Discover how the brain's communication networks form in preterm infants and what this means for their neurological development
Imagine a sprawling, complex city in the early stages of construction. The major highways aren't yet paved, but the blueprint for their connections already exists. This is similar to the brain of a newborn infant—especially one born prematurely. While the brain's physical structures are present, the sophisticated communication networks that will enable everything from recognizing a parent's face to solving complex problems are still under development.
of all newborns are born prematurely each year 1
trimester is a critical period for brain network formation 8
early brain patterns predict outcomes at this age 5
For the 10% of all newborns born prematurely each year, this construction process is abruptly transferred from the protected environment of the womb to the outside world during a critically important period of brain development 1 . Neuroscience research has revealed that this early transition has profound consequences for how the brain's networks form, with lasting effects on neurological performance throughout life. What scientists are now discovering—through advanced imaging technologies and meticulous research—is that the specific patterns of connection and communication between different brain regions in these earliest days of life can provide remarkable insights into a child's future developmental trajectory.
To appreciate why premature birth affects brain development, we need to understand some key concepts about how our brains are organized:
This refers to how different brain regions "talk" to each other. Using specialized brain imaging techniques, researchers can observe how synchronized various brain areas are in their activity patterns. When two regions frequently activate in sync, they're considered strongly connected—much like close friends who often think alike 2 9 .
The brain's cortex (its outer layer) organizes itself into distinct networks, each with specialized functions. In infants, the most developed networks handle basic sensory processing, while higher-order networks responsible for complex thinking, attention, and self-awareness are still forming 2 .
The third trimester of pregnancy is a period of explosive brain growth and organization. When a baby is born prematurely, this delicate process continues outside the womb, where the brain is exposed to stimuli, stressors, and conditions vastly different from what it would have experienced in the uterus 8 .
Groundbreaking research published in Nature Communications in 2024 has revealed that the dynamic connections in infant brains follow predictable patterns, but these patterns look significantly different in preterm infants compared to their full-term counterparts 3 5 .
Preterm infants show an altered repertoire of brain states and transition between them differently than term-born infants 3 . These early dynamic patterns correlate with social, sensory, and repetitive behaviors measured at 18 months of age 5 .
Studies examining brain activity in preterm infants at what would have been their full-term due date consistently find widespread differences in functional connectivity across multiple frequency bands 1 . These aren't isolated changes—they affect networks throughout the brain, with particularly pronounced alterations in connections involving the frontal regions, which are crucial for higher-order cognitive functions 6 .
Using precision mapping approaches, researchers have discovered that while preterm infants show ongoing brain network development after birth, they typically don't reach the same level of connectivity as term-born infants by their term-equivalent age 2 . Primary sensory networks mature earlier and appear more resilient, while higher-order association networks show more pronounced and prolonged disruptions 2 .
To understand how scientists uncover these remarkable insights, let's examine a key experiment from the landmark 2024 Nature Communications study that investigated dynamic functional connectivity in preterm and term infants 3 5 .
Infants were scanned during natural sleep without sedation, using specialized noise-reduction and motion-correction techniques adapted for tiny subjects 9 .
The fMRI scanner measured blood flow changes in the brain, which indicate regional brain activity, over approximately 20 minutes while the infants slept.
Researchers used advanced computational methods to identify momentary patterns of synchronization between different brain regions, applying a technique called Leading Eigenvector Analysis (LEiDA) to capture the brain's constantly shifting connectivity states 3 .
Through clustering algorithms, the team identified six recurrent brain states—three characterized by widespread global synchronization and three showing more regionally specific patterns 3 .
Finally, they examined how measures of brain dynamics correlated with neurodevelopmental assessments conducted at 18 months of age.
