Differences in the functional brain architecture of sustained attention and working memory in youth and adults
Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predicto...
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| Veröffentlicht in: | PLoS biology 2022-12, Vol.20 (12), p.e3001938 |
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| creator | Kardan, Omid Stier, Andrew J Cardenas-Iniguez, Carlos Schertz, Kathryn E Pruin, Julia C Deng, Yuting Chamberlain, Taylor Meredith, Wesley J Zhang, Xihan Bowman, Jillian E Lakhtakia, Tanvi Tindel, Lucy Avery, Emily W Lin, Qi Yoo, Kwangsun Chun, Marvin M Berman, Marc G Rosenberg, Monica D |
| description | Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA. |
| doi_str_mv | 10.1371/journal.pbio.3001938 |
| format | Article |
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We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. 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Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Kardan et al 2022 Kardan et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c695t-337ffa87769085513c950cdfc8245afc22b62b67daf8b86ae1f2091540bbbbbf3</citedby><cites>FETCH-LOGICAL-c695t-337ffa87769085513c950cdfc8245afc22b62b67daf8b86ae1f2091540bbbbbf3</cites><orcidid>0000-0003-4187-5228</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815648/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815648/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36542658$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Cohen Kadosh, Roi</contributor><creatorcontrib>Kardan, Omid</creatorcontrib><creatorcontrib>Stier, Andrew J</creatorcontrib><creatorcontrib>Cardenas-Iniguez, Carlos</creatorcontrib><creatorcontrib>Schertz, Kathryn E</creatorcontrib><creatorcontrib>Pruin, Julia C</creatorcontrib><creatorcontrib>Deng, Yuting</creatorcontrib><creatorcontrib>Chamberlain, Taylor</creatorcontrib><creatorcontrib>Meredith, Wesley J</creatorcontrib><creatorcontrib>Zhang, Xihan</creatorcontrib><creatorcontrib>Bowman, Jillian E</creatorcontrib><creatorcontrib>Lakhtakia, Tanvi</creatorcontrib><creatorcontrib>Tindel, Lucy</creatorcontrib><creatorcontrib>Avery, Emily W</creatorcontrib><creatorcontrib>Lin, Qi</creatorcontrib><creatorcontrib>Yoo, Kwangsun</creatorcontrib><creatorcontrib>Chun, Marvin M</creatorcontrib><creatorcontrib>Berman, Marc G</creatorcontrib><creatorcontrib>Rosenberg, Monica D</creatorcontrib><title>Differences in the functional brain architecture of sustained attention and working memory in youth and adults</title><title>PLoS biology</title><addtitle>PLoS Biol</addtitle><description>Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. 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Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.</description><subject>Accuracy</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Adults</subject><subject>Attention</subject><subject>Behavior</subject><subject>Biology and Life Sciences</subject><subject>Brain</subject><subject>Brain architecture</subject><subject>Brain Mapping - methods</subject><subject>Child</subject><subject>Children</subject><subject>Children & youth</subject><subject>Cognition & reasoning</subject><subject>Cognitive development</subject><subject>Computer and Information Sciences</subject><subject>Computer architecture</subject><subject>Humans</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Medicine and Health Sciences</subject><subject>Memory</subject><subject>Memory, Short-Term</subject><subject>Neural 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Roi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differences in the functional brain architecture of sustained attention and working memory in youth and adults</atitle><jtitle>PLoS biology</jtitle><addtitle>PLoS Biol</addtitle><date>2022-12-21</date><risdate>2022</risdate><volume>20</volume><issue>12</issue><spage>e3001938</spage><pages>e3001938-</pages><issn>1545-7885</issn><issn>1544-9173</issn><eissn>1545-7885</eissn><abstract>Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>36542658</pmid><doi>10.1371/journal.pbio.3001938</doi><orcidid>https://orcid.org/0000-0003-4187-5228</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central |
| subjects | Accuracy Adolescent Adult Adults Attention Behavior Biology and Life Sciences Brain Brain architecture Brain Mapping - methods Child Children Children & youth Cognition & reasoning Cognitive development Computer and Information Sciences Computer architecture Humans Magnetic resonance imaging Magnetic Resonance Imaging - methods Medicine and Health Sciences Memory Memory, Short-Term Neural networks Neurosciences Performance prediction Physical Sciences Physiological aspects Psychological aspects Research and Analysis Methods Short term memory Social Sciences Structure Teenagers Youth |
| title | Differences in the functional brain architecture of sustained attention and working memory in youth and adults |
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