The relationship between spatial configuration and functional connectivity of brain regions revisited
Abstract
In our previous paper (Bijsterbosch et al., 2018), we showed that network-based modelling of brain connectivity interacts strongly with the shape and exact location of brain regions, such that cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Here we show that these spatial effects on connectivity estimates actually occur as a result of spatial overlap between brain networks. This is shown to systematically bias connectivity estimates obtained from group spatial ICA followed by dual regression. We introduce an extended method that addresses the bias and achieves more accurate connectivity estimates.
Data availability
Simulation analysis scripts are available on git.Source data files for Figures 1 and 5 will be made available on BALSA (https://balsa.wustl.edu/) upon acceptance.
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Human Connectome Project: WU-Minn HCP consortiumYoung Adult, S1200.
Article and author information
Author details
Funding
Wellcome (098369/Z/12/Z)
- Stephen M Smith
Wellcome (091509/Z/10/Z)
- Stephen M Smith
Wellcome (203139/Z/16/Z)
- Stephen M Smith
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: HCP data were acquired using protocols approved by the Washington University institutional review board (Mapping the Human Connectome: Structure, Function, and Heritability; IRB # 201204036). Informed consent was obtained from subjects. Anonymised data are publicly available from ConnectomeDB (db.humanconnectome.org; Hodge et al., 2016). Certain parts of the dataset used in this study, such as the age of the subjects, are available subject to restricted data usage terms, requiring researchers to ensure that the anonymity of subjects is protected (Van Essen et al., 2013).
Copyright
© 2019, Bijsterbosch et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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