Accelerated Infant Brain Rhythm Maturation in Autism

Electroencephalography (EEG) captures characteristic oscillatory shifts in infant brain rhythms over the first year of life, offering unique insights into early functional brain development and potential markers for detecting neural differences associated with autism. This study used functional principal component analysis (FPCA) to derive dynamic markers of spectral maturation from task-free EEG recordings collected at 3, 6, 9, and 12 months from 87 infants, 51 of whom were at higher likelihood of developing autism due to an older sibling diagnosed with the condition. FPCA revealed three principal components explaining over 96% of the variance in infant power spectra, with power increases between 6 and 9 Hz (FPC1) representing the most significant age-related trend, accounting for more than 71% of the variance. Notably, this oscillatory change occurred at a faster rate in infants later diagnosed with autism, indicated by a steeper trajectory of FPC1 scores between 3 and 12 months (p < 0.001). Age-related spectral changes were consistent regardless of familial likelihood status, suggesting that differences in oscillatory timing are associated with autism outcomes rather than genetic predisposition. These findings indicate that while the typical sequence of oscillatory maturation is preserved in autism, the timing of these changes is altered, underscoring the critical role of timing in autism pathophysiology and the development of potential screening tools.

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Publication Details

Journal
Developmental Science
Published
2024-12-20
DOI
https://doi.org/10.1111/desc.13593
Citations
3
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
1.03

Funders

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article

Accelerated Infant Brain Rhythm Maturation in Autism

Mirella Dapretto, Emilie Campos, Abigail Dickinson, Damla Şentürk et al.
3 citations
Developmental Science
Functional Brain Connectivity Studies
1.03
article

Accelerated Infant Brain Rhythm Maturation in Autism

Mirella Dapretto, Emilie Campos, Abigail Dickinson, Damla Şentürk, Nicole M. McDonald, Shafali Jeste
article en
3 citations

Abstract

Electroencephalography (EEG) captures characteristic oscillatory shifts in infant brain rhythms over the first year of life, offering unique insights into early functional brain development and potential markers for detecting neural differences associated with autism. This study used functional principal component analysis (FPCA) to derive dynamic markers of spectral maturation from task-free EEG recordings collected at 3, 6, 9, and 12 months from 87 infants, 51 of whom were at higher likelihood of developing autism due to an older sibling diagnosed with the condition. FPCA revealed three principal components explaining over 96% of the variance in infant power spectra, with power increases between 6 and 9 Hz (FPC1) representing the most significant age-related trend, accounting for more than 71% of the variance. Notably, this oscillatory change occurred at a faster rate in infants later diagnosed with autism, indicated by a steeper trajectory of FPC1 scores between 3 and 12 months (p < 0.001). Age-related spectral changes were consistent regardless of familial likelihood status, suggesting that differences in oscillatory timing are associated with autism outcomes rather than genetic predisposition. These findings indicate that while the typical sequence of oscillatory maturation is preserved in autism, the timing of these changes is altered, underscoring the critical role of timing in autism pathophysiology and the development of potential screening tools.

Developmental ScienceVol. 28(1)
Children's Hospital of Los Angeles (US), University of California, Los Angeles (US), Brain Mapping Foundation (US), Oklahoma State University Center for Health Sciences (US)
National Institute of Mental Health, National Institute of Child Health and Human Development
Openalex Percentile: Top 23%
Functional Brain Connectivity Studies
1.03
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