Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity.
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| Title: | Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity. |
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| Authors: | Rangaprakash, D.1,2, Wu, Guo‐Rong3,4, Marinazzo, Daniele3, Hu, Xiaoping5, Deshpande, Gopikrishna1,6,7,8 gopi@auburn.edu |
| Source: | Magnetic Resonance in Medicine. Oct2018, Vol. 80 Issue 4, p1697-1713. 17p. |
| Abstract: | Purpose: fMRI is the convolution of the hemodynamic response function (HRF) and unmeasured neural activity. HRF variability (HRFv) across the brain could, in principle, alter functional connectivity (FC) estimates from resting‐state fMRI (rs‐fMRI). Given that HRFv is driven by both neural and non‐neural factors, it is problematic when it confounds FC. However, this aspect has remained largely unexplored even though FC studies have grown exponentially. We hypothesized that HRFv confounds FC estimates in the brain's default‐mode‐network. Methods: We tested this hypothesis using both simulations (where the ground truth is known and modulated) as well as rs‐fMRI data obtained in a 7T MRI scanner (N = 47, healthy). FC was obtained using 2 pipelines: data with hemodynamic deconvolution (DC) to estimate the HRF and minimize HRFv, and data with no deconvolution (NDC, HRFv‐ignored). DC and NDC FC networks were compared, along with regional HRF differences, revealing potential false connectivities that resulted from HRFv. Results: We found evidence supporting our hypothesis using both simulations and experimental data. With simulations, we found that HRFv could cause a change of up to 50% in FC. With rs‐fMRI, several potential false connectivities attributable to HRFv, with majority connections being between different lobes, were identified. We found a double exponential relationship between the magnitude of HRFv and its impact on FC, with a mean/median error of 30.5/11.5% caused in FC by HRF confounds. Conclusion: HRFv, if ignored, could cause identification of false FC. FC findings from HRFv‐ignored data should be interpreted cautiously. We suggest deconvolution to minimize HRFv. [ABSTRACT FROM AUTHOR] |
| Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 131262238 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rangaprakash%2C+D%2E%22">Rangaprakash, D.</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Wu%2C+Guo‐Rong%22">Wu, Guo‐Rong</searchLink><relatesTo>3,4</relatesTo><br /><searchLink fieldCode="AR" term="%22Marinazzo%2C+Daniele%22">Marinazzo, Daniele</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Hu%2C+Xiaoping%22">Hu, Xiaoping</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Deshpande%2C+Gopikrishna%22">Deshpande, Gopikrishna</searchLink><relatesTo>1,6,7,8</relatesTo><i> gopi@auburn.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Oct2018, Vol. 80 Issue 4, p1697-1713. 17p. – Name: Abstract Label: Abstract Group: Ab Data: Purpose: fMRI is the convolution of the hemodynamic response function (HRF) and unmeasured neural activity. HRF variability (HRFv) across the brain could, in principle, alter functional connectivity (FC) estimates from resting‐state fMRI (rs‐fMRI). Given that HRFv is driven by both neural and non‐neural factors, it is problematic when it confounds FC. However, this aspect has remained largely unexplored even though FC studies have grown exponentially. We hypothesized that HRFv confounds FC estimates in the brain's default‐mode‐network. Methods: We tested this hypothesis using both simulations (where the ground truth is known and modulated) as well as rs‐fMRI data obtained in a 7T MRI scanner (N = 47, healthy). FC was obtained using 2 pipelines: data with hemodynamic deconvolution (DC) to estimate the HRF and minimize HRFv, and data with no deconvolution (NDC, HRFv‐ignored). DC and NDC FC networks were compared, along with regional HRF differences, revealing potential false connectivities that resulted from HRFv. Results: We found evidence supporting our hypothesis using both simulations and experimental data. With simulations, we found that HRFv could cause a change of up to 50% in FC. With rs‐fMRI, several potential false connectivities attributable to HRFv, with majority connections being between different lobes, were identified. We found a double exponential relationship between the magnitude of HRFv and its impact on FC, with a mean/median error of 30.5/11.5% caused in FC by HRF confounds. Conclusion: HRFv, if ignored, could cause identification of false FC. FC findings from HRFv‐ignored data should be interpreted cautiously. We suggest deconvolution to minimize HRFv. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mrm.27146 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 1697 Titles: – TitleFull: Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rangaprakash, D. – PersonEntity: Name: NameFull: Wu, Guo‐Rong – PersonEntity: Name: NameFull: Marinazzo, Daniele – PersonEntity: Name: NameFull: Hu, Xiaoping – PersonEntity: Name: NameFull: Deshpande, Gopikrishna IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 07403194 Numbering: – Type: volume Value: 80 – Type: issue Value: 4 Titles: – TitleFull: Magnetic Resonance in Medicine Type: main |
| ResultId | 1 |
