Evidence map›Paper›PMID 39636849›Full record

ArticlePloS one2024

Infant low-frequency EEG cortical power, cortical tracking and phase-amplitude coupling predicts language a year later.

Adam Attaheri, Áine Ní Choisdealbha, Sinead Rocha, Perrine Brusini, Giovanni M Di Liberto, Natasha Mead, Helen Olawole-Scott, Panagiotis Boutris, Samuel Gibbon, Isabel Williams and 5 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  4. Infant Cortical Tracking of Speech Shows Emerging Spatial Release from Masking in the First Year of Life.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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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

15 authors.

Adam AttaheriDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-5158-7329
Áine Ní ChoisdealbhaDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Sinead RochaDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Perrine BrusiniDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Giovanni M Di LibertoSchool of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland.
Natasha MeadDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-0737-8738
Helen Olawole-ScottDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-9236-2345
Panagiotis BoutrisDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Samuel GibbonDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-5485-7523
Isabel WilliamsDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Christina GreyDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Maria Alfaro E OliveiraDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Carmel BroughDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.
Sheila FlanaganDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-0119-4196
Usha GoswamiDepartment of Psychology, Centre for Neuroscience in Education, University of Cambridge, Cambridge, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cortical signals have been shown to track acoustic and linguistic properties of continuous speech. This phenomenon has been measured in both children and adults, reflecting speech understanding by adults as well as cognitive functions such as attention and prediction. Furthermore, atypical low-frequency cortical tracking of speech is found in children with phonological difficulties (developmental dyslexia). Accordingly, low-frequency cortical signals may play a critical role in language acquisition. A recent investigation with infants Attaheri et al., 2022 [1] probed cortical tracking mechanisms at the ages of 4, 7 and 11 months as participants listened to sung speech. Results from temporal response function (TRF), phase-amplitude coupling (PAC) and dynamic theta-delta power (PSD) analyses indicated speech envelope tracking and stimulus-related power (PSD) for delta and theta neural signals. Furthermore, delta- and theta-driven PAC was found at all ages, with theta phases displaying stronger PAC with high-frequency amplitudes than delta. The present study tests whether these previous findings replicate in the second half of the full cohort of infants (N = 122) who were participating in this longitudinal study (first half: N = 61, (1); second half: N = 61). In addition to demonstrating good replication, we investigate whether cortical tracking in the first year of life predicts later language acquisition for the full cohort (122 infants recruited, 113 retained) using both infant-led and parent-estimated measures and multivariate and univariate analyses. Increased delta cortical tracking in the univariate analyses, increased ~2Hz PSD power and stronger theta-gamma PAC in both multivariate and univariate analyses were related to better language outcomes using both infant-led and parent-estimated measures. By contrast, increased ~4Hz PSD power in the multi-variate analyses, increased delta-beta PAC and a higher theta/delta power ratio in the multi-variate analyses were related to worse language outcomes. The data are interpreted within a "Temporal Sampling" framework for developmental language trajectories.

Indexed as

ElectroencephalographyLanguage DevelopmentCerebral CortexFemaleHumansInfantLanguageLongitudinal StudiesMaleSpeech PerceptionTheta Rhythm

Identifiers

PMID39636849
PMCPMC11620356

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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.