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Neuroinformatics
Published in: Neuroinformatics 2/2023

25-11-2022 | Original Article

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains

Authors: Harshvardhan Gazula, Kelly Rootes-Murdy, Bharath Holla, Sunitha Basodi, Zuo Zhang, Eric Verner, Ross Kelly, Pratima Murthy, Amit Chakrabarti, Debasish Basu, Subodh Bhagyalakshmi Nanjayya, Rajkumar Lenin Singh, Roshan Lourembam Singh, Kartik Kalyanram, Kamakshi Kartik, Kumaran Kalyanaraman, Krishnaveni Ghattu, Rebecca Kuriyan, Sunita Simon Kurpad, Gareth J Barker, Rose Dawn Bharath, Sylvane Desrivieres, Meera Purushottam, Dimitri Papadopoulos Orfanos, Eesha Sharma, Matthew Hickman, Mireille Toledano, Nilakshi Vaidya, Tobias Banaschewski, Arun L. W. Bokde, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillére Martinot, Eric Artiges, Frauke Nees, Tomás Paus, Luise Poustka, Juliane H. Fröhner, Lauren Robinson, Michael N. Smolka, Henrik Walter, Jeanne Winterer, Robert Whelan, Jessica A. Turner, Anand D. Sarwate, Sergey M. Plis, Vivek Benegal, Gunter Schumann, Vince D. Calhoun, IMAGEN Consortium

