Deficits in neural encoding of speech in preterm infants

Novitskiy, Nikolay; Chan, Peggy Hiu Ying; Chan, Mavis; Lai, Chi Ming; Leung, Tak Yeung; Leung, Ting Fan; Bornstein, Marc H.; Lam, Hugh Simon; Wong, Patrick C. M.

doi:10.1016/j.dcn.2023.101259

Cited by 3 publications

(8 citation statements)

References 86 publications

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“…On the other hand, no group differences were observed in measures related to response power. However, the length of gestation of the preterm sample, the age of the sample and other methodological differences hinders the comparison our results with those of Novitskiy et al (2023) .…”

Section: Discussionmentioning

confidence: 71%

“…However, the GA of their preterm neonates (i.e., ≤ 32 weeks of GA), as well as the lack of a control group, limits the possibility to compare their results directly with the present findings. Novitskiy et al (2023) explored whether the neural encoding of three different speech stimuli differed between a group of preterm infants delivered from 22 to 34 weeks of gestation and a group of term infants delivered from 38 to 40 weeks of gestation. To that end, different parameters related to response synchronization and response power were retrieved from the FFR.…”

Section: Discussionmentioning

confidence: 99%

“…As discussed above, existing FFR studies in premature populations conducted during the first years of life suggest that premature infants born before 34 weeks of GA have limited neural encoding abilities of complex sound features ( Madrid et al, 2021 ; Novitskiy et al, 2023 ). However, no previous studies explored preterm babies born from 34 0/7 through 36 6/7 weeks of GA.…”

Section: Introductionmentioning

confidence: 98%

“…The FFR has been recorded in normal and clinical populations at the adulthood ( White-Schwoch et al, 2020 ; Bidelman and Momtaz, 2021 ), childhood ( Thompson et al, 2019 , 2021 ), and the neonatal periods ( Gardi et al, 1979 ; Jeng et al, 2010 , 2011 , 2016a , b ; Ribas-Prats et al, 2019 ; Richard et al, 2020 ; Lemos et al, 2021 ; Ribas-Prats et al, 2022 , 2023 ; see reviews in Gorina-Careta et al, 2022 ). In premature populations, recent FFR studies disclosed altered neural encoding of several speech cues crucial to ensure proper language acquisition ( Madrid et al, 2021 ; Novitskiy et al, 2023 ). Madrid et al (2021) enrolled 28 preterm infants with ≤32 weeks of gestational age (GA) in a longitudinal study.…”

Section: Introductionmentioning

confidence: 99%

“…However, for higher frequencies of the first formant and higher harmonics (>270 Hz) such increase was not found. Novitskiy et al (2023) recorded the FFR from 45 preterm infants with a GA ≤ 34 weeks and 45 term infants from 0 to 12 months of age during natural sleep. In this study, three stimuli that differed in pitch were employed although no main effect of stimulus was found.…”

Section: Introductionmentioning

confidence: 99%

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The frequency-following response in late preterm neonates: a pilot study

Ribas-Prats,

Arenillas-Alcón,

Martínez

et al. 2024

Front. Psychol.

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IntroductionInfants born very early preterm are at high risk of language delays. However, less is known about the consequences of late prematurity. Hence, the aim of the present study is to characterize the neural encoding of speech sounds in late preterm neonates in comparison with those born at term.MethodsThe speech-evoked frequency-following response (FFR) was recorded to a consonant-vowel stimulus /da/ in 36 neonates in three different groups: 12 preterm neonates [mean gestational age (GA) 36.05 weeks], 12 “early term neonates” (mean GA 38.3 weeks), and “late term neonates” (mean GA 41.01 weeks).ResultsFrom the FFR recordings, a delayed neural response and a weaker stimulus F0 encoding in premature neonates compared to neonates born at term was observed. No differences in the response time onset nor in stimulus F0 encoding were observed between the two groups of neonates born at term. No differences between the three groups were observed in the neural encoding of the stimulus temporal fine structure.DiscussionThese results highlight alterations in the neural encoding of speech sounds related to prematurity, which were present for the stimulus F0 but not for its temporal fine structure.

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Section: Discussionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The frequency-following response in late preterm neonates: a pilot study

Ribas-Prats,

Arenillas-Alcón,

Martínez

et al. 2024

Front. Psychol.

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Brain templates for Chinese babies from newborn to three months of age

Geng,

Chan,

Lam

et al. 2024

NeuroImage

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Infant Neural Speech Encoding Forecasts Language Difficulties in Preschool Years

Wong,

Pan,

Lai

et al. 2024

Preprint

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Importance: Developmental language problems must be detected early to capitalize on the high effectiveness of early intervention. Because developmental language problems are not formally diagnosed until preschool years, a method must be developed and validated to forecast language problems from as early as infancy. Objective: To develop and validate predictive models of language problems with neural data collected from as early as infancy and language problems detected up to 36 months of age.Design, Setting, & Participants: Electroencephalography (EEG) neural encoding of speech, gestational age, birth weight, birth sex, and language outcome data were collected from 439 healthy children from a community sample. Ages and Stages Questionnaire data were also collected from a subset of children. EEG was collected between 3 weeks to 24 months of age and language outcome up to 36 months of age.Exposure: All children underwent EEG testing in which they listened to three speech stimuli (two native and one non-native) and early-latency and long-latency responses were collected. No intervention was involved in the study.Main Outcome Measures: The Chinese Communicative Development Inventory – Cantonese version (CCDI-C) and the language subscale of the Bayley Scales of Infant and Toddler Development, third edition (Bayley-III) were collected between 7 to 36 months of age. Results: Random Forest was used as machine learning algorithm to classify children into binary groups based on a percentile-rank cut-off on the outcome measures (e.g., below or above the 16th percentile). Different predictive models were developed and compared, including those with and without EEG and clinical measures. Models with non-neural measures (e.g., gestational age and birth weight) predicted language outcome above chance level. Models with EEG measures alone outperformed any models without neural features, with sensitivity and Area Under Curve (AUC) scoring well above 90% for the best models. When validated with unseen data, both sensitivity and AUC remained at 90%.Conclusion & Relevance: EEG neural encoding of speech can be a new procedure for screening language developmental problems as early as infancy. Families with children who are screened positive may consider early intervention in the form of parent coaching to promote better language development.

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Deficits in neural encoding of speech in preterm infants

Cited by 3 publications

References 86 publications

The frequency-following response in late preterm neonates: a pilot study

The frequency-following response in late preterm neonates: a pilot study

Brain templates for Chinese babies from newborn to three months of age

Infant Neural Speech Encoding Forecasts Language Difficulties in Preschool Years

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