Scientists May Have Found How the Brain Becomes One Intelligent System

New research suggests intelligence arises not from a single brain region, but from how networks across the brain work together as an integrated system.

Neuroscientists often describe the brain as a collection of specialist teams. Skills like attention, perception, memory, language, and thinking have been linked to different networks, and research has typically zoomed in on one network at a time.

That focus has delivered major progress, but it leaves a bigger mystery on the table: everyday experience does not feel like a set of separate modules. Most of the time, the mind works as one coordinated system, even when the task pulls in many different abilities at once.

Researchers at the University of Notre Dame are now using neuroimaging to take a more whole-brain view, asking how the brain’s overall organization supports intelligence. Instead of treating networks like isolated islands, this approach looks at how they connect and cooperate, more like a city’s transportation grid than a single road.

“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.

How cognitive ties form ‘general intelligence’

For decades, psychologists have noticed a pattern: people who perform well in one mental domain often tend to do well in others. Abilities as different as attention, perception, memory, and language are linked in a way that points to a shared thread, which researchers call “general intelligence.” This broad factor helps explain how people learn, reason, and handle the shifting demands of school, work, relationships, and health.

That same pattern has hinted for more than a century that cognition is unified at a deep level. The missing piece has been an account of why those connections appear in the first place, and what it is about the brain that makes so many different abilities rise and fall together.

“The problem of intelligence is not one of functional localization,” said Barbey, who is also the director of 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.”

Barbey and his research team, including Notre Dame graduate student and lead author Ramsey Wilcox, investigated the predictions of the unifying framework, called the Network Neuroscience Theory. Their study was recently published in the journal Nature Communications.

The Network Neuroscience Theory

General intelligence is not itself a skill or strategy, the researchers argued. It is a pattern — the tendency for diverse abilities to be positively correlated. The study argues that this pattern reflects differences in how efficiently brain networks are organized and work together.

To test this claim, the cognitive neuroscientists analyzed brain imaging and cognitive data from one of the largest studies conducted to date, examining 831 adults in the Human Connectome Project, along with an independent sample of 145 adults in the INSIGHT Study, which was funded by the Intelligence Advanced Research Projects Activity’s SHARP program. The researchers integrated measures of both brain structure and function to enable a more precise characterization of the human brain.

Rather than identifying intelligence with a particular cognitive function or brain network, the Network Neuroscience Theory characterizes it as a property of how the brain works as a whole. In this view, intelligence reflects how brain networks are coordinated and dynamically reconfigured to solve the diverse problems we encounter in life.

This research represents an important shift, according to Barbey and Wilcox.

“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 a globally coordinated system of networks

The researchers found evidence to support four predictions of the Network Neuroscience Theory.

First, the theory predicts that intelligence is not localized to a single brain network but arises from processing distributed across multiple networks. Intelligence, therefore, depends on how the brain manages the division of labor across different networks and combines them as needed.

Second, for the brain to manage this distributed processing, it requires integration and effective long-range communications. To synchronize those efforts, Barbey said, there is “a large and complex system of connections that serve as ‘shortcuts’ linking distant brain regions and integrating information across the networks.” These pathways connect structurally distant areas of the brain, enabling efficient communication and supporting coordinated processing across the system.

Third, effective integration requires regulatory control that coordinates interactions among networks by shaping how information flows throughout the brain. These areas serve as regulatory hubs, reaching out to other networks to orchestrate the brain’s ongoing activities. They selectively recruit the appropriate networks for the specific task at hand — whether it be piecing together subtle clues to make sense of a problem, learning a new skill or deciding whether a situation requires careful deliberation or a rapid, intuitive response.

Finally, Barbey said that general intelligence depends on the brain’s ability to balance local specialization with global integration. In other words, the brain functions best when tightly connected local clusters communicate well, but are still able to link to distant regions of the brain across short communication paths. This makes the most effective problem-solving possible, according to the co-authors.

The research suggests that intelligence is unified not because the brain relies on a single general-purpose processor, but because the same organizational principles shape how all cognitive functions work together.

Across both datasets, individual differences in general intelligence were consistently associated with these system-level properties. No single region or canonical “intelligence network” accounted for the effect.

“General intelligence becomes visible when cognition is coordinated,” Barbey noted, “when many processes must work together under system-level constraints.”

Applications for artificial intelligence

The implications of this study extend beyond intelligence research, he added. By grounding cognition in large-scale organization, the study offers a principled account of why the mind is unified at all.

This framework helps explain why intelligence develops broadly during childhood, declines with aging, and is particularly sensitive to diffuse brain injury. In each case, it is large-scale coordination — not isolated function — that changes.

The findings also inform ongoing debates about artificial intelligence and how AI models are developed. If general intelligence in humans arises from system-level organization rather than from a dedicated general-purpose mechanism, then achieving general intelligence in artificial systems may require more than the accumulation or scaling of specialized capabilities.

“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.”

Reference: “The network architecture of general intelligence in the human connectome” by Ramsey R. Wilcox, Babak Hemmatian, Lav R. Varshney and Aron K. Barbey, 26 January 2026, Nature Communications.
DOI: 10.1038/s41467-026-68698-5

Funding: Intelligence Advanced Research Projects Activity, Department of Defense, Defense Advanced Research Projects Agency (DARPA)

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