Effective connectivity during haptic perception: a study using Granger causality analysis of functional magnetic resonance imaging data.
Identifieur interne : 001504 ( PubMed/Corpus ); précédent : 001503; suivant : 001505Effective connectivity during haptic perception: a study using Granger causality analysis of functional magnetic resonance imaging data.
Auteurs : Gopikrishna Deshpande ; Xiaoping Hu ; Randall Stilla ; K. SathianSource :
- NeuroImage [ 1053-8119 ] ; 2008.
English descriptors
- KwdEn :
- Adult, Algorithms, Female, Form Perception (physiology), Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging (methods), Male, Nerve Net (physiology), Parietal Lobe (physiology), Perception (physiology), Prefrontal Cortex (physiology), Psychomotor Performance (physiology), Recruitment, Neurophysiological (physiology), Somatosensory Cortex (physiology), Touch (physiology), Visual Cortex (physiology), Visual Perception (physiology).
- MESH :
- methods : Magnetic Resonance Imaging.
- physiology : Form Perception, Nerve Net, Parietal Lobe, Perception, Prefrontal Cortex, Psychomotor Performance, Recruitment, Neurophysiological, Somatosensory Cortex, Touch, Visual Cortex, Visual Perception.
- Adult, Algorithms, Female, Humans, Image Processing, Computer-Assisted, Male.
Abstract
Although it is accepted that visual cortical areas are recruited during touch, it remains uncertain whether this depends on top-down inputs mediating visual imagery or engagement of modality-independent representations by bottom-up somatosensory inputs. Here we addressed this by examining effective connectivity in humans during haptic perception of shape and texture with the right hand. Multivariate Granger causality analysis of functional magnetic resonance imaging (fMRI) data was conducted on a network of regions that were shape- or texture-selective. A novel network reduction procedure was employed to eliminate connections that did not contribute significantly to overall connectivity. Effective connectivity during haptic perception was found to involve a variety of interactions between areas generally regarded as somatosensory, multisensory, visual and motor, emphasizing flexible cooperation between different brain regions rather than rigid functional separation. The left postcentral sulcus (PCS), left precentral gyrus and right posterior insula were important sources of connections in the network. Bottom-up somatosensory inputs from the left PCS and right posterior insula fed into visual cortical areas, both the shape-selective right lateral occipital complex (LOC) and the texture-selective right medial occipital cortex (probable V2). In addition, top-down inputs from left postero-supero-medial parietal cortex influenced the right LOC. Thus, there is strong evidence for the bottom-up somatosensory inputs predicted by models of visual cortical areas as multisensory processors and suggestive evidence for top-down parietal (but not prefrontal) inputs that could mediate visual imagery. This is consistent with modality-independent representations accessible through both bottom-up sensory inputs and top-down processes such as visual imagery.
DOI: 10.1016/j.neuroimage.2008.01.044
PubMed: 18329290
Links to Exploration step
pubmed:18329290Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Effective connectivity during haptic perception: a study using Granger causality analysis of functional magnetic resonance imaging data.</title><author><name sortKey="Deshpande, Gopikrishna" sort="Deshpande, Gopikrishna" uniqKey="Deshpande G" first="Gopikrishna" last="Deshpande">Gopikrishna Deshpande</name><affiliation><nlm:affiliation>Coulter Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, GA 30322, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Hu, Xiaoping" sort="Hu, Xiaoping" uniqKey="Hu X" first="Xiaoping" last="Hu">Xiaoping Hu</name></author><author><name sortKey="Stilla, Randall" sort="Stilla, Randall" uniqKey="Stilla R" first="Randall" last="Stilla">Randall Stilla</name></author><author><name sortKey="Sathian, K" sort="Sathian, K" uniqKey="Sathian K" first="K" last="Sathian">K. Sathian</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2008">2008</date><idno type="doi">10.1016/j.neuroimage.2008.01.044</idno><idno type="RBID">pubmed:18329290</idno><idno type="pmid">18329290</idno><idno type="wicri:Area/PubMed/Corpus">001504</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Effective connectivity during haptic perception: a study using Granger causality analysis of functional magnetic resonance imaging data.</title><author><name sortKey="Deshpande, Gopikrishna" sort="Deshpande, Gopikrishna" uniqKey="Deshpande G" first="Gopikrishna" last="Deshpande">Gopikrishna Deshpande</name><affiliation><nlm:affiliation>Coulter Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, GA 30322, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Hu, Xiaoping" sort="Hu, Xiaoping" uniqKey="Hu X" first="Xiaoping" last="Hu">Xiaoping Hu</name></author><author><name sortKey="Stilla, Randall" sort="Stilla, Randall" uniqKey="Stilla R" first="Randall" last="Stilla">Randall Stilla</name></author><author><name sortKey="Sathian, K" sort="Sathian, K" uniqKey="Sathian K" first="K" last="Sathian">K. Sathian</name></author></analytic><series><title level="j">NeuroImage</title><idno type="ISSN">1053-8119</idno><imprint><date when="2008" type="published">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Algorithms</term><term>Female</term><term>Form Perception (physiology)</term><term>Humans</term><term>Image Processing, Computer-Assisted</term><term>Magnetic Resonance Imaging (methods)</term><term>Male</term><term>Nerve Net (physiology)</term><term>Parietal Lobe (physiology)</term><term>Perception (physiology)</term><term>Prefrontal Cortex (physiology)</term><term>Psychomotor Performance (physiology)</term><term>Recruitment, Neurophysiological (physiology)</term><term>Somatosensory Cortex (physiology)</term><term>Touch (physiology)</term><term>Visual Cortex (physiology)</term><term>Visual Perception (physiology)</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Magnetic Resonance Imaging</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Form Perception</term><term>Nerve Net</term><term>Parietal Lobe</term><term>Perception</term><term>Prefrontal Cortex</term><term>Psychomotor Performance</term><term>Recruitment, Neurophysiological</term><term>Somatosensory Cortex</term><term>Touch</term><term>Visual Cortex</term><term>Visual Perception</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Algorithms</term><term>Female</term><term>Humans</term><term>Image Processing, Computer-Assisted</term><term>Male</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Although