Evidence map›Paper›PMID 39258437›Full record

ArticleHuman brain mapping2024

Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study.

Ishara Paranawithana, Darren Mao, Colette M McKay, Yan T Wong

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Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Ishara ParanawithanaDepartment of Electrical and Computer Systems Engineering, Monash University, Clayton, Victoria, Australia.ORCID 0000-0001-6509-9687
Darren MaoBionics Institute, East Melbourne, Victoria, Australia.
Colette M McKayBionics Institute, East Melbourne, Victoria, Australia.
Yan T WongDepartment of Electrical and Computer Systems Engineering, Monash University, Clayton, Victoria, Australia.

Funding

Medical Research Future Fund (BioMedTech Horizons Program)National Health and Medical Research Council GNT1154233Victorian Medical Research Acceleration Fund
6 · The paper itself

Abstract

Task-related studies have consistently reported that listening to speech sounds activate the temporal and prefrontal regions of the brain. However, it is not well understood how functional organization of auditory and language networks differ when processing speech sounds from its resting state form. The knowledge of language network organization in typically developing infants could serve as an important biomarker to understand network-level disruptions expected in infants with hearing impairment. We hypothesized that topological differences of language networks can be characterized using functional connectivity measures in two experimental conditions (1) complete silence (resting) and (2) in response to repetitive continuous speech sounds (steady). Thirty normal-hearing infants (14 males and 16 females, age: 7.8 ± 4.8 months) were recruited in this study. Brain activity was recorded from bilateral temporal and prefrontal regions associated with speech and language processing for two experimental conditions: resting and steady states. Topological differences of functional language networks were characterized using graph theoretical analysis. The normalized global efficiency and clustering coefficient were used as measures of functional integration and segregation, respectively. We found that overall, language networks of infants demonstrate the economic small-world organization in both resting and steady states. Moreover, language networks exhibited significantly higher functional integration and significantly lower functional segregation in resting state compared to steady state. A secondary analysis that investigated developmental effects of infants aged 6-months or below and above 6-months revealed that such topological differences in functional integration and segregation across resting and steady states can be reliably detected after the first 6-months of life. The higher functional integration observed in resting state suggests that language networks of infants facilitate more efficient parallel information processing across distributed language regions in the absence of speech stimuli. Moreover, higher functional segregation in steady state indicates that the speech information processing occurs within densely interconnected specialized regions in the language network.

Indexed as

ConnectomeNerve NetSpectroscopy, Near-InfraredSpeech PerceptionFemaleHumansInfantLanguageMalePrefrontal Cortexfunctional connectivityfunctional near‐infrared spectroscopygraph network measureslanguage networksresting statesmall‐world topologysteady state

Identifiers

PMID39258437
PMCPMC11387990

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