Big data initiatives in psychiatry: Global neuroimaging studies

Paul M. Thompson, Christopher R.K. Ching, Emily L. Dennis, Lauren E. Salminen, Jessica A. Turner, Theo G.M. van Erp, Neda Jahanshad

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations


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.

Original languageEnglish
Title of host publicationNeuroimaging in Schizophrenia
PublisherSpringer International Publishing
Number of pages16
ISBN (Electronic)9783030352066
ISBN (Print)9783030352059
StatePublished - 1 Jan 2020
Externally publishedYes


  • Imaging genetics
  • International consortia
  • Neuroimaging
  • Reproducibility
  • Team science


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