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Big Data Initiatives in Psychiatry: Global Neuroimaging Studies

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Neuroimaging in Schizophrenia

Abstract

Big data and large-scale biobanks offer the potential to answer new types of questions as well as address older questions with greater confidence and rigor in order to overcome the ‘crisis of reproducibility’ in the neurosciences, in which findings from small datasets were often not replicated in independent samples. A recent paradigm shift has led to the formation of large-scale consortia that pool resources from around the world and significantly improve the power to establish the effects of genetics, and a large range of psychiatric disorders, on the brain in populations worldwide. The individual studies with diverse datasets from people with different ethnic and cultural backgrounds can now be pooled to combine evidence across collaborative studies to determine the robust brain signatures of psychiatric disorders, as well as factors that modulate them. In this chapter, we describe some of the efforts underway internationally to analyze mental health data in a coordinated way, as well as some of the challenges in comparing data from different studies. We discuss “Big Data” as international neuroimaging and genetic data, the need for large scale efforts in brain imaging and genetics, and the activities and findings from the psychiatry focused groups of the ENIGMA consortium, efforts developed to bring together researchers and resources to improve our understanding of how psychiatric disorders affect brain structure and function.

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Acknowledgments

This work is supported in part by NIH grant U54 EB020403 from the BD2K Initiative. Additional support was provided by R01 MH116147, P41 EB015922, RF1 AG051710, and RF1 AG041915. We also thank the many scientists and participants worldwide who contributed to the studies reviewed here.

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Authors and Affiliations

  1. Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    Paul M. Thompson, Christopher R. K. Ching, Lauren E. Salminen & Neda Jahanshad

  2. Department of Neurology, TBI and Concussion Center, University of Utah, Salt Lake City, UT, USA

    Emily L. Dennis

  3. Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA

    Jessica A. Turner

  4. Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA

    Theo G. M. van Erp

  5. Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA

    Theo G. M. van Erp

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  1. Paul M. Thompson
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  2. Christopher R. K. Ching
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  3. Emily L. Dennis
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  4. Lauren E. Salminen
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  5. Jessica A. Turner
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  6. Theo G. M. van Erp
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  7. Neda Jahanshad
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Correspondence to Paul M. Thompson .

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Editors and Affiliations

  1. Department of Psychiatry and Radiology, Brigham and Women’s Hospital, Boston, MA, USA

    Marek Kubicki

  2. Department of Psychiatry and Radiology, Brigham and Women’s Hospital, Boston, MA, USA

    Martha E. Shenton

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Thompson, P.M. et al. (2020). Big Data Initiatives in Psychiatry: Global Neuroimaging Studies. In: Kubicki, M., Shenton, M. (eds) Neuroimaging in Schizophrenia . Springer, Cham. https://doi.org/10.1007/978-3-030-35206-6_21

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  • DOI: https://doi.org/10.1007/978-3-030-35206-6_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35205-9

  • Online ISBN: 978-3-030-35206-6

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