Resting-state networks in awake five- to eight-year old children
During the first 6–7 years of life children undergo a period of major neurocognitive development. Higher‐order cognitive functions such as executive control of attention, encoding and retrieving of stored information and goal‐directed behavior are present but less developed compared to older individ...
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Veröffentlicht in: | Human brain mapping 2012-05, Vol.33 (5), p.1189-1201 |
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creator | de Bie, Henrica M.A. Boersma, Maria Adriaanse, Sofie Veltman, Dick J. Wink, Alle Meije Roosendaal, Stefan D. Barkhof, Frederik Stam, Cornelis J. Oostrom, Kim J. Delemarre-van de Waal, Henriette A. Sanz-Arigita, Ernesto J. |
description | During the first 6–7 years of life children undergo a period of major neurocognitive development. Higher‐order cognitive functions such as executive control of attention, encoding and retrieving of stored information and goal‐directed behavior are present but less developed compared to older individuals. There is only very limited information from functional magnetic resonance imaging (fMRI) studies about the level of organization of functional networks in children in the early school period. In this study we perform continuous resting‐state functional connectivity MRI in 5‐ to 8‐year‐old children in an awake state to identify and characterize resting‐state networks (RSNs). Temporal concatenation independent component analysis (ICA) approach was applied to analyze the data. We identified 14 components consisting of regions known to be involved in visual and auditory processing, motor function, attention control, memory, and the default mode network (DMN). Most networks, in particular those supporting basic motor function and sensory related processing, had a robust functional organization similar to mature adult patterns. In contrast, the DMN and other RSNs involved in higher‐order cognitive functions had immature characteristics, revealing incomplete and fragmented patterns indicating less developed functional connectivity. We therefore conclude that the DMN and other RSNs involved in higher order cognitive functioning are detectable, yet in an immature state, at an age when these cognitive abilities are mastered. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc. |
doi_str_mv | 10.1002/hbm.21280 |
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Higher‐order cognitive functions such as executive control of attention, encoding and retrieving of stored information and goal‐directed behavior are present but less developed compared to older individuals. There is only very limited information from functional magnetic resonance imaging (fMRI) studies about the level of organization of functional networks in children in the early school period. In this study we perform continuous resting‐state functional connectivity MRI in 5‐ to 8‐year‐old children in an awake state to identify and characterize resting‐state networks (RSNs). Temporal concatenation independent component analysis (ICA) approach was applied to analyze the data. We identified 14 components consisting of regions known to be involved in visual and auditory processing, motor function, attention control, memory, and the default mode network (DMN). Most networks, in particular those supporting basic motor function and sensory related processing, had a robust functional organization similar to mature adult patterns. In contrast, the DMN and other RSNs involved in higher‐order cognitive functions had immature characteristics, revealing incomplete and fragmented patterns indicating less developed functional connectivity. We therefore conclude that the DMN and other RSNs involved in higher order cognitive functioning are detectable, yet in an immature state, at an age when these cognitive abilities are mastered. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.</description><identifier>ISSN: 1065-9471</identifier><identifier>ISSN: 1097-0193</identifier><identifier>EISSN: 1097-0193</identifier><identifier>DOI: 10.1002/hbm.21280</identifier><identifier>PMID: 21520347</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Adult ; Age Factors ; Attention - physiology ; Biological and medical sciences ; Brain - physiology ; Brain Mapping - methods ; Child ; Child, Preschool ; children ; Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases ; development ; Female ; functional connectivity ; functional MRI ; Humans ; Investigative techniques, diagnostic techniques (general aspects) ; Magnetic Resonance Imaging - methods ; Male ; Medical sciences ; Nerve Net - physiology ; Nervous system ; Neurology ; Radiodiagnosis. Nmr imagery. Nmr spectrometry ; Rest - physiology ; resting state ; resting state networks ; Young Adult</subject><ispartof>Human brain mapping, 2012-05, Vol.33 (5), p.1189-1201</ispartof><rights>Copyright © 2011 Wiley‐Liss, Inc.