Published in: Neuroinformatics | Issue 2/2023

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Abstract

With the growth of decentralized/federated analysis approaches in neuroimaging, the opportunities to study brain disorders using data from multiple sites has grown multi-fold. One such initiative is the Neuromark, a fully automated spatially constrained independent component analysis (ICA) that is used to link brain network abnormalities among different datasets, studies, and disorders while leveraging subject-specific networks. In this study, we implement the neuromark pipeline in COINSTAC, an open-source neuroimaging framework for collaborative/decentralized analysis. Decentralized exploratory analysis of nearly 2000 resting-state functional magnetic resonance imaging datasets collected at different sites across two cohorts and co-located in different countries was performed to study the resting brain functional network connectivity changes in adolescents who smoke and consume alcohol. Results showed hypoconnectivity across the majority of networks including sensory, default mode, and subcortical domains, more for alcohol than smoking, and decreased low frequency power. These findings suggest that global reduced synchronization is associated with both tobacco and alcohol use. This proof-of-concept work demonstrates the utility and incentives associated with large-scale decentralized collaborations spanning multiple sites.
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Literature
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., et al. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, 2.CrossRefPubMedPubMedCentral
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010). Functional-anatomic fractionation of the brain’s default network. Neuron, 65, 550–562.CrossRefPubMedPubMedCentral
Baker, B. T., Damaraju, E., Silva, R. F., Plis, S. M., & Calhoun, V. D. (2020). Decentralized dynamic functional network connectivity: State analysis in collaborative settings. Human Brain Mapping.
Baker, B. T., Silva, R. F., Calhoun, V. D., Sarwate, A. D., & Plis, S. M. (2015). Large scale collaboration with autonomy: Decentralized data ica. In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP) (pp. 1–6). IEEE.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57, 289–300.
Calhoun, V. D., Liu, J., & Adalı, T. (2009). A review of group ica for fmri data and ica for joint inference of imaging, genetic, and erp data. Neuroimage, 45, S163–S172.CrossRefPubMed
Camchong, J., Stenger, A., & Fein, G. (2012). Resting-State Synchrony During Early Alcohol Abstinence Can Predict Subsequent Relapse. Cerebral Cortex, 23, 2086–2099.CrossRefPubMedPubMedCentral
Du, Y., Allen, E., He, H., Sui, J., Wu, L., & Calhoun, V. (2016). Artifact removal in the context of group ica: A comparison of single-subject and group approaches. Human Brain Mapping, 37, 1005–1025.CrossRefPubMed
Du, Y., & Fan, Y. (2013). Group information guided ica for fmri data analysis. Neuroimage, 69, 157–197.CrossRefPubMed
Du, Y., Fu, Z., Sui, J., Gao, S., Xing, Y., Lin, D., Salman, M., Abrol, A., Rahaman, M. A., Chen, J., Hong, L. E., Kochunov, P., Osuch, E. A., & Calhoun, V. D. (2020). NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders. NeuroImage: Clinical, 28, 102375.
Ebner, T. J., & Pasalar, S. (2008). Cerebellum predicts the future motor state. The Cerebellum, 7, 583–588.CrossRefPubMed
Eickhoff, S., Nichols, T. E., Horn, J. D. V., & Turner, J. A. (2016). Sharing the wealth: Neuroimaging data repositories. NeuroImage, 124, 1065–1068.CrossRefPubMed
Fedota, J. R., & Stein, E. A. (2015). Resting-state functional connectivity and nicotine addiction: prospects for biomarker development. Annals of the New York Academy of Sciences, 1349, 64.CrossRefPubMedPubMedCentral
Gazula, H., Baker, B., Damaraju, E., Plis, S. M., Panta, S. R., Silva, R. F., & Calhoun, V. D. (2018). Decentralized analysis of brain imaging data: Voxel-based morphometry and dynamic functional network connectivity. Frontiers in Neuroinformatics, 12, 55.CrossRefPubMedPubMedCentral
Gazula, H., Holla, B., Zhang, Z., Xu, J., Verner, E., Kelly, R., Jain, S., Bharath, R. D., Barker, G. J., Basu, D., Chakrabarti, A., Kalyanram, K., Kumaran, K., Singh, L., Kuriyan, R., Murthy, P., Benega, V., Plis, S. M., Sarwate, A. D., Turner, J. A., Schumann, G., & Calhoun, V. D. (2021). Decentralized multisite VBM analysis during adolescence shows structural changes linked to age, body mass index, and smoking: a COINSTAC analysis. Neuroinformatics.
Gazula, H., Kelly, R., Romero, J., Verner, E., Baker, B. T., Silva, R. F., Imtiaz, H., Saha, D. K., Raja, R., Turner, J. A., et al. (2020). Coinstac: Collaborative informatics and neuroimaging suite toolkit for anonymous computation. Journal of Open Source Software, 5, 2166.CrossRef
Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., & FAGERSTROM, K. -O. (1991). The fagerström test for nicotine dependence: a revision of the fagerstrom tolerance questionnaire. British Journal of Addiction, 86, 1119–1127.
Holmes, A. J., Hollinshead, M. O., O’keefe, T. M., Petrov, V. I., Fariello, G. R., Wald, L. L., Fischl, B., Rosen, B. R., Mair, R. W., Roffman, J. L., et al. (2015). Brain genomics superstruct project initial data release with structural, functional, and behavioral measures. Scientific Data, 2, 1–16.
Jansen, J. M., van Holst, R. J., van den Brink, W., Veltman, D. J., Caan, M. W., & Goudriaan, A. E. (2015). Brain function during cognitive flexibility and white matter integrity in alcohol-dependent patients, problematic drinkers and healthy controls. Addiction biology, 20, 979–989.CrossRefPubMed
