Structurally-constrained relationships between cognitive states in the human brain.
Identifieur interne : 002D16 ( PubMed/Corpus ); précédent : 002D15; suivant : 002D17Structurally-constrained relationships between cognitive states in the human brain.
Auteurs : Ann M. Hermundstad ; Kevin S. Brown ; Danielle S. Bassett ; Elissa M. Aminoff ; Amy Frithsen ; Arianne Johnson ; Christine M. Tipper ; Michael B. Miller ; Scott T. Grafton ; Jean M. CarlsonSource :
- PLoS computational biology [ 1553-7358 ] ; 2014.
English descriptors
- KwdEn :
- Attention (physiology), Brain (anatomy & histology), Brain (physiology), Cognition (physiology), Computer Simulation, Connectome (methods), Humans, Memory (physiology), Models, Anatomic, Models, Neurological, Nerve Net (anatomy & histology), Nerve Net (physiology), White Matter (anatomy & histology), White Matter (physiology).
- MESH :
- anatomy & histology : Brain, Nerve Net, White Matter.
- methods : Connectome.
- physiology : Attention, Brain, Cognition, Memory, Nerve Net, White Matter.
- Computer Simulation, Humans, Models, Anatomic, Models, Neurological.
Abstract
The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD) signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function.
DOI: 10.1371/journal.pcbi.1003591
PubMed: 24830758
Links to Exploration step
pubmed:24830758Le document en format XML
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Brown</name><affiliation><nlm:affiliation>Department of Biomedical Engineering, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Physics, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Marine Sciences, University of Connecticut, Groton, Conneticutt, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Bassett, Danielle S" sort="Bassett, Danielle S" uniqKey="Bassett D" first="Danielle S" last="Bassett">Danielle S. 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Hermundstad</name><affiliation><nlm:affiliation>Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America; Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Brown, Kevin S" sort="Brown, Kevin S" uniqKey="Brown K" first="Kevin S" last="Brown">Kevin S. Brown</name><affiliation><nlm:affiliation>Department of Biomedical Engineering, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Physics, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Marine Sciences, University of Connecticut, Groton, Conneticutt, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Bassett, Danielle S" sort="Bassett, Danielle S" uniqKey="Bassett D" first="Danielle S" last="Bassett">Danielle S. Bassett</name><affiliation><nlm:affiliation>Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America; Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America; Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Aminoff, Elissa M" sort="Aminoff, Elissa M" uniqKey="Aminoff E" first="Elissa M" last="Aminoff">Elissa M. Aminoff</name><affiliation><nlm:affiliation>Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Frithsen, Amy" sort="Frithsen, Amy" uniqKey="Frithsen A" first="Amy" last="Frithsen">Amy Frithsen</name><affiliation><nlm:affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Johnson, Arianne" sort="Johnson, Arianne" uniqKey="Johnson A" first="Arianne" last="Johnson">Arianne Johnson</name><affiliation><nlm:affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Tipper, Christine M" sort="Tipper, Christine M" uniqKey="Tipper C" first="Christine M" last="Tipper">Christine M. Tipper</name><affiliation><nlm:affiliation>Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.</nlm:affiliation></affiliation></author><author><name sortKey="Miller, Michael B" sort="Miller, Michael B" uniqKey="Miller M" first="Michael B" last="Miller">Michael B. Miller</name><affiliation><nlm:affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Grafton, Scott T" sort="Grafton, Scott T" uniqKey="Grafton S" first="Scott T" last="Grafton">Scott T. Grafton</name><affiliation><nlm:affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</nlm:affiliation></affiliation></author><author><name sortKey="Carlson, Jean M" sort="Carlson, Jean M" uniqKey="Carlson J" first="Jean M" last="Carlson">Jean M. Carlson</name><affiliation><nlm:affiliation>Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America.