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Pathways to Neuroprediction: Opportunities and Challenges to Prediction of Treatment Response in Depression

  • Mood and Anxiety Disorders (C Harmer, Section Editor)
  • Published:
Current Behavioral Neuroscience Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

We set out to review the current state of science in neuroprediction, using biological measures of brain function, with task based fMRI to prospectively predict response to a variety of treatments.

Recent Findings

Task-based fMRI neuroprediction studies are balanced between whole brain and ROI specific analyses. The predominant tasks are emotion processing, with ROIs based upon amygdala and subgenual anterior cingulate gyrus, both within the salience and emotion network. A rapidly emerging new area of neuroprediction is of disease course and illness recurrence. Concerns include use of open-label and single arm studies, lack of consideration of placebo effects, unbalanced adjustments for multiple comparisons (over focus on type I error), small sample sizes, unreported effect sizes, overreliance on ROI studies.

Summary

There is a need to adjust neuroprediction study reporting so that greater coherence can facilitate meta analyses, and increased funding for more multiarm studies in neuroprediction.

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Acknowledgements

Support for this work was provided by MH101487 (SAL, LMJ. KLP, NAC), MH101497 (KLP, HK, SAL), MH112705 (HK, SAL, KLP), T32 MH067631 (NAC, Rasenick Pi).

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  1. The University of Illinois at Chicago, 1610 W Taylor St, Chicago, IL, 60612, USA

    Scott A. Langenecker, Natania A. Crane, Lisanne M. Jenkins, K. Luan Phan & Heide Klumpp

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  1. Scott A. Langenecker
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The authors have received grant money from the National Institute of Mental Health.

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Langenecker, S.A., Crane, N.A., Jenkins, L.M. et al. Pathways to Neuroprediction: Opportunities and Challenges to Prediction of Treatment Response in Depression. Curr Behav Neurosci Rep 5, 48–60 (2018). https://doi.org/10.1007/s40473-018-0140-2

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