The Emergence of Network Inefficiencies in Infants With Autism Spectrum Disorder

John D Lewis1, Alan C Evans1, John R Pruett2

  • 1Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.

Insights

Early brain connectivity differences in infants at high risk for autism spectrum disorder (ASD) are detectable by 6 months. These network inefficiencies in infants later diagnosed with ASD predict symptom severity.

Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Pediatrics

Background:

  • Autism spectrum disorder (ASD) is characterized by developmental behaviors and associated brain connectivity abnormalities.
  • Previous studies are confounded by including individuals past the typical age of onset.
  • A prior study identified reduced network efficiencies in toddlers with ASD.

Purpose of the Study:

  • To map the emergence of brain network inefficiencies in the first year of life in infants at high risk for ASD.
  • To investigate early indicators of neurodevelopmental differences associated with ASD.
  • To understand the developmental trajectory of brain connectivity in early infancy.

Main Methods:

  • Utilized diffusion data from 260 infants (6 and 12 months old) at high and low familial risk for ASD.
  • Calculated brain network efficiency using measures of connection length and strength.
  • Employed linear mixed-effects models to assess group differences in efficiency.

Main Results:

  • Detected connectivity inefficiencies in high-risk infants as early as 6 months of age.
  • These early inefficiencies were localized to brain regions involved in low-level sensory processing.
  • In high-risk infants, early network inefficiencies predicted symptom severity at 24 months.

Conclusions:

  • Infants who develop ASD exhibit connectivity deficits related to low-level processing before 6 months of age.
  • These early deficits may initiate a developmental cascade impacting brain organization and higher-level functions.
  • Findings highlight the importance of early detection and intervention for ASD.
Abstract

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