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논문 기본정보

Resting-State Network Complexity and Magnitude Are Reduced in Prematurely Born Infants

논문 개요

기관명, 저널명, ISSN, ISBN 으로 구성된 논문 개요 표입니다.
기관명 NDSL
저널명 Cerebral cortex
ISSN 1047-3211,1460-2199
ISBN

논문저자 및 소속기관 정보

저자, 소속기관, 출판인, 간행물 번호, 발행연도, 초록, 원문UR, 첨부파일 순으로 구성된 논문저자 및 소속기관 정보표입니다
저자(한글) Smyser, Christopher D.,Snyder, Abraham Z.,Shimony, Joshua S.,Mitra, Anish,Inder, Terrie E.,Neil, Jeffrey J.
저자(영문)
소속기관
소속기관(영문)
출판인
간행물 번호
발행연도 2016-01-01
초록 Premature birth is associated with high rates of motor and cognitive disability. Investigations have described resting-state functional magnetic resonance imaging (rs-fMRI) correlates of prematurity in older children, but comparable data in the neonatal period remain scarce. We studied 25 term-born control infants within the first week of life and 25 very preterm infants (born at gestational ages ranging from 23 to 29 weeks) without evident structural injury at term equivalent postmenstrual age. Conventional resting-state network (RSN) mapping revealed only modest differences between the term and prematurely born infants, in accordance with previous work. However, clear group differences were observed in quantitative analyses based on correlation and covariance matrices representing the functional MRI time series extracted from 31 regions of interest in 7 RSNs. In addition, the maximum likelihood dimensionality estimates of the group-averaged covariance matrices in the term and preterm infants were 5 and 3, respectively, indicating that prematurity leads to a reduction in the complexity of rs-fMRI covariance structure. These findings highlight the importance of quantitative analyses of rs-fMRI data and suggest a more sensitive method for delineating the effects of preterm birth in infants without evident structural injury.
원문URL http://click.ndsl.kr/servlet/OpenAPIDetailView?keyValue=03553784&target=NART&cn=NART74661890
첨부파일

추가정보

과학기술표준분류, ICT 기술분류,DDC 분류,주제어 (키워드) 순으로 구성된 추가정보표입니다
과학기술표준분류
ICT 기술분류
DDC 분류
주제어 (키워드) developmental neuroimaging,functional MRI,infant,prematurity,resting-state networks