Structural architecture supports functional organization in the human aging brain at a regionwise and network level
Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age‐related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (...
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Veröffentlicht in: | Human brain mapping 2016-07, Vol.37 (7), p.2645-2661 |
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creator | Zimmermann, Joelle Ritter, Petra Shen, Kelly Rothmeier, Simon Schirner, Michael McIntosh, Anthony R. |
description | Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age‐related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC–FC coupling in human aging as inferred from resting‐state blood oxygen‐level dependent functional magnetic resonance imaging and diffusion‐weighted imaging in a sample of 47 adults with an age range of 18–82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age‐dependency of regionwise SC–FC coupling and network‐level SC–FC relations. A specific pattern of SC–FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC–FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645–2661, 2016. © 2016 Wiley Periodicals, Inc. |
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Accordingly, age‐related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC–FC coupling in human aging as inferred from resting‐state blood oxygen‐level dependent functional magnetic resonance imaging and diffusion‐weighted imaging in a sample of 47 adults with an age range of 18–82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age‐dependency of regionwise SC–FC coupling and network‐level SC–FC relations. A specific pattern of SC–FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC–FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645–2661, 2016. © 2016 Wiley Periodicals, Inc.</description><identifier>ISSN: 1065-9471</identifier><identifier>EISSN: 1097-0193</identifier><identifier>DOI: 10.1002/hbm.23200</identifier><identifier>PMID: 27041212</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Adolescent ; Adult ; Aged ; Aged, 80 and over ; aging ; Aging - pathology ; Aging - physiology ; Brain - diagnostic imaging ; Brain - physiology ; brain connectivity ; Brain Mapping ; Cerebrovascular Circulation - physiology ; Female ; function ; Humans ; Image Processing, Computer-Assisted ; Magnetic Resonance Imaging ; Male ; Middle Aged ; Neural Pathways - diagnostic imaging ; Neural Pathways - physiology ; Oxygen - blood ; Regression Analysis ; Rest ; resting-state network ; structure ; Young Adult</subject><ispartof>Human brain mapping, 2016-07, Vol.37 (7), p.2645-2661</ispartof><rights>2016 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4800-a9ed78086e22eaa0f61f43f955f062979bbc4631f987417c7757b4b5cedb9e113</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6867479/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6867479/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,1417,27924,27925,45574,45575,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27041212$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zimmermann, Joelle</creatorcontrib><creatorcontrib>Ritter, Petra</creatorcontrib><creatorcontrib>Shen, Kelly</creatorcontrib><creatorcontrib>Rothmeier, Simon</creatorcontrib><creatorcontrib>Schirner, Michael</creatorcontrib><creatorcontrib>McIntosh, Anthony R.</creatorcontrib><title>Structural architecture supports functional organization in the human aging brain at a regionwise and network level</title><title>Human brain mapping</title><addtitle>Hum. Brain Mapp</addtitle><description>Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age‐related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC–FC coupling in human aging as inferred from resting‐state blood oxygen‐level dependent functional magnetic resonance imaging and diffusion‐weighted imaging in a sample of 47 adults with an age range of 18–82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age‐dependency of regionwise SC–FC coupling and network‐level SC–FC relations. A specific pattern of SC–FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC–FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645–2661, 2016. © 2016 Wiley Periodicals, Inc.