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2011 Wiley-Liss, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5760-587dc26e715fc6173e90e2f058612017633b0de6ffe084a0e7f7b7755ce40a6e3</citedby><cites>FETCH-LOGICAL-c5760-587dc26e715fc6173e90e2f058612017633b0de6ffe084a0e7f7b7755ce40a6e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6870031/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6870031/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,1417,27924,27925,45574,45575,53791,53793</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=25777249$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21520347$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>de Bie, Henrica M.A.</creatorcontrib><creatorcontrib>Boersma, Maria</creatorcontrib><creatorcontrib>Adriaanse, Sofie</creatorcontrib><creatorcontrib>Veltman, Dick J.</creatorcontrib><creatorcontrib>Wink, Alle Meije</creatorcontrib><creatorcontrib>Roosendaal, Stefan D.</creatorcontrib><creatorcontrib>Barkhof, Frederik</creatorcontrib><creatorcontrib>Stam, Cornelis J.</creatorcontrib><creatorcontrib>Oostrom, Kim J.</creatorcontrib><creatorcontrib>Delemarre-van de Waal, Henriette A.</creatorcontrib><creatorcontrib>Sanz-Arigita, Ernesto J.</creatorcontrib><title>Resting-state networks in awake five- to eight-year old children</title><title>Human brain mapping</title><addtitle>Hum. Brain Mapp</addtitle><description>During the first 6–7 years of life children undergo a period of major neurocognitive development. Higher‐order cognitive functions such as executive control of attention, encoding and retrieving of stored information and goal‐directed behavior are present but less developed compared to older individuals. There is only very limited information from functional magnetic resonance imaging (fMRI) studies about the level of organization of functional networks in children in the early school period. In this study we perform continuous resting‐state functional connectivity MRI in 5‐ to 8‐year‐old children in an awake state to identify and characterize resting‐state networks (RSNs). Temporal concatenation independent component analysis (ICA) approach was applied to analyze the data. We identified 14 components consisting of regions known to be involved in visual and auditory processing, motor function, attention control, memory, and the default mode network (DMN). Most networks, in particular those supporting basic motor function and sensory related processing, had a robust functional organization similar to mature adult patterns. In contrast, the DMN and other RSNs involved in higher‐order cognitive functions had immature characteristics, revealing incomplete and fragmented patterns indicating less developed functional connectivity. We therefore conclude that the DMN and other RSNs involved in higher order cognitive functioning are detectable, yet in an immature state, at an age when these cognitive abilities are mastered. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.</description><subject>Adult</subject><subject>Age Factors</subject><subject>Attention - physiology</subject><subject>Biological and medical sciences</subject><subject>Brain - physiology</subject><subject>Brain Mapping - methods</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>children</subject><subject>Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases</subject><subject>development</subject><subject>Female</subject><subject>functional connectivity</subject><subject>functional MRI</subject><subject>Humans</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Nerve Net - physiology</subject><subject>Nervous system</subject><subject>Neurology</subject><subject>Radiodiagnosis. Nmr imagery. Nmr spectrometry</subject><subject>Rest - physiology</subject><subject>resting state</subject><subject>resting state networks</subject><subject>Young Adult</subject><issn>1065-9471</issn><issn>1097-0193</issn><issn>1097-0193</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kVtvEzEQhS0EoqXwwB9AKyGEeNh2xl7buy8VENGbCggE6qPleGcTN5t1sTcN-ffdkDRcJJ5mpPnmzBkdxp4jHCIAP5qO54cceQkP2D5CpXPASjxc90rmVaFxjz1J6RoAUQI-ZnscJQdR6H329iul3neTPPW2p6yjfhniLGW-y-zSzihr_C3lWR8y8pNpn6_Ixiy0deamvq0jdU_Zo8a2iZ5t6wH7fvLh2-gsv_x8ej56d5k7qRXkstS144o0ysYp1IIqIN6ALBVyQK2EGENNqmkIysIC6UaPtZbSUQFWkThgxxvdm8V4TrWjro-2NTfRz21cmWC9-XvS-amZhFujSg0gcBB4vRWI4cdi-NrMfXLUtrajsEimqoRAJUo-kC__Ia_DInbDdwblYF0qwDX1ZkO5GFKK1Oy8IJh1LGaIxfyKZWBf_Gl-R97nMACvtoBNzrZNtJ3z6Tcntda8qAbuaMMtfUur_180Z-8_3p_ONxs-9fRzt2HjzCgttDRXn04NXJRQXvGR-SLuAJOKsTk</recordid><startdate>201205</startdate><enddate>201205</enddate><creator>de Bie, Henrica M.A.</creator><creator>Boersma, Maria</creator><creator>Adriaanse, Sofie</creator><creator>Veltman, Dick J.</creator><creator>Wink, Alle Meije</creator><creator>Roosendaal, Stefan D.</creator><creator>Barkhof, Frederik</creator><creator>Stam, Cornelis J.</creator><creator>Oostrom, Kim J.</creator><creator>Delemarre-van de Waal, Henriette A.</creator><creator>Sanz-Arigita, Ernesto J.