Evidence map›Paper›PMID 39704490›Full record

ArticleDevelopmental science2025

Accelerated Infant Brain Rhythm Maturation in Autism.

Abigail Dickinson, Nicole McDonald, Mirella Dapretto, Emilie Campos, Damla Senturk, Shafali Jeste

Abstract read
In one paragraph

Article in Developmental science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Abigail DickinsonSemel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-1936-2135
Nicole McDonaldSemel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, California, USA.
Mirella DaprettoAhmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, California, USA.
Emilie CamposUCLA Department of Biostatistics, Center for Health Sciences, University of California, Los Angeles, California, USA.
Damla SenturkUCLA Department of Biostatistics, Center for Health Sciences, University of California, Los Angeles, California, USA.
Shafali JesteDivision of Neurology and Neurological Institute, The Children's Hospital of Los Angeles, Los Angeles, California, USA.

Funding

Understanding Repetitive Behavior in AutismP50HD055784 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BOOKHEIMER, SUSAN Y · 2007 to 2021
$32.0M
UCLA Center for Translational Research in Neurodevelopment: UC-TRaNU54HD087101 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MCCRACKEN, JAMES T. · 2016 to 2020
$6.5M
Functional Data Analysis for High-Dimensional Biobehavioral DataR01MH122428 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SENTURK, DAMLA, TELESCA, DONATELLO · 2020 to 2024
$1.8M
National Institute of Child Health and Human Development 2P50HD055784-08NICHD NIH HHS P50 HD055784NICHD NIH HHS U54 HD087101NIMH NIH HHS R01 MH122428
6 · The paper itself

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.

Indexed as

Autistic DisorderBrainElectroencephalographyBrain WavesFemaleHumansInfantMalePrincipal Component Analysisautismelectrophysiologyinfancyoscillatory dynamics

Identifiers

PMID39704490
PMCPMC11686827

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.