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Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm
The latter half of gestation is a period of rapid brain development, including the formation of fundamental functional brain network architecture. Unlike fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidenc...
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| Published in: | Frontiers in neuroscience 2023-09, Vol.17, p.1214080-1214080 |
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| creator | Cook, Kevin M De Asis-Cruz, Josepheen Basu, Sudeepta K Andescavage, Nickie Murnick, Jonathan Spoehr, Emma du Plessis, Adré J Limperopoulos, Catherine |
| description | The latter half of gestation is a period of rapid brain development, including the formation of fundamental functional brain network architecture. Unlike
fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored.
From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex.
A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r
range 0.143-0.401, |
| doi_str_mv | 10.3389/fnins.2023.1214080 |
| format | article |
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fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored.
From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex.
A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r
range 0.143-0.401,
< 0048), with C and LE exhibited trending increases with age.
This is the first direct investigation on the extra-uterine formation of functional brain architecture in preterm infants. Importantly, our results suggest that changes in functional architecture with increasing age exhibit a different trajectory relative to
fetus. Instead, they exhibit developmental changes more similar to the early postnatal period in term born infants.</description><identifier>ISSN: 1662-4548</identifier><identifier>ISSN: 1662-453X</identifier><identifier>EISSN: 1662-453X</identifier><identifier>DOI: 10.3389/fnins.2023.1214080</identifier><identifier>PMID: 37719160</identifier><language>eng</language><publisher>Switzerland: Frontiers Research Foundation</publisher><subject>Age ; Brain architecture ; brain development ; Brain mapping ; brain network ; Efficiency ; Fetuses ; Functional magnetic resonance imaging ; Functional morphology ; Gestational age ; graph theory ; Infants ; Neonates ; Neuroscience ; Newborn babies ; Pregnancy ; Premature babies ; prematurity ; Regression analysis ; resting state fMRI ; stress</subject><ispartof>Frontiers in neuroscience, 2023-09, Vol.17, p.1214080-1214080</ispartof><rights>Copyright © 2023 Cook, De Asis-Cruz, Basu, Andescavage, Murnick, Spoehr, du Plessis and Limperopoulos.</rights><rights>2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Copyright © 2023 Cook, De Asis-Cruz, Basu, Andescavage, Murnick, Spoehr, du Plessis and Limperopoulos. 2023 Cook, De Asis-Cruz, Basu, Andescavage, Murnick, Spoehr, du Plessis and Limperopoulos</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c448t-d132660bce36e78ddbbeb6cbe3a2a85ffbcb92a90fc00b12f784bf7c3c8e0eec3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2859389371/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2859389371?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37719160$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cook, Kevin M</creatorcontrib><creatorcontrib>De Asis-Cruz, Josepheen</creatorcontrib><creatorcontrib>Basu, Sudeepta K</creatorcontrib><creatorcontrib>Andescavage, Nickie</creatorcontrib><creatorcontrib>Murnick, Jonathan</creatorcontrib><creatorcontrib>Spoehr, Emma</creatorcontrib><creatorcontrib>du Plessis, Adré J</creatorcontrib><creatorcontrib>Limperopoulos, Catherine</creatorcontrib><title>Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm</title><title>Frontiers in neuroscience</title><addtitle>Front Neurosci</addtitle><description>The latter half of gestation is a period of rapid brain development, including the formation of fundamental functional brain network architecture. Unlike
fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored.
From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex.
A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r
range 0.143-0.401,
< 0048), with C and LE exhibited trending increases with age.
This is the first direct investigation on the extra-uterine formation of functional brain architecture in preterm infants. Importantly, our results suggest that changes in functional architecture with increasing age exhibit a different trajectory relative to
fetus. Instead, they exhibit developmental changes more similar to the early postnatal period in term born infants.</description><subject>Age</subject><subject>Brain architecture</subject><subject>brain development</subject><subject>Brain mapping</subject><subject>brain network</subject><subject>Efficiency</subject><subject>Fetuses</subject><subject>Functional magnetic resonance imaging</subject><subject>Functional morphology</subject><subject>Gestational age</subject><subject>graph theory</subject><subject>Infants</subject><subject>Neonates</subject><subject>Neuroscience</subject><subject>Newborn babies</subject><subject>Pregnancy</subject><subject>Premature babies</subject><subject>prematurity</subject><subject>Regression analysis</subject><subject>resting state fMRI</subject><subject>stress</subject><issn>1662-4548</issn><issn>1662-453X</issn><issn>1662-453X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdUk1vEzEQXSEQLYU_wAFZ4sIlwR-7Xu8JoapApUpcQOJm2d5x4rBrB9sbGo795fU2IaKcPHrz5s2HX1W9JnjJmOjeW-98WlJM2ZJQUmOBn1TnhHO6qBv24-kprsVZ9SKlDcacipo-r85Y25KOcHxe3V3dLqYMMaC8drFHOboRUgFQDzsYwnYEn9WAzFr5FSTkPLKTN9kFX1AdVQE85N8h_kQhrpR3f9ScnInOW-VzQjpEj3YQ90j5HsFtjjDCsEfbCKXR-LJ6ZtWQ4NXxvai-f7r6dvllcfP18_Xlx5uFqWuRFz1hlHOsDTAOreh7rUFzo4EpqkRjrTa6o6rD1mCsCbWtqLVtDTMCMIBhF9X1QbcPaiO3ZVEV9zIoJx-AMr1UMTszgGQ1EMZZ6WZ5rRSovoS0ZoSJ0lHgovXhoLWd9Ai9KUeKangk-jjj3Vquwk4S3JT_Yl1ReHdUiOHXVE4uR5cMDIPyEKYkqeCcENI0pFDf_kfdhCmW-8-spitWYO3MogeWiSGlCPY0DcFy9ot88Iuc_SKPfilFb_7d41Ty1yDsHgn6wfk</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Cook, Kevin M</creator><creator>De Asis-Cruz, Josepheen</creator><creator>Basu, Sudeepta K</creator><creator>Andescavage, Nickie</creator><creator>Murnick, Jonathan</creator><creator>Spoehr, Emma</creator><creator>du Plessis, Adré J</creator><creator>Limperopoulos, Catherine</creator><general>Frontiers Research Foundation</general><general>Frontiers Media S.A</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20230901</creationdate><title>Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm</title><author>Cook, Kevin M ; 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Unlike
fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored.
From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex.
A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r
range 0.143-0.401,
< 0048), with C and LE exhibited trending increases with age.
This is the first direct investigation on the extra-uterine formation of functional brain architecture in preterm infants. Importantly, our results suggest that changes in functional architecture with increasing age exhibit a different trajectory relative to
fetus. Instead, they exhibit developmental changes more similar to the early postnatal period in term born infants.</abstract><cop>Switzerland</cop><pub>Frontiers Research Foundation</pub><pmid>37719160</pmid><doi>10.3389/fnins.2023.1214080</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| source | Publicly Available Content Database; PubMed Central |
| subjects | Age Brain architecture brain development Brain mapping brain network Efficiency Fetuses Functional magnetic resonance imaging Functional morphology Gestational age graph theory Infants Neonates Neuroscience Newborn babies Pregnancy Premature babies prematurity Regression analysis resting state fMRI stress |
| title | Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm |
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