Why Some Brains Switch Gears More Efficiently Than Others and What That Reveals About Human Intelligence
The human brain is constantly juggling information that unfolds at very different speeds. Some signals demand instant reactions, like stepping aside when something suddenly moves toward us, while others unfold slowly, such as understanding language, planning future actions, or reflecting on complex ideas. A new scientific study from Rutgers Health, published in Nature Communications, takes a deep dive into why some brains manage these rapid shifts more efficiently than others—and what this means for cognition, behavior, and mental health.
At the heart of this research is a concept known as intrinsic neural timescales, often shortened to INTs. These timescales describe how long different brain regions hold onto information. Some areas are built for speed, processing information over milliseconds, while others integrate signals over much longer periods. The way these fast and slow systems interact turns out to be critical for how effectively the brain functions as a whole.
Understanding How the Brain Integrates Fast and Slow Information
The study shows that the brain’s ability to function smoothly depends on how well it combines information processed at different speeds. To produce meaningful behavior—whether that’s making decisions, reacting to the environment, or solving problems—the brain must coordinate these varied signals across its network.
This coordination is made possible by white matter connectivity, the brain’s internal wiring that links different regions together. White matter pathways allow information processed in one area to be shared with others, ensuring that fast reactions and slower, more reflective processes can influence each other. The researchers found that this integration is not random; it follows structured patterns that vary from person to person.
To explore this in detail, the research team analyzed multimodal brain imaging data from 960 individuals. Using this data, they constructed detailed maps of each participant’s brain connectivity, known as connectomes. These maps show how different regions are physically connected through white matter pathways.
Advanced mathematical models—borrowed from the study of complex systems—were then applied to understand how information flows through these networks over time. This allowed the researchers to directly infer intrinsic neural timescales from brain connectivity, creating a clear link between local information processing and global brain communication.
Key Findings From the Rutgers Study
One of the most important findings is that the distribution of neural timescales across the cortex plays a major role in how efficiently the brain can switch between large-scale activity patterns. These patterns are closely tied to behavior, meaning that how well the brain transitions between them can affect cognitive performance.
Crucially, this organization differs across individuals. Some people’s brains are wired in a way that better matches how different regions handle fast and slow information. These individuals tend to show higher cognitive capacity, suggesting that efficient “gear switching” may be one of the foundations of intelligence.
The study also found that these neural timescale patterns are deeply rooted in biology. They are linked to genetic, molecular, and cellular features of specific brain regions, grounding the findings in fundamental neurobiology rather than abstract theory. This biological connection strengthens the idea that differences in cognition are not just shaped by experience, but also by the brain’s underlying structure.
Interestingly, similar relationships were observed in the mouse brain, indicating that these mechanisms are likely conserved across species. This cross-species consistency suggests that the way brains integrate information over time is a fundamental principle of neural organization.
Why Intrinsic Neural Timescales Matter
Intrinsic neural timescales help explain why different parts of the brain specialize in different tasks. Sensory regions, such as those involved in vision or hearing, typically operate on short timescales, allowing them to respond quickly to incoming stimuli. Higher-order regions involved in reasoning, memory, and planning operate on longer timescales, enabling them to integrate information over extended periods.
What makes this study stand out is its demonstration that how these timescales are distributed and connected across the brain influences overall cognitive efficiency. It’s not just about having fast or slow regions, but about how well these regions communicate through the brain’s white matter network.
This insight helps explain individual differences in cognition. People vary in how their brains are wired, and these variations can affect how smoothly they transition between different modes of thinking—such as shifting from quick reactions to deliberate analysis.
Implications for Mental Health and Psychiatry
Beyond healthy cognition, the findings have important implications for understanding neuropsychiatric conditions. Disorders such as schizophrenia, bipolar disorder, and depression have long been associated with disruptions in brain connectivity. This research suggests that such disruptions may interfere with how the brain integrates information across timescales.
The research team is now extending their work to examine these conditions more closely. By studying how altered white matter connectivity affects intrinsic neural timescales, scientists hope to gain new insights into the mechanisms underlying psychiatric symptoms. This could eventually inform more targeted treatments that focus on restoring balanced information processing rather than just addressing surface-level symptoms.
A Closer Look at White Matter Connectivity
White matter plays a central role in this research, yet it often receives less attention than gray matter, where neurons do most of their computation. White matter consists of bundles of axons that connect distant brain regions, enabling communication across the brain.
Efficient white matter organization allows information to travel quickly and reliably between areas with different processing speeds. When this organization is well matched to intrinsic neural timescales, the brain can smoothly coordinate fast and slow processes. When it’s not, communication becomes less efficient, potentially leading to cognitive difficulties.
This study reinforces the idea that cognition emerges from network-level interactions, not just isolated brain regions. Intelligence, attention, and flexibility depend on how well the brain’s wiring supports the flow of information over time.
What This Research Adds to Neuroscience
Previous studies have examined intrinsic neural timescales using direct neural recordings, often in animals or small human samples. What sets this work apart is its large sample size and its ability to infer timescales directly from brain connectivity data. This opens the door to studying temporal processing in large populations without invasive methods.
The use of optimal control theory—a mathematical framework for understanding how systems evolve over time—adds another layer of innovation. It allows researchers to model how brain networks naturally shift between states, providing a more dynamic view of cognition than static brain maps.
By linking timescales, connectivity, genetics, and behavior, this study offers a more integrated understanding of how the brain works as a complex system.
Looking Ahead
The findings suggest that cognitive differences between individuals may be partly explained by how well their brain wiring supports the integration of fast and slow information. This perspective moves beyond simple notions of “more activity” or “less activity” in certain brain regions and instead focuses on timing, coordination, and network structure.
As research continues, intrinsic neural timescales could become an important framework for understanding not only intelligence, but also learning, aging, and mental illness. By revealing why some brains switch gears more efficiently than others, this study brings us one step closer to understanding the deeper principles that shape human thought and behavior.
Research paper:
https://doi.org/10.1038/s41467-025-66542-w
