Great Expectations: A Critical Review of and Suggestions for the Study of Reward Processing as a Cause and Predictor of Depression

Dylan M. Nielson, Hanna Keren, Georgia O'Callaghan, Sarah M. Jackson, Ioanna Douka, Pablo Vidal-Ribas, Narun Pornpattananangkul, Christopher C. Camp, Lisa S. Gorham, Christine Wei, Stuart Kirwan, Charles Y. Zheng, Argyris Stringaris

Research output: Contribution to journalReview articlepeer-review

47 Scopus citations

Abstract

Both human and animal studies support the relationship between depression and reward processing abnormalities, giving rise to the expectation that neural signals of these processes may serve as biomarkers or mechanistic treatment targets. Given the great promise of this research line, we scrutinized those findings and the theoretical claims that underlie them. To achieve this, we applied the framework provided by classical work on causality as well as contemporary approaches to prediction. We identified a number of conceptual, practical, and analytical challenges to this line of research and used a preregistered meta-analysis to quantify the longitudinal associations between reward processing abnormalities and depression. We also investigated the impact of measurement error on reported data. We found that reward processing abnormalities do not reach levels that would be useful for clinical prediction, yet the available evidence does not preclude a possible causal role in depression.

Original languageEnglish
Pages (from-to)134-143
Number of pages10
JournalBiological Psychiatry
Volume89
Issue number2
DOIs
StatePublished - 15 Jan 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020

Keywords

  • Depression
  • Development
  • Meta-analysis
  • Reliability
  • Reproducibility
  • Reward processing

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