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

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

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)48-60
Number of pages13
JournalCurrent Behavioral Neuroscience Reports
Issue number1
StatePublished - Mar 1 2018
Externally publishedYes


  • Cognitive behavioral therapy
  • Depression
  • Networks
  • Prediction
  • Psychopharmacology
  • fMRI

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Behavioral Neuroscience


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