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>aging</subject><subject>Aging - pathology</subject><subject>Aging - physiology</subject><subject>Brain - diagnostic imaging</subject><subject>Brain - physiology</subject><subject>brain connectivity</subject><subject>Brain Mapping</subject><subject>Cerebrovascular Circulation - physiology</subject><subject>Female</subject><subject>function</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Neural Pathways - diagnostic imaging</subject><subject>Neural Pathways - physiology</subject><subject>Oxygen - blood</subject><subject>Regression Analysis</subject><subject>Rest</subject><subject>resting-state network</subject><subject>structure</subject><subject>Young Adult</subject><issn>1065-9471</issn><issn>1097-0193</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkstu1DAUhiMEohdY8ALIEhs2aW3Hl3iDRCuYglqQKAjExnIyJ4nbxBlsp9Py9DgzZQRsWPlcvv_o2P6z7BnBRwRjetxVwxEtKMYPsn2ClcwxUcXDORY8V0ySvewghCuMCeGYPM72qMSMUEL3s3AZ_VTHyZseGV93NsKcAQrTajX6GFAzuTra0SVg9K1x9qeZU2Qdih2gbhqMQ6a1rkWVN6lqIjLIQ5ugtQ2AjFsiB3E9-mvUww30T7JHjekDPL0_D7Mvb998Pj3Lzz8u3p2-Ps9rVmKcGwVLWeJSAKVgDG4EaVjRKM4bLKiSqqpqJgrSqFIyImspuaxYxWtYVgoIKQ6zV9u5q6kaYFmDi-maeuXtYPydHo3Vf3ec7XQ73mhRCsmkSgNe3g_w448JQtSDDTX0vXEwTkGTeTusGOH_R6USoqQcs4S--Ae9Gief3ndD8ZIIWhaJev7n8rutf39dAo63wNr2cLfrE6xnT-jkCb3xhD47udgESZFvFTZEuN0pjL_WQhaS668fFlp-Kr5_u3x_oRfFL9CZufg</recordid><startdate>201607</startdate><enddate>201607</enddate><creator>Zimmermann, Joelle</creator><creator>Ritter, Petra</creator><creator>Shen, Kelly</creator><creator>Rothmeier, Simon</creator><creator>Schirner, Michael</creator><creator>McIntosh, Anthony R.</creator><general>Blackwell Publishing Ltd</general><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</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>201607</creationdate><title>Structural architecture supports functional organization in the human aging brain at a regionwise and network level</title><author>Zimmermann, Joelle ; Ritter, Petra ; Shen, Kelly ; Rothmeier, Simon ; Schirner, Michael ; McIntosh, Anthony R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4800-a9ed78086e22eaa0f61f43f955f062979bbc4631f987417c7757b4b5cedb9e113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>aging</topic><topic>Aging - pathology</topic><topic>Aging - physiology</topic><topic>Brain - diagnostic imaging</topic><topic>Brain - physiology</topic><topic>brain connectivity</topic><topic>Brain Mapping</topic><topic>Cerebrovascular Circulation - physiology</topic><topic>Female</topic><topic>function</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Neural Pathways - diagnostic imaging</topic><topic>Neural Pathways - physiology</topic><topic>Oxygen - blood</topic><topic>Regression Analysis</topic><topic>Rest</topic><topic>resting-state network</topic><topic>structure</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zimmermann, Joelle</creatorcontrib><creatorcontrib>Ritter, Petra</creatorcontrib><creatorcontrib>Shen, Kelly</creatorcontrib><creatorcontrib>Rothmeier, Simon</creatorcontrib><creatorcontrib>Schirner, Michael</creatorcontrib><creatorcontrib>McIntosh, Anthony R.</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</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>Zimmermann, Joelle</au><au>Ritter, Petra</au><au>Shen, Kelly</au><au>Rothmeier, Simon</au><au>Schirner, Michael</au><au>McIntosh, Anthony R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Structural architecture supports functional organization in the human aging brain at a regionwise and network level</atitle><jtitle>Human brain mapping</jtitle><addtitle>Hum. Brain Mapp</addtitle><date>2016-07</date><risdate>2016</risdate><volume>37</volume><issue>7</issue><spage>2645</spage><epage>2661</epage><pages>2645-2661</pages><issn>1065-9471</issn><eissn>1097-0193</eissn><abstract>Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age‐related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC–FC coupling in human aging as inferred from resting‐state blood oxygen‐level dependent functional magnetic resonance imaging and diffusion‐weighted imaging in a sample of 47 adults with an age range of 18–82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age‐dependency of regionwise SC–FC coupling and network‐level SC–FC relations. A specific pattern of SC–FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC–FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645–2661, 2016. © 2016 Wiley Periodicals, Inc.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>27041212</pmid><doi>10.1002/hbm.23200</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Aged Aged, 80 and over aging Aging - pathology Aging - physiology Brain - diagnostic imaging Brain - physiology brain connectivity Brain Mapping Cerebrovascular Circulation - physiology Female function Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Middle Aged Neural Pathways - diagnostic imaging Neural Pathways - physiology Oxygen - blood Regression Analysis Rest resting-state network structure Young Adult |
title | Structural architecture supports functional organization in the human aging brain at a regionwise and network level |
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