it is accepted that visual cortical areas are recruited during touch, it remains uncertain whether this depends on top-down inputs mediating visual imagery or engagement of modality-independent representations by bottom-up somatosensory inputs. Here we addressed this by examining effective connectivity in humans during haptic perception of shape and texture with the right hand. Multivariate Granger causality analysis of functional magnetic resonance imaging (fMRI) data was conducted on a network of regions that were shape- or texture-selective. A novel network reduction procedure was employed to eliminate connections that did not contribute significantly to overall connectivity. Effective connectivity during haptic perception was found to involve a variety of interactions between areas generally regarded as somatosensory, multisensory, visual and motor, emphasizing flexible cooperation between different brain regions rather than rigid functional separation. The left postcentral sulcus (PCS), left precentral gyrus and right posterior insula were important sources of connections in the network. Bottom-up somatosensory inputs from the left PCS and right posterior insula fed into visual cortical areas, both the shape-selective right lateral occipital complex (LOC) and the texture-selective right medial occipital cortex (probable V2). In addition, top-down inputs from left postero-supero-medial parietal cortex influenced the right LOC. Thus, there is strong evidence for the bottom-up somatosensory inputs predicted by models of visual cortical areas as multisensory processors and suggestive evidence for top-down parietal (but not prefrontal) inputs that could mediate visual imagery. This is consistent with modality-independent representations accessible through both bottom-up sensory inputs and top-down processes such as visual imagery.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">18329290</PMID><DateCreated><Year>2008</Year><Month>04</Month><Day>14</Day></DateCreated><DateCompleted><Year>2008</Year><Month>06</Month><Day>23</Day></DateCompleted><DateRevised><Year>2014</Year><Month>09</Month><Day>15</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">1053-8119</ISSN><JournalIssue CitedMedium="Print"><Volume>40</Volume><Issue>4</Issue><PubDate><Year>2008</Year><Month>May</Month><Day>1</Day></PubDate></JournalIssue><Title>NeuroImage</Title><ISOAbbreviation>Neuroimage</ISOAbbreviation></Journal><ArticleTitle>Effective connectivity during haptic perception: a study using Granger causality analysis of functional magnetic resonance imaging data.</ArticleTitle><Pagination><MedlinePgn>1807-14</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.neuroimage.2008.01.044</ELocationID><Abstract><AbstractText>Although it is accepted that visual cortical areas are recruited during touch, it remains uncertain whether this depends on top-down inputs mediating visual imagery or engagement of modality-independent representations by bottom-up somatosensory inputs. Here we addressed this by examining effective connectivity in humans during haptic perception of shape and texture with the right hand. Multivariate Granger causality analysis of functional magnetic resonance imaging (fMRI) data was conducted on a network of regions that were shape- or texture-selective. A novel network reduction procedure was employed to eliminate connections that did not contribute significantly to overall connectivity. Effective connectivity during haptic perception was found to involve a variety of interactions between areas generally regarded as somatosensory, multisensory, visual and motor, emphasizing flexible cooperation between different brain regions rather than rigid functional separation. The left postcentral sulcus (PCS), left precentral gyrus and right posterior insula were important sources of connections in the network. Bottom-up somatosensory inputs from the left PCS and right posterior insula fed into visual cortical areas, both the shape-selective right lateral occipital complex (LOC) and the texture-selective right medial occipital cortex (probable V2). In addition, top-down inputs from left postero-supero-medial parietal cortex influenced the right LOC. Thus, there is strong evidence for the bottom-up somatosensory inputs predicted by models of visual cortical areas as multisensory processors and suggestive evidence for top-down parietal (but not prefrontal) inputs that could mediate visual imagery. This is consistent with modality-independent representations accessible through both bottom-up sensory inputs and top-down processes such as visual imagery.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Deshpande</LastName><ForeName>Gopikrishna</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Coulter Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, GA 30322, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hu</LastName><ForeName>Xiaoping</ForeName><Initials>X</Initials></Author><Author ValidYN="Y"><LastName>Stilla</LastName><ForeName>Randall</ForeName><Initials>R</Initials></Author><Author ValidYN="Y"><LastName>Sathian</LastName><ForeName>K</ForeName><Initials>K</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>K24 EY017332</GrantID><Acronym>EY</Acronym><Agency>NEI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>K24 EY017332-02</GrantID><Acronym>EY</Acronym><Agency>NEI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>K24 EY17332</GrantID><Acronym>EY</Acronym><Agency>NEI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 EB002009</GrantID><Acronym>EB</Acronym><Agency>NIBIB NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 EB002009</GrantID><Acronym>EB</Acronym><Agency>NIBIB NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 EB002009-12</GrantID><Acronym>EB</Acronym><Agency>NIBIB NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 EY012440</GrantID><Acronym>EY</Acronym><Agency>NEI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 EY012440-07</GrantID><Acronym>EY</Acronym><Agency>NEI NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>R01 EY12440</GrantID><Acronym>EY</Acronym><Agency>NEI NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2008</Year><Month>02</Month><Day>09</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Neuroimage</MedlineTA><NlmUniqueID>9215515</NlmUniqueID><ISSNLinking>1053-8119</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2000 Mar;11(3):188-202</RefSource><PMID Version="1">10694461</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Neuroimage. 2000 Jun;11(6 Pt 1):684-96</RefSource><PMID 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