The experiment revealed striking differences between term and preterm infants:
| Global Dynamic Features in Term vs. Preterm Infants | ||||
|---|---|---|---|---|
| Dynamic Feature | Term-Born Infants | Preterm Infants | Effect Size | Significance |
| Mean Synchronisation | 0.52 (SD 0.08) | 0.48 (SD 0.08) | Cohen's D = 0.567 | p < 0.001 |
| Metastability | 0.20 (SD 0.02) | 0.19 (SD 0.02) | Cohen's D = 0.454 | p < 0.001 |
Preterm infants showed significantly lower mean synchronisation—indicating less coordinated activity across brain regions—and reduced metastability, reflecting less flexible switching between brain states 3 . These global measures of brain dynamics were not just statistical curiosities; lower mean synchronisation was significantly associated with higher (more atypical) scores on the Quantitative Checklist for Autism in Toddlers (Q-CHAT) at 18 months of age 5 .
| Characteristics of Six Neonatal Brain States | |||
|---|---|---|---|
| Brain State | Type | Primary Regions | Key Characteristics |
| Global State A | Widespread | Whole-brain | Highest synchronisation, fractional occupancy, and dwell times |
| Global State B | Widespread | Whole-brain | Intermediate synchronisation |
| Global State C | Widespread | Whole-brain | Intermediate synchronisation, increases with age |
| Occipital State | Regional | Visual cortex | Specialized for visual processing |
| Sensorimotor State | Regional | Sensorimotor cortex | Specialized for movement and sensation |
| Frontoparietal State | Regional | Frontal cortex, angular gyrus, posterior cingulate | Potential precursor to higher cognitive networks |
When examining how these brain states changed with development, researchers found that higher postmenstrual age at scan was correlated with:
Perhaps most importantly, the altered dynamic connectivity patterns in preterm infants were associated with atypical social, sensory, and repetitive behaviors at 18 months of age, suggesting these early measurements could serve as valuable biomarkers for identifying infants who might benefit from early intervention 3 .
To conduct this sophisticated research, scientists rely on an array of specialized tools and techniques:
| Key Research Tools for Studying Infant Brain Connectivity | ||
|---|---|---|
| Tool or Technique | Function | Application in Infants |
| Multi-channel EEG | Measures electrical activity from the scalp | Used to compute phase connectivity between brain regions during different sleep states 1 |
| fMRI (functional MRI) | Tracks blood flow changes indicating brain activity | Captures resting-state functional connectivity; adapted for silent operation for sleeping infants 9 |
| Debiased Weighted Phase Lag Index | Quantifies synchronization between brain signals | Calculates phase connectivity from source-level EEG data 1 |
| Network-Based Statistic | Statistical method for identifying network differences | Tests group differences in functional connectivity between preterm and term infants 1 |
| Graph Theory Analysis | Mathematical approach to network organization | Quantifies global and regional brain network properties 9 |
| Leading Eigenvector Analysis (LEiDA) | Captures time-resolved connectivity patterns | Identifies transient brain states from dynamic fMRI data 3 |
Functional MRI allows researchers to observe brain activity in real-time by detecting changes in blood flow. Special adaptations make it suitable for studying sleeping infants without sedation.
Electroencephalography provides high temporal resolution for studying rapid changes in brain activity, making it ideal for analyzing dynamic connectivity patterns.
The revelation that preterm infants have distinctly different patterns of functional brain connectivity—and that these patterns predict later neurodevelopmental outcomes—represents a paradigm shift in how we understand the long-term effects of premature birth. We're beginning to appreciate that the issue isn't just about the size or structure of the brain, but about the complex dance of communication between different brain regions.
These discoveries are paving the way for more personalized approaches to monitoring and supporting neurodevelopment in children born preterm. The goal is shifting from simply ensuring survival to optimizing the quality of neurological development from the earliest possible moment.
As research continues, scientists hope to identify specific patterns that reliably predict which children might face challenges with executive function, social communication, or sensory processing—allowing for targeted early interventions while the brain remains at its most plastic and responsive.
What makes this research particularly hopeful is that by understanding these early blueprints of brain organization, we're moving closer to a future where we can provide precisely timed, individualized support that helps every child—regardless of their start in life—build the strongest possible foundation for their future cognitive and emotional well-being.