Cognitive Abilities
Psychologists have long observed that skills like attention, memory, perception, and language are often linked. People who perform well in one area tend to excel in others, a pattern known as “general intelligence.” This pattern influences how effectively individuals learn, solve problems, and adapt across various settings. For over a century, it has suggested that human cognition is unified at a deep level, yet scientists have lacked a clear explanation for this unity.
“The problem of intelligence is not one of functional localization,” said Barbey, who also directs the Notre Dame Human Neuroimaging Center. “Contemporary research often asks where general intelligence originates in the brain—focusing primarily on specific networks 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.”
The Network Neuroscience Theory Explained
To explore a broader perspective, Barbey and his team, including lead author and Notre Dame graduate student Ramsey Wilcox, tested the Network Neuroscience Theory. Their findings, published in Nature Communications, propose that general intelligence is not a specific ability or mental strategy but reflects a pattern where many cognitive skills are positively related. This pattern stems from the efficient structure and cooperation of the brain’s networks.
The team analyzed brain imaging and cognitive performance data from 831 adults in the Human Connectome Project and an independent group of 145 adults in the INSIGHT Study. By combining measures of brain structure and function, they created a detailed picture of large-scale brain organization. The Network Neuroscience Theory views intelligence as a property of the brain as a whole, dependent on how effectively networks coordinate and reorganize to handle different challenges.
“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.”
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 but 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 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, helping orchestrate activity across networks. Whether interpreting subtle clues, learning a new skill, or deciding between careful analysis and quick intuition, these regulatory areas 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 maintaining short communication paths to distant regions, supporting flexible and effective problem-solving.
“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. This perspective may also explain why intelligence tends to increase during childhood, decline with aging, and be especially vulnerable to widespread brain injury, as large-scale coordination changes more than isolated functions.
The results contribute to debates about artificial intelligence. If human intelligence depends on system-level organization rather than a single general-purpose mechanism, 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. 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, offering a new perspective on the intricate workings of the human mind and its potential applications in artificial intelligence.
