A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age
The objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-10-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2021.768418/full |
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| author | Xia Li Håkan Fischer Håkan Fischer Amirhossein Manzouri Kristoffer N. T. Månsson Kristoffer N. T. Månsson Tie-Qiang Li Tie-Qiang Li Tie-Qiang Li |
| author_facet | Xia Li Håkan Fischer Håkan Fischer Amirhossein Manzouri Kristoffer N. T. Månsson Kristoffer N. T. Månsson Tie-Qiang Li Tie-Qiang Li Tie-Qiang Li |
| author_sort | Xia Li |
| collection | DOAJ |
| description | The objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T clinical MRI scanner in 227 healthy adult volunteers (N = 227, aged 18–76 years old, male/female = 99/128). With the proposed QDA framework we derived two types of voxel-wise RFC metrics: the connectivity strength index and connectivity density index utilizing the convolutions of the cross-correlation histogram with different kernels. Furthermore, we assessed the negative and positive portions of these metrics separately. With the QDA framework we found age-related declines of RFC metrics in the superior and middle frontal gyri, posterior cingulate cortex (PCC), right insula and inferior parietal lobule of the default mode network (DMN), which resembles previously reported results using other types of RFC data processing methods. Importantly, our new findings complement previously undocumented results in the following aspects: (1) the PCC and right insula are anti-correlated and tend to manifest simultaneously declines of both the negative and positive connectivity strength with subjects’ age; (2) separate assessment of the negative and positive RFC metrics provides enhanced sensitivity to the aging effect; and (3) the sensorimotor network depicts enhanced negative connectivity strength with the adult age. The proposed QDA framework can produce threshold-free and voxel-wise RFC metrics from R-fMRI data. The detected adult age effect is largely consistent with previously reported studies using different R-fMRI analysis approaches. Moreover, the separate assessment of the negative and positive contributions to the RFC metrics can enhance the RFC sensitivity and clarify some of the mixed results in the literature regarding to the DMN and sensorimotor network involvement in adult aging. |
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| format | Article |
| id | doaj.art-b8a2f8377bee452eb0602c4b6b7c40f7 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-16T09:24:26Z |
| publishDate | 2021-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-b8a2f8377bee452eb0602c4b6b7c40f72022-12-21T22:36:40ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2021-10-011510.3389/fnins.2021.768418768418A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult AgeXia Li0Håkan Fischer1Håkan Fischer2Amirhossein Manzouri3Kristoffer N. T. Månsson4Kristoffer N. T. Månsson5Tie-Qiang Li6Tie-Qiang Li7Tie-Qiang Li8Institute of Informatics Engineering, China Jiliang University, Hangzhou, ChinaDepartment of Psychology, Stockholm University, Stockholm, SwedenStockholm University Brain Imaging Centre, Stockholm, SwedenDepartment of Psychology, Stockholm University, Stockholm, SwedenDepartment of Psychology, Stockholm University, Stockholm, SwedenCentre of Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, SwedenInstitute of Informatics Engineering, China Jiliang University, Hangzhou, ChinaDepartment of Clinical Science, Intervention, and Technology, Karolinska Institute, Solna, SwedenDepartment of Medical Radiation and Nuclear Medicine, Karolinska University Hospital, Solna, SwedenThe objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T clinical MRI scanner in 227 healthy adult volunteers (N = 227, aged 18–76 years old, male/female = 99/128). With the proposed QDA framework we derived two types of voxel-wise RFC metrics: the connectivity strength index and connectivity density index utilizing the convolutions of the cross-correlation histogram with different kernels. Furthermore, we assessed the negative and positive portions of these metrics separately. With the QDA framework we found age-related declines of RFC metrics in the superior and middle frontal gyri, posterior cingulate cortex (PCC), right insula and inferior parietal lobule of the default mode network (DMN), which resembles previously reported results using other types of RFC data processing methods. Importantly, our new findings complement previously undocumented results in the following aspects: (1) the PCC and right insula are anti-correlated and tend to manifest simultaneously declines of both the negative and positive connectivity strength with subjects’ age; (2) separate assessment of the negative and positive RFC metrics provides enhanced sensitivity to the aging effect; and (3) the sensorimotor network depicts enhanced negative connectivity strength with the adult age. The proposed QDA framework can produce threshold-free and voxel-wise RFC metrics from R-fMRI data. The detected adult age effect is largely consistent with previously reported studies using different R-fMRI analysis approaches. Moreover, the separate assessment of the negative and positive contributions to the RFC metrics can enhance the RFC sensitivity and clarify some of the mixed results in the literature regarding to the DMN and sensorimotor network involvement in adult aging.https://www.frontiersin.org/articles/10.3389/fnins.2021.768418/fullquantitative data-driven analysis (QDA)resting-state functional magnetic resonance imaging (R-fMRI)resting-state functional connectivity (RFC)connectivity strength index (CSI)connectivity density index (CDI)adult age |
| spellingShingle | Xia Li Håkan Fischer Håkan Fischer Amirhossein Manzouri Kristoffer N. T. Månsson Kristoffer N. T. Månsson Tie-Qiang Li Tie-Qiang Li Tie-Qiang Li A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age Frontiers in Neuroscience quantitative data-driven analysis (QDA) resting-state functional magnetic resonance imaging (R-fMRI) resting-state functional connectivity (RFC) connectivity strength index (CSI) connectivity density index (CDI) adult age |
| title | A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age |
| title_full | A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age |
| title_fullStr | A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age |
| title_full_unstemmed | A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age |
| title_short | A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age |
| title_sort | quantitative data driven analysis framework for resting state functional magnetic resonance imaging a study of the impact of adult age |
| topic | quantitative data-driven analysis (QDA) resting-state functional magnetic resonance imaging (R-fMRI) resting-state functional connectivity (RFC) connectivity strength index (CSI) connectivity density index (CDI) adult age |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2021.768418/full |
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