</nlm:affiliation></affiliation></author></analytic><series><title level="j">PLoS computational biology</title><idno type="eISSN">1553-7358</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Attention (physiology)</term><term>Brain (anatomy & histology)</term><term>Brain (physiology)</term><term>Cognition (physiology)</term><term>Computer Simulation</term><term>Connectome (methods)</term><term>Humans</term><term>Memory (physiology)</term><term>Models, Anatomic</term><term>Models, Neurological</term><term>Nerve Net (anatomy & histology)</term><term>Nerve Net (physiology)</term><term>White Matter (anatomy & histology)</term><term>White Matter (physiology)</term></keywords><keywords scheme="MESH" qualifier="anatomy & histology" xml:lang="en"><term>Brain</term><term>Nerve Net</term><term>White Matter</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Connectome</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Attention</term><term>Brain</term><term>Cognition</term><term>Memory</term><term>Nerve Net</term><term>White Matter</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Humans</term><term>Models, Anatomic</term><term>Models, Neurological</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD) signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">24830758</PMID><DateCreated><Year>2014</Year><Month>05</Month><Day>16</Day></DateCreated><DateCompleted><Year>2015</Year><Month>05</Month><Day>21</Day></DateCompleted><DateRevised><Year>2017</Year><Month>02</Month><Day>20</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1553-7358</ISSN><JournalIssue CitedMedium="Internet"><Volume>10</Volume><Issue>5</Issue><PubDate><Year>2014</Year><Month>May</Month></PubDate></JournalIssue><Title>PLoS computational biology</Title><ISOAbbreviation>PLoS Comput. Biol.</ISOAbbreviation></Journal><ArticleTitle>Structurally-constrained relationships between cognitive states in the human brain.</ArticleTitle><Pagination><MedlinePgn>e1003591</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pcbi.1003591</ELocationID><Abstract><AbstractText>The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD) signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Hermundstad</LastName><ForeName>Ann M</ForeName><Initials>AM</Initials><AffiliationInfo><Affiliation>Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America; Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Brown</LastName><ForeName>Kevin S</ForeName><Initials>KS</Initials><AffiliationInfo><Affiliation>Department of Biomedical Engineering, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Physics, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Conneticutt, United States of America; Department of Marine Sciences, University of Connecticut, Groton, Conneticutt, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bassett</LastName><ForeName>Danielle S</ForeName><Initials>DS</Initials><AffiliationInfo><Affiliation>Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America; Sage Center for the Study of the Mind, University of California, Santa Barbara, Santa Barbara, California, United States of America; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America; Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Aminoff</LastName><ForeName>Elissa M</ForeName><Initials>EM</Initials><AffiliationInfo><Affiliation>Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Frithsen</LastName><ForeName>Amy</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Johnson</LastName><ForeName>Arianne</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tipper</LastName><ForeName>Christine M</ForeName><Initials>CM</Initials><AffiliationInfo><Affiliation>Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Miller</LastName><ForeName>Michael B</ForeName><Initials>MB</Initials><AffiliationInfo><Affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Grafton</LastName><ForeName>Scott T</ForeName><Initials>ST</Initials><AffiliationInfo><Affiliation>Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Carlson</LastName><ForeName>Jean M</ForeName><Initials>JM</Initials><AffiliationInfo><Affiliation>Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>05</Month><Day>15</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS Comput Biol</MedlineTA><NlmUniqueID>101238922</NlmUniqueID><ISSNLinking>1553-734X</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Schizophr Bull. 2012 Mar;38(2):285-94</RefSource><PMID Version="1">20595202</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Cereb Cortex. 2009 Jan;19(1):72-8</RefSource><PMID 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histology</QualifierName><QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4022461</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2013</Year><Month>07</Month><Day>22</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>03</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>5</Month><Day>17</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>5</Month><Day>17</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>5</Month><Day>23</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">24830758</ArticleId><ArticleId IdType="doi">10.1371/journal.pcbi.1003591</ArticleId><ArticleId IdType="pii">PCOMPBIOL-D-13-01309</ArticleId><ArticleId IdType="pmc">PMC4022461</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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