Five Phases of Brain Wiring: How Your Neural Networks Change From Birth to Old Age
- Fred Shaffer
- 2 hours ago
- 9 min read
Mousley and colleagues (2025) present a view of the brain as a living network that does not simply mature and then decline. Instead, its wiring passes through a series of turning points that divide the lifespan into five distinct phases, each with its own characteristic pattern of connections between brain regions.
What is the Science?
Your brain isn't like a computer that gets built once and then slowly wears out. Instead, the way different brain regions connect changes throughout your entire life, passing through five distinct phases, almost like chapters in a book.
To understand this study, think of the brain as a network, similar to a social network or a road map. Different brain regions are like cities, and the white matter tracts that carry signals between them are like highways. Scientists can map these connections using a special type of brain scan called diffusion MRI, which tracks the movement of water molecules along nerve fibers to reveal the brain's wiring.
The researchers measured three main qualities of these brain networks:
Integration refers to how easily information can travel across the entire brain. A highly integrated brain can quickly send signals between regions, like a country with many direct flights between cities.
Segregation refers to the degree to which the brain is divided into specialized neighborhoods or modules. A highly segregated brain has tightly knit clusters of regions that work closely together, like a city with distinct districts for business, the arts, and residential life.
Centrality refers to the importance of certain brain regions as hubs or relay stations. Some regions act like major airport hubs, where a lot of traffic passes through.
Their big finding? The balance between these qualities doesn't change smoothly as we age. Instead, there are four specific ages at which the brain's organization shifts: around 9, 32, 66, and 83 years old. These turning points divide life into five distinct eras of brain wiring.
How Did They Study the Brain?
The research team pulled together brain scans from nine large-scale studies, giving them data that spans from newborn babies to 90-year-olds. That's rare, since most brain studies focus on just one age group, like children or older adults.
After cleaning up the data, they analyzed scans from 3,802 people, with roughly equal numbers of males and females. They divided each brain into 90 regions and measured how strongly each region connected to every other region. They used special versions of their brain map for different ages, since a newborn's brain is shaped very differently from an adult's, even though the same basic regions are present.
For each brain, they calculated twelve different measures of network organization, covering integration, segregation, and centrality. They then used statistical techniques to see how these measures changed with age.
How Did They Compare Brains Scanned by Different Labs?
Here's where the methods get clever. Because the brain scans came from different research centers and were acquired with different equipment, the team first had to "harmonize" the data, essentially adjusting for differences between scanners so they could fairly compare brains scanned in different places.
They also had to deal with a tricky problem: some brains have more connections than others, regardless of how those connections are organized. To make fair comparisons, they kept only the strongest 10 percent of connections in each brain. This way, they were comparing the pattern of connections, not just the total number.
To find the turning points, the researchers used a technique called manifold learning. Imagine taking all 12 measures for each age and plotting them as points in space. As age increases, these points trace out a path. The researchers looked for places where this path changed direction, signaling a shift in how the brain is organized.
To make sure their findings weren't just statistical flukes, they ran the analysis 968 different ways with slightly different settings. The same four turning points kept showing up: around ages 9, 32, 66, and 83.
What Did They Find?
Birth to Age 9: Building Local Circuits
In the earliest years of life, the brain becomes less globally connected but more locally organized. Think of it like a new country that starts by building strong local roads within each city before connecting cities. The brain is consolidating neighborhood circuits, creating tightly knit local clusters.
Ages 9 to 32: The Road to Peak Efficiency
This extended period, which the researchers call the "adolescent phase," is when the brain becomes increasingly efficient at both local and global communication. The brain develops what scientists call "small-world" organization, a sweet spot where regions maintain strong local connections while also having efficient long-distance routes. By the early thirties, the brain reaches peak global efficiency. Interestingly, this is also when personality traits and many cognitive abilities tend to stabilize.
Age 32: The Major Turning Point
This is the biggest shift in the data. Around age 32, nearly every measure of brain organization reverses direction. Global efficiency begins to, while local clustering continues to strengthen. The brain begins a gradual transition from prioritizing long-range communication to emphasizing local, specialized processing.
Ages 32 to 66: The Long Adult Phase
During these decades, the brain slowly becomes less integrated (worse at long-distance communication) but more segregated (better organized into local modules). It's as if the brain is gradually shifting resources from maintaining interstate highways to strengthening local roads. These changes happen slowly and steadily.
Age 66: A Subtle Decline but Real Shift
Around 66, something changes again. The brain becomes noticeably more modular and more dependent on hub regions. This transition aligns with increased rates of high blood pressure, cognitive decline, and dementia risk in the general population. The brain's organization seems to reflect the increased vulnerability that comes with aging.
After Age 83: Individual Differences Take Over
In the final phase, the relationship between age and brain organization weakens considerably. Only one measure (subgraph centrality, which tracks how central certain regions are to local circuits) still clearly changes with age. This might be because the sample of very old adults was small, but it might also mean that by this age, individual factors like health, lifestyle, and genetics matter more than age itself.
What Were the Strengths and Limitations?
Strengths
The biggest strength is the scope. Very few studies have tracked brain organization from birth to age 90 in a single, consistent analysis. The researchers also went to great lengths to ensure their findings were robust, testing their methods in hundreds of different ways and consistently finding the same four turning points.
Limitations
This was a cross-sectional study, meaning they scanned different people at different ages rather than following the same people over time. That's an important distinction because some of the age differences might actually reflect generational differences rather than true aging effects.
The sample of adults over 80 was relatively small and probably healthier than average, since people with serious health problems are less likely to volunteer for research studies. This could make the late-life findings less reliable.
Finally, while the turning points at 9, 32, 66, and 83 are statistically robust, they shouldn't be taken as exact biological deadlines. Your brain doesn't flip a switch on your 32nd birthday. These are averages that describe general trends, not precise milestones.
