Journal article
Improved interpretability of brain-behaviour CCA with domain-driven dimension reduction
- Abstract:
- Canonical Correlation Analysis (CCA) has been widely applied to study correlations between neuroimaging data and behavioral data. Practical use of CCA typically requires dimensionality reduction with, for example, Principal Components Analysis (PCA), however, this can result in CCA results that are difficult to interpret. In this paper, we introduce a Domain-driven Dimension Reduction (DDR) method, reducing the dimensionality of the original datasets combining human knowledge of the structure of the variables studied. We apply the method to the Human Connectome Project S1200 release and compare standard PCA across all variables with DDR applied to individual classes of variables, finding that DDR-CCA results are more stable and interpretable, allowing the contribution of each class of variable to be better understood. By carefully designing the analysis pipeline and cross-validating the results, we offer more insights on the interpretation of CCA applied to brain-behaviour data.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 3.7MB, Terms of use)
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- Publisher copy:
- 10.3389/fnins.2022.851827
Authors
- Publisher:
- Frontiers Media
- Journal:
- Frontiers in Neuroscience More from this journal
- Volume:
- 16
- Article number:
- 851827
- Publication date:
- 2022-06-23
- Acceptance date:
- 2022-05-24
- DOI:
- EISSN:
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1662-453X
- ISSN:
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1662-4548
- Language:
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English
- Keywords:
- Pubs id:
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1262660
- Local pid:
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pubs:1262660
- Deposit date:
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2022-06-09
Terms of use
- Copyright holder:
- Liu et al
- Copyright date:
- 2022
- Rights statement:
- © 2022 Liu, Whitaker, Smith and Nichols. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
- Licence:
- CC Attribution (CC BY)
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