Altmann, A;
Mourao-Miranda, J;
(2019)
Evidence for bias of genetic ancestry in resting state functional MRI.
In: Linguraru, Marius George and Grisan, Enrico, (eds.)
Proceedings of the IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).
IEEE Xplore: New York, USA.
(In press).
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Abstract
Resting state functional magnetic resonance imaging (rsfMRI) is a popular imaging modality for mapping the functional connectivity of the brain. Rs-fMRI is, just like other neuroimaging modalities, subject to a series of technical and subject level biases that change the inferred connectivity pattern. In this work we predicted genetic ancestry from rs-fMRI connectivity data at very high performance (area under the ROC curve of 0.93). Thereby, we demonstrated that genetic ancestry is encoded in the functional connectivity pattern of the brain at rest. We hypothesize that these observed differences are a result of known ethnicity-related variations in head and brain morphology, which may be carried forward through the rs-fMRI processing pipeline, rather than true neuronal differences. In any case, genetic ancestry constitutes a bias that should be accounted for in the analysis of rs-fMRI data.
| Type: | Proceedings paper |
|---|---|
| Title: | Evidence for bias of genetic ancestry in resting state functional MRI |
| Event: | IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 8-11 April 2019, Venice, Italy |
| Location: | Venice, Italy |
| Dates: | 08 April 2019 - 11 April 2019 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://biomedicalimaging.org/2019/ |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | resting state fMRI, genetics, ancestry, imaging genetics, machine learning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10069396 |
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