Impact of concatenating fMRI data on reliability for functional connectomics
Compelling evidence suggests the need for more data per individual to reliably map the functional organization of the human connectome. As the notion that ‘more data is better’ emerges as a golden rule for functional connectomics, researchers find themselves grappling with the challenges of how to o...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-02-01
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| Series: | NeuroImage |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S105381192031034X |
| _version_ | 1818322608560537600 |
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| author | Jae Wook Cho Annachiara Korchmaros Joshua T Vogelstein Michael P Milham Ting Xu |
| author_facet | Jae Wook Cho Annachiara Korchmaros Joshua T Vogelstein Michael P Milham Ting Xu |
| author_sort | Jae Wook Cho |
| collection | DOAJ |
| description | Compelling evidence suggests the need for more data per individual to reliably map the functional organization of the human connectome. As the notion that ‘more data is better’ emerges as a golden rule for functional connectomics, researchers find themselves grappling with the challenges of how to obtain the desired amounts of data per participant in a practical manner, particularly for retrospective data aggregation. Increasingly, the aggregation of data across all fMRI scans available for an individual is being viewed as a solution, regardless of scan condition (e.g., rest, task, movie). A number of open questions exist regarding the aggregation process and the impact of different decisions on the reliability of resultant aggregate data. We leveraged the availability of highly sampled test-retest datasets to systematically examine the impact of data aggregation strategies on the reliability of cortical functional connectomics. Specifically, we compared functional connectivity estimates derived after concatenating from: 1) multiple scans under the same state, 2) multiple scans under different states (i.e. hybrid or general functional connectivity), and 3) subsets of one long scan. We also varied connectivity processing (i.e. global signal regression, ICA-FIX, and task regression) and estimation procedures. When the total number of time points is equal, and the scan state held constant, concatenating multiple shorter scans had a clear advantage over a single long scan. However, this was not necessarily true when concatenating across different fMRI states (i.e. task conditions), where the reliability from the aggregate data varied across states. Concatenating fewer numbers of states that are more reliable tends to yield higher reliability. Our findings provide an overview of multiple dependencies of data concatenation that should be considered to optimize reliability in analysis of functional connectivity data. |
| first_indexed | 2024-12-13T10:59:30Z |
| format | Article |
| id | doaj.art-3e4b649ea9ab4036bda23079ace462fc |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-13T10:59:30Z |
| publishDate | 2021-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-3e4b649ea9ab4036bda23079ace462fc2022-12-21T23:49:18ZengElsevierNeuroImage1095-95722021-02-01226117549Impact of concatenating fMRI data on reliability for functional connectomicsJae Wook Cho0Annachiara Korchmaros1Joshua T Vogelstein2Michael P Milham3Ting Xu4The Child Mind Institute, 101 East 56th Street, New York, NY 10022, United StatesThe Child Mind Institute, 101 East 56th Street, New York, NY 10022, United StatesDepartment of Biomedical Engineering, Institute for Computational Medicine, Kavli Neuroscience Discovery Institute, Johns Hopkins University, 3400N. Charles St Baltimore, MD 21218, United StatesThe Child Mind Institute, 101 East 56th Street, New York, NY 10022, United StatesThe Child Mind Institute, 101 East 56th Street, New York, NY 10022, United States; Corresponding author.Compelling evidence suggests the need for more data per individual to reliably map the functional organization of the human connectome. As the notion that ‘more data is better’ emerges as a golden rule for functional connectomics, researchers find themselves grappling with the challenges of how to obtain the desired amounts of data per participant in a practical manner, particularly for retrospective data aggregation. Increasingly, the aggregation of data across all fMRI scans available for an individual is being viewed as a solution, regardless of scan condition (e.g., rest, task, movie). A number of open questions exist regarding the aggregation process and the impact of different decisions on the reliability of resultant aggregate data. We leveraged the availability of highly sampled test-retest datasets to systematically examine the impact of data aggregation strategies on the reliability of cortical functional connectomics. Specifically, we compared functional connectivity estimates derived after concatenating from: 1) multiple scans under the same state, 2) multiple scans under different states (i.e. hybrid or general functional connectivity), and 3) subsets of one long scan. We also varied connectivity processing (i.e. global signal regression, ICA-FIX, and task regression) and estimation procedures. When the total number of time points is equal, and the scan state held constant, concatenating multiple shorter scans had a clear advantage over a single long scan. However, this was not necessarily true when concatenating across different fMRI states (i.e. task conditions), where the reliability from the aggregate data varied across states. Concatenating fewer numbers of states that are more reliable tends to yield higher reliability. Our findings provide an overview of multiple dependencies of data concatenation that should be considered to optimize reliability in analysis of functional connectivity data.http://www.sciencedirect.com/science/article/pii/S105381192031034X |
| spellingShingle | Jae Wook Cho Annachiara Korchmaros Joshua T Vogelstein Michael P Milham Ting Xu Impact of concatenating fMRI data on reliability for functional connectomics NeuroImage |
| title | Impact of concatenating fMRI data on reliability for functional connectomics |
| title_full | Impact of concatenating fMRI data on reliability for functional connectomics |
| title_fullStr | Impact of concatenating fMRI data on reliability for functional connectomics |
| title_full_unstemmed | Impact of concatenating fMRI data on reliability for functional connectomics |
| title_short | Impact of concatenating fMRI data on reliability for functional connectomics |
| title_sort | impact of concatenating fmri data on reliability for functional connectomics |
| url | http://www.sciencedirect.com/science/article/pii/S105381192031034X |
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