Building better biomarkers: Brain models in translational neuroimaging

Choong Wan Woo, Luke J. Chang, Martin Lindquist, Tor D. Wager

Research output: Contribution to journalReview article

Abstract

Despite its great promise, neuroimaging has yet to substantially impact clinical practice and public health. However, a developing synergy between emerging analysis techniques and data-sharing initiatives has the potential to transform the role of neuroimaging in clinical applications. We review the state of translational neuroimaging and outline an approach to developing brain signatures that can be shared, tested in multiple contexts and applied in clinical settings. The approach rests on three pillars: (i) the use of multivariate pattern-recognition techniques to develop brain signatures for clinical outcomes and relevant mental processes; (ii) assessment and optimization of their diagnostic value; and (iii) a program of broad exploration followed by increasingly rigorous assessment of generalizability across samples, research contexts and populations. Increasingly sophisticated models based on these principles will help to overcome some of the obstacles on the road from basic neuroscience to better health and will ultimately serve both basic and applied goals.

Original languageEnglish (US)
Pages (from-to)365-377
Number of pages13
JournalNature Neuroscience
Volume20
Issue number3
DOIs
StatePublished - Feb 23 2017

ASJC Scopus subject areas

  • Neuroscience(all)

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