Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life.
Five-month-old babies who have a high autism risk already show crowded local brain networks that bedside light sensors can catch.
01Research in Context
What this study did
Researchers placed a soft cap with tiny lights on 5-month-old babies. The lights sent safe red light through the scalp. A camera tracked how the light changed. This shows blood flow in the brain.
The team studied babies who have an older sibling with autism. These babies have a higher chance of autism. They also studied babies with no family history. They wanted to see if brain networks looked different.
What they found
The high-risk babies had too many local connections. Their networks looked crowded. Messages moved slowly. The test told the groups apart with about 78 percent accuracy.
Low-risk babies had cleaner long-distance links. Their networks worked like open highways. The gap was already clear at five months.
How this fits with other research
Wagner et al. (2025) scanned the same babies again at nine months. They found the high-risk group still had odd brain answers when hearing speech. The new study adds language detail to the early network picture.
Bassett-Gunter et al. (2017) saw high-risk babies lose interest in speech sounds during the first year. Fen et al. now show the brain wiring behind that drop. Heart-rate and light-based measures tell one story.
Gandhi et al. (2022) reviewed 17 brain-and-language papers. They found no single pattern. The 2022 fNIRS result helps explain why: the first difference is network shape, not language spots.
Why it matters
You now have a five-month warning sign that is easy to collect. The cap weighs less than a hat. You can track siblings of clients you already serve. Spotting odd wiring early lets you start play-based intervention before delays show. Share the light-cap idea with pediatricians. Earlier entry means better outcomes for the whole family.
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02At a glance
03Original abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10 months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life.
Autism research : official journal of the International Society for Autism Research, 2022 · doi:10.1002/aur.2827