Lin, Q. -H., Liu, J., Zheng, Y. -R., Liang, H., & Calhoun, V. D. (2010). Semiblind spatial ica of fmri using spatial constraints. Human Brain Mapping, 31, 1076–1088.CrossRefPubMed
Ming, J., Verner, E., Sarwate, A., Kelly, R., Reed, C., Kahleck, T., Silva, R., Panta, S., Turner, J., Plis, S., et al. (2017). Coinstac: Decentralizing the future of brain imaging analysis. F1000Research, 6, 1512.
Plis, S. M., Sarwate, A. D., Wood, D., Dieringer, C., Landis, D., Reed, C., Panta, S. R., Turner, J. A., Shoemaker, J. M., Carter, K. W., et al. (2016). Coinstac: a privacy enabled model and prototype for leveraging and processing decentralized brain imaging data. Frontiers in Neuroscience, 10, 365.CrossRefPubMedPubMedCentral
Pujol, J., Blanco-Hinojo, L., Batalla, A., López-Solà, M., Harrison, B. J., Soriano-Mas, C., Crippa, J. A., Fagundo, A. B., Deus, J., De la Torre, R., et al. (2014). Functional connectivity alterations in brain networks relevant to self-awareness in chronic cannabis users. Journal of Psychiatric Research, 51, 68–78.CrossRefPubMed
Saha, D. K., Calhoun, V. D., Du, Y., Fu, Z., Panta, S. R., Kwon, S., Sarwate, A., & Plis, S. M. (2021). Privacy-preserving quality control of neuroimaging datasets in federated environment. bioRxiv, (p. 826974).
Saha, D. K., Calhoun, V. D., Panta, S. R., & Plis, S. M. (2017). See without looking: joint visualization of sensitive multi-site datasets. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI’2017) (pp. 2672–2678). Melbourne, Australia.
Salman, M. S., Wager, T. D., Damaraju, E., Abrol, A., Vergara, V. M., Fu, Z., & Calhoun, V. D. (2021). An approach to automatically label and order brain activity/component maps. Brain Connectivity.
Sarwate, A. D., Plis, S. M., Turner, J. A., Arbabshirani, M. R., & Calhoun, V. D. (2014). Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation. Frontiers in Neuroinformatics, 8, 35.CrossRefPubMedPubMedCentral
Schumann, G., Loth, E., Banaschewski, T., Barbot, A., Barker, G., Büchel, C., Conrod, P., Dalley, J., Flor, H., Gallinat, J., et al. (2010). The imagen study: reinforcement-related behaviour in normal brain function and psychopathology. Molecular Psychiatry, 15, 1128.CrossRefPubMed
Sharma, E., Vaidya, N., Iyengar, U., Zhang, Y., Holla, B., Purushottam, M., Chakrabarti, A., Fernandes, G. S., Heron, J., Hickman, M., Desrivieres, S., Kartik, K., Jacob, P., Rangaswamy, M., Bharath, R. D., Barker, G., Orfanos, D. P., Ahuja, C., Murthy, P., Jain, S., Varghese, M., Jayarajan, D., Kumar, K., Thennarasu, K., Basu, D., Subodh, B. N., Kuriyan, R., Kurpad, S. S., Kalyanram, K., Krishnaveni, G., Krishna, M., Singh, R. L., Singh, L. R., Kalyanram, K., Toledano, M., Schumann, G., & Benegal, V. (2020). Consortium on vulnerability to externalizing disorders and addictions (cVEDA): A developmental cohort study protocol. BMC Psychiatry, 20.
Shringarpure, S. S., & Bustamante, C. D. (2015). Privacy risks from genomic data-sharing beacons. The American Journal of Human Genetics, 97, 631–646.CrossRefPubMed
Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10, 557–570.CrossRef
Vergara, V. M., Liu, J., Claus, E. D., Hutchison, K., & Calhoun, V. (2017). Alterations of resting state functional network connectivity in the brain of nicotine and alcohol users. NeuroImage, 151, 45–54.CrossRefPubMed
White, T., Blok, E., & Calhoun, V. D. (2020). Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed. Human Brain Mapping.
Wilcox, C. E., Brett, M. E., & Calhoun, V. D. (2020). Objective markers for psychiatric decision-making: How to move imaging into clinical practice. NeuroImage: Clinical, 26, 102084.
Zhang, Y., Vaidya, N., Iyengar, U., Sharma, E., Holla, B., Ahuja, C. K., Barker, G. J., Basu, D., Bharath, R. D., Chakrabarti, A., Desrivieres, S., Elliott, P., Fernandes, G., Gourisankar, A., Heron, J., Hickman, M., Jacob, P., Jain, S., Jayarajan, D., Kalyanram, K., Kartik, K., Krishna, M., Krishnaveni, G., Kumar, K., Kumaran, K., Kuriyan, R., Murthy, P., Orfanos, D. P., Purushottam, M., Rangaswamy, M., Kupard, S. S., Singh, L., Singh, R., Subodh, B. N., Thennarasu, K., Toledano, M., Varghese, M., Benegal, V., & Schumann, G. (2020). The consortium on vulnerability to externalizing disorders and addictions (c-VEDA): an accelerated longitudinal cohort of children and adolescents in India. Molecular Psychiatry, 25, 1618–1630.CrossRefPubMed
Zhu, X., Cortes, C. R., Mathur, K., Tomasi, D., & Momenan, R. (2017). Model-free functional connectivity and impulsivity correlates of alcohol dependence: a resting-state study. Addiction Biology, 22, 206–217.CrossRef
Metadata
Title
Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains
Authors
Harshvardhan Gazula
Kelly Rootes-Murdy
Bharath Holla
Sunitha Basodi
Zuo Zhang
Eric Verner
Ross Kelly
Pratima Murthy
Amit Chakrabarti
Debasish Basu
Subodh Bhagyalakshmi Nanjayya
Rajkumar Lenin Singh
Roshan Lourembam Singh
Kartik Kalyanram
Kamakshi Kartik
Kumaran Kalyanaraman
Krishnaveni Ghattu
Rebecca Kuriyan
Sunita Simon Kurpad
Gareth J Barker
Rose Dawn Bharath
Sylvane Desrivieres
Meera Purushottam
Dimitri Papadopoulos Orfanos
Eesha Sharma
Matthew Hickman
Mireille Toledano
Nilakshi Vaidya
Tobias Banaschewski
Arun L. W. Bokde
Herta Flor
Antoine Grigis
Hugh Garavan
Penny Gowland
Andreas Heinz
Rüdiger Brühl
Jean-Luc Martinot
Marie-Laure Paillére Martinot
Eric Artiges
Frauke Nees
Tomás Paus
Luise Poustka
Juliane H. Fröhner
Lauren Robinson
Michael N. Smolka
Henrik Walter
Jeanne Winterer
Robert Whelan
Jessica A. Turner
Anand D. Sarwate
Sergey M. Plis
Vivek Benegal
Gunter Schumann
Vince D. Calhoun
IMAGEN Consortium
Publication date
25-11-2022
Publisher
Springer US
Published in
Neuroinformatics / Issue 2/2023
Print ISSN: 1539-2791
Electronic ISSN: 1559-0089
DOI
https://doi.org/10.1007/s12021-022-09604-4

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