Physiological and motion signatures in static and time-varying functional connectivity and their subject identifiability

Abstract
Data availability
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Abstract

Human brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based connectivity fingerprinting to characterize individual patterns of brain activity. However, it is not clear whether these patterns mainly reflect neural activity or the effect of physiological and motion processes. To answer this question, we capitalize on a large data sample from the Human Connectome Project and rigorously investigate the contribution of the aforementioned processes on functional connectivity (FC) and time-varying FC, as well as their contribution to subject identifiability. We find that head motion, as well as heart rate and breathing fluctuations, induce artifactual connectivity within distinct resting-state networks and that they correlate with recurrent patterns in time-varying FC. Even though the spatiotemporal signatures of these processes yield above-chance levels in subject identifiability, removing their effects at the preprocessing stage improves identifiability, suggesting a neural component underpinning the inter-individual differences in connectivity.

Data availability

Matlab code used in this work can be found here: https://github.com/axifra/Nuisance_signatures_FC

The following previously published data sets were used

1. Van Essen D
2. Ugurbil K
(2017) Human Connectome Project: WU- Minn HCP consortium
Young Adult, S1200.

https://www.humanconnectome.org/study/hcp-young-adult

Article and author information

Author details

Alba Xifra-Porxas

Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, Canada

For correspondence
alba.xifraporxas@mail.mcgill.ca

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-9023-2432
Michalis Kassinopoulos

Graduate Program in Biological and Biomedical Engineering, McGill University, Montreal, Canada

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-4312-4401
Georgios D Mitsis

Bioengineering, McGill University, Montreal, Canada

For correspondence
georgios.mitsis@mcgill.ca

Competing interests
The authors declare that no competing interests exist.

Funding

Natural Sciences and Engineering Research Council of Canada (Discovery Grant 34362)

Georgios D Mitsis

Fonds de la Recherche du Quebec - Nature et Technologies (PR191780-2016)

Georgios D Mitsis

Canada First Research Excellence Fund (Healthy Brains for Healthy Lives Scholarship)

Michalis Kassinopoulos

Quebec Bio-Imaging Network (Doctoral Scholarships)

Alba Xifra-Porxas
Michalis Kassinopoulos

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: 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).

Copyright

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.