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Influence of heart rate on the BOLD signal: The cardiac response function
It has previously been shown that low-frequency fluctuations in both respiratory volume and cardiac rate can induce changes in the blood-oxygen level dependent (BOLD) signal. Such physiological noise can obscure the detection of neural activation using fMRI, and it is therefore important to model an...
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Published in: | NeuroImage (Orlando, Fla.) Fla.), 2009-02, Vol.44 (3), p.857-869 |
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description | It has previously been shown that low-frequency fluctuations in both respiratory volume and cardiac rate can induce changes in the blood-oxygen level dependent (BOLD) signal. Such physiological noise can obscure the detection of neural activation using fMRI, and it is therefore important to model and remove the effects of this noise. While a hemodynamic response function relating respiratory variation (RV) and the BOLD signal has been described [Birn, R.M., Smith, M.A., Jones, T.B., Bandettini, P.A., 2008b. The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage 40, 644–654.], no such mapping for heart rate (HR) has been proposed. In the current study, the effects of RV and HR are simultaneously deconvolved from resting state fMRI. It is demonstrated that a convolution model including RV and HR can explain significantly more variance in gray matter BOLD signal than a model that includes RV alone, and an average HR response function is proposed that well characterizes our subject population. It is observed that the voxel-wise morphology of the deconvolved RV responses is preserved when HR is included in the model, and that its form is adequately modeled by Birn et al.'s previously-described respiration response function. Furthermore, it is shown that modeling out RV and HR can significantly alter functional connectivity maps of the default-mode network. |
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Such physiological noise can obscure the detection of neural activation using fMRI, and it is therefore important to model and remove the effects of this noise. While a hemodynamic response function relating respiratory variation (RV) and the BOLD signal has been described [Birn, R.M., Smith, M.A., Jones, T.B., Bandettini, P.A., 2008b. The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage 40, 644–654.], no such mapping for heart rate (HR) has been proposed. In the current study, the effects of RV and HR are simultaneously deconvolved from resting state fMRI. It is demonstrated that a convolution model including RV and HR can explain significantly more variance in gray matter BOLD signal than a model that includes RV alone, and an average HR response function is proposed that well characterizes our subject population. It is observed that the voxel-wise morphology of the deconvolved RV responses is preserved when HR is included in the model, and that its form is adequately modeled by Birn et al.'s previously-described respiration response function. Furthermore, it is shown that modeling out RV and HR can significantly alter functional connectivity maps of the default-mode network.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2008.09.029</identifier><identifier>PMID: 18951982</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; BOLD signal ; Brain - physiology ; Brain Mapping - methods ; Cardiovascular ; Deconvolution ; Evoked Potentials - physiology ; Female ; fMRI ; Gaussian process ; Heart rate ; Heart Rate - physiology ; Hemodynamic response ; Humans ; Magnetic Resonance Imaging - methods ; Male ; Noise ; Physiological noise ; Reproducibility of Results ; Respiration ; Sensitivity and Specificity ; Time series</subject><ispartof>NeuroImage (Orlando, Fla.), 2009-02, Vol.44 (3), p.857-869</ispartof><rights>2008 Elsevier Inc.</rights><rights>Copyright Elsevier Limited Feb 1, 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c602t-bfbe8bea9d15699f1de75480181dda06a00693a2bbfadc5d2d49591a575ca6553</citedby><cites>FETCH-LOGICAL-c602t-bfbe8bea9d15699f1de75480181dda06a00693a2bbfadc5d2d49591a575ca6553</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18951982$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chang, Catie</creatorcontrib><creatorcontrib>Cunningham, John P.</creatorcontrib><creatorcontrib>Glover, Gary H.</creatorcontrib><title>Influence of heart rate on the BOLD signal: The cardiac response function</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>It has previously been shown that low-frequency fluctuations in both respiratory volume and cardiac rate can induce changes in the blood-oxygen level dependent (BOLD) signal. Such physiological noise can obscure the detection of neural activation using fMRI, and it is therefore important to model and remove the effects of this noise. While a hemodynamic response function relating respiratory variation (RV) and the BOLD signal has been described [Birn, R.M., Smith, M.A., Jones, T.B., Bandettini, P.A., 2008b. The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage 40, 644–654.], no such mapping for heart rate (HR) has been proposed. In the current study, the effects of RV and HR are simultaneously deconvolved from resting state fMRI. It is demonstrated that a convolution model including RV and HR can explain significantly more variance in gray matter BOLD signal than a model that includes RV alone, and an average HR response function is proposed that well characterizes our subject population. It is observed that the voxel-wise morphology of the deconvolved RV responses is preserved when HR is included in the model, and that its form is adequately modeled by Birn et al.'s previously-described respiration response function. 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Cunningham, John P. ; Glover, Gary H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c602t-bfbe8bea9d15699f1de75480181dda06a00693a2bbfadc5d2d49591a575ca6553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Adult</topic><topic>BOLD signal</topic><topic>Brain - physiology</topic><topic>Brain Mapping - methods</topic><topic>Cardiovascular</topic><topic>Deconvolution</topic><topic>Evoked Potentials - physiology</topic><topic>Female</topic><topic>fMRI</topic><topic>Gaussian process</topic><topic>Heart rate</topic><topic>Heart Rate - physiology</topic><topic>Hemodynamic response</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Noise</topic><topic>Physiological noise</topic><topic>Reproducibility of Results</topic><topic>Respiration</topic><topic>Sensitivity and Specificity</topic><topic>Time series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chang, Catie</creatorcontrib><creatorcontrib>Cunningham, John P.</creatorcontrib><creatorcontrib>Glover, Gary H.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>NeuroImage (Orlando, Fla.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chang, Catie</au><au>Cunningham, John P.</au><au>Glover, Gary H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influence of heart rate on the BOLD signal: The cardiac response function</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2009-02-01</date><risdate>2009</risdate><volume>44</volume><issue>3</issue><spage>857</spage><epage>869</epage><pages>857-869</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract>It has previously been shown that low-frequency fluctuations in both respiratory volume and cardiac rate can induce changes in the blood-oxygen level dependent (BOLD) signal. Such physiological noise can obscure the detection of neural activation using fMRI, and it is therefore important to model and remove the effects of this noise. While a hemodynamic response function relating respiratory variation (RV) and the BOLD signal has been described [Birn, R.M., Smith, M.A., Jones, T.B., Bandettini, P.A., 2008b. The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage 40, 644–654.], no such mapping for heart rate (HR) has been proposed. In the current study, the effects of RV and HR are simultaneously deconvolved from resting state fMRI. It is demonstrated that a convolution model including RV and HR can explain significantly more variance in gray matter BOLD signal than a model that includes RV alone, and an average HR response function is proposed that well characterizes our subject population. It is observed that the voxel-wise morphology of the deconvolved RV responses is preserved when HR is included in the model, and that its form is adequately modeled by Birn et al.'s previously-described respiration response function. Furthermore, it is shown that modeling out RV and HR can significantly alter functional connectivity maps of the default-mode network.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>18951982</pmid><doi>10.1016/j.neuroimage.2008.09.029</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult BOLD signal Brain - physiology Brain Mapping - methods Cardiovascular Deconvolution Evoked Potentials - physiology Female fMRI Gaussian process Heart rate Heart Rate - physiology Hemodynamic response Humans Magnetic Resonance Imaging - methods Male Noise Physiological noise Reproducibility of Results Respiration Sensitivity and Specificity Time series |
title | Influence of heart rate on the BOLD signal: The cardiac response function |
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