Why Does This Matter?
This research changes how we think about brain development in several important ways:
First, it challenges the idea that the brain is "fully developed" by age 25 or even 18.
If global integration continues to increase into the early thirties, the brain is still maturing well into what we consider full adulthood.
Second, it reframes aging. Rather than a simple story of growth followed by decline, brain organization moves through distinct phases, each with its own character.
The 66-year-old brain isn't just a degraded version of the 32-year-old brain; it's organized differently, with stronger local modules and more prominent hub regions.
Third, this framework could help physicians and researchers consider when the brain might be most vulnerable to various problems.
Mental health disorders often emerge in late childhood and adolescence, right around the first turning point. Dementia risk increases after the mid-sixties, around the third turning point. These alignments might not be coincidental.
Finally, the research offers a hopeful message: brain development is extended, dynamic, and potentially influenced by lifestyle choices, not a brief burst of growth followed by inevitable decline.
Key Takeaways
The brain's wiring passes through five distinct phases, with turning points at roughly ages 9, 32, 66, and 83.
Global efficiency, the brain's ability to communicate across long distances, peaks around age 32.
After 32, the local organization continues to strengthen while long-range efficiency gradually declines.
Around age 66, the brain shifts toward more modular, hub-dependent organization, coinciding with increased health risks.
After 83, individual health and lifestyle factors may matter more than age in determining brain organization.
Glossary
adolescent phase: the extended period from roughly age 9 to the early 30s during which brain networks become increasingly efficient and reorganize in characteristic ways.
aging: the later stages of life in which brain structure and function progressively change, here emphasizing the period after midlife when network organization becomes more modular and hub dependent, and disease risk increases.
brain development: the lifelong process by which the brain’s structure and connectivity change, including both early maturation and later reorganization across distinct phases.
brain network: a description of the brain as a set of interconnected regions, where each region is treated as a node, and the physical or functional links between them are the connections.
brain region: a distinct anatomical area of the brain that can be treated as a single unit in analysis and that participates as a node in a brain network.
centrality: a family of network measures that quantify how important or influential a node is for communication within the network, for example, by how many information pathways pass through it.
cognitive abilities: mental capacities such as memory, attention, reasoning, and problem solving that depend on underlying brain structure and connectivity.
cross-sectional study: a study design in which different individuals of various ages are measured once, so age differences are inferred by comparing groups rather than by following the same people over time.
dementia: a group of disorders characterized by progressive decline in cognitive abilities severe enough to interfere with daily life, often associated with structural and functional brain changes.
diffusion MRI: a type of magnetic resonance imaging that measures the movement of water molecules in tissue, allowing researchers to infer the orientation of nerve fibers and map white matter connections.
era of brain wiring: a span of years during which the overall pattern of brain connectivity changes in a broadly consistent way, separated from other eras by identifiable turning points in network organization.
global efficiency: a network measure of how easily and quickly information can be exchanged across the entire brain, based on the average length of the shortest paths linking all pairs of regions.
hub region: a highly central brain region that connects many other regions or lies on many shortest paths, acting as a major relay or integration point for communication.
integration: the capacity of the brain’s network to support efficient information transfer between distant regions through short or strong paths, reflecting how well different parts of the brain can work together.
local circuits: tightly interconnected groups of nearby neurons or brain regions that support specialized processing within a limited spatial neighborhood.
local modules: clusters of brain regions that are more strongly connected to each other than to the rest of the brain, forming relatively specialized neighborhoods within the larger network.
manifold learning: a set of machine learning techniques that reduce complex, high-dimensional data to a lower-dimensional space while preserving important structure, used here to trace how brain network measures change with age.
mental health disorders: conditions such as depression, anxiety, or psychosis that affect mood, thinking, or behavior and are linked to alterations in brain development and network organization.
modularity: a property of a network describing how clearly it can be partitioned into communities or modules of nodes that are densely connected internally and more sparsely connected to other modules.
neural architecture: the large-scale structural organization of the brain, including how regions are arranged and interconnected.
network organization: the overall pattern and structure of connections within a brain network, encompassing how integrated, segregated, or hub-dominated the system is.
segregation: the degree to which the brain’s network is divided into specialized, tightly knit modules or neighborhoods that support distinct functions.
small-world organization: a network configuration that combines short average path lengths (supporting global communication) with high local clustering (supporting specialized processing), often seen as an efficient architecture for the brain.
subgraph centrality: a centrality measure that counts the number of closed walks of all lengths that start and end at a node, giving more weight to shorter walks, and reflecting a region’s importance in local circuits.
turning point: an age at which the overall trajectory of brain network organization changes direction, marking the boundary between distinct eras of brain wiring.
white matter: brain tissue composed mainly of myelinated axons that carry electrical signals between gray matter regions and form the physical substrate of long-range connectivity.
white matter tract: a bundle of parallel white matter fibers that links two or more brain regions, serving as a structural “highway” for neural communication.
Open-Access Reference
Mousley, A., Bethlehem, R. A. I., Yeh, F. C., & Astle, D. E. (2025). Topological turning points across the human lifespan. Nature Communications, 16, 10055. https://doi.org/10.1038/s41467-025-65974-8
About the Author
Fred Shaffer earned his PhD in Psychology from Oklahoma State University. He earned BCIA certifications in Biofeedback and HRV Biofeedback. Fred is an Allen Fellow and Professor of Psychology at Truman State University, where has has taught for 50 years. He is a Biological Psychologist who consults and lectures in heart rate variability biofeedback, Physiological Psychology, and Psychopharmacology. Fred helped to edit Evidence-Based Practice in Biofeedback and Neurofeedback (3rd and 4th eds.) and helped to maintain BCIA's certification programs.
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