</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>Wiley-Liss</general><general>John Wiley & Sons, Inc</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QR</scope><scope>7TK</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>201205</creationdate><title>Resting-state networks in awake five- to eight-year old children</title><author>de Bie, Henrica M.A. ; Boersma, Maria ; Adriaanse, Sofie ; Veltman, Dick J. ; Wink, Alle Meije ; Roosendaal, Stefan D. ; Barkhof, Frederik ; Stam, Cornelis J. ; Oostrom, Kim J. ; Delemarre-van de Waal, Henriette A. ; Sanz-Arigita, Ernesto J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5760-587dc26e715fc6173e90e2f058612017633b0de6ffe084a0e7f7b7755ce40a6e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Adult</topic><topic>Age Factors</topic><topic>Attention - physiology</topic><topic>Biological and medical sciences</topic><topic>Brain - physiology</topic><topic>Brain Mapping - methods</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>children</topic><topic>Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases</topic><topic>development</topic><topic>Female</topic><topic>functional connectivity</topic><topic>functional MRI</topic><topic>Humans</topic><topic>Investigative techniques, diagnostic techniques (general aspects)</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Nerve Net - physiology</topic><topic>Nervous system</topic><topic>Neurology</topic><topic>Radiodiagnosis. Nmr imagery. Nmr spectrometry</topic><topic>Rest - physiology</topic><topic>resting state</topic><topic>resting state networks</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Bie, Henrica M.A.</creatorcontrib><creatorcontrib>Boersma, Maria</creatorcontrib><creatorcontrib>Adriaanse, Sofie</creatorcontrib><creatorcontrib>Veltman, Dick J.</creatorcontrib><creatorcontrib>Wink, Alle Meije</creatorcontrib><creatorcontrib>Roosendaal, Stefan D.</creatorcontrib><creatorcontrib>Barkhof, Frederik</creatorcontrib><creatorcontrib>Stam, Cornelis J.</creatorcontrib><creatorcontrib>Oostrom, Kim J.</creatorcontrib><creatorcontrib>Delemarre-van de Waal, Henriette A.</creatorcontrib><creatorcontrib>Sanz-Arigita, Ernesto J.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Human brain mapping</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Bie, Henrica M.A.</au><au>Boersma, Maria</au><au>Adriaanse, Sofie</au><au>Veltman, Dick J.</au><au>Wink, Alle Meije</au><au>Roosendaal, Stefan D.</au><au>Barkhof, Frederik</au><au>Stam, Cornelis J.</au><au>Oostrom, Kim J.</au><au>Delemarre-van de Waal, Henriette A.</au><au>Sanz-Arigita, Ernesto J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Resting-state networks in awake five- to eight-year old children</atitle><jtitle>Human brain mapping</jtitle><addtitle>Hum. Brain Mapp</addtitle><date>2012-05</date><risdate>2012</risdate><volume>33</volume><issue>5</issue><spage>1189</spage><epage>1201</epage><pages>1189-1201</pages><issn>1065-9471</issn><issn>1097-0193</issn><eissn>1097-0193</eissn><abstract>During the first 6–7 years of life children undergo a period of major neurocognitive development. Higher‐order cognitive functions such as executive control of attention, encoding and retrieving of stored information and goal‐directed behavior are present but less developed compared to older individuals. There is only very limited information from functional magnetic resonance imaging (fMRI) studies about the level of organization of functional networks in children in the early school period. In this study we perform continuous resting‐state functional connectivity MRI in 5‐ to 8‐year‐old children in an awake state to identify and characterize resting‐state networks (RSNs). Temporal concatenation independent component analysis (ICA) approach was applied to analyze the data. We identified 14 components consisting of regions known to be involved in visual and auditory processing, motor function, attention control, memory, and the default mode network (DMN). Most networks, in particular those supporting basic motor function and sensory related processing, had a robust functional organization similar to mature adult patterns. In contrast, the DMN and other RSNs involved in higher‐order cognitive functions had immature characteristics, revealing incomplete and fragmented patterns indicating less developed functional connectivity. We therefore conclude that the DMN and other RSNs involved in higher order cognitive functioning are detectable, yet in an immature state, at an age when these cognitive abilities are mastered. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><pmid>21520347</pmid><doi>10.1002/hbm.21280</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Age Factors Attention - physiology Biological and medical sciences Brain - physiology Brain Mapping - methods Child Child, Preschool children Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases development Female functional connectivity functional MRI Humans Investigative techniques, diagnostic techniques (general aspects) Magnetic Resonance Imaging - methods Male Medical sciences Nerve Net - physiology Nervous system Neurology Radiodiagnosis. Nmr imagery. Nmr spectrometry Rest - physiology resting state resting state networks Young Adult |
title | Resting-state networks in awake five- to eight-year old children |
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