Larger error signals in major depression are associated with better avoidance learning

James F. Cavanagh, Andrew J. Bismark, Michael J. Frank, John J.B. Allen

Research output: Contribution to journalArticle

31 Scopus citations

Abstract

The medial prefrontal cortex (mPFC) is particularly reactive to signals of error, punishment, and conflict in the service of behavioral adaptation and it is consistently implicated in the etiology of major depressive disorder (MDD). This association makes conceptual sense, given that MDD has been associated with hyper-reactivity in neural systems associated with punishment processing. Yet in practice, depression-related variance in measures of mPFC functioning often fails to relate to performance. For example, neuroelectric reflections of mediofrontal error signals are often found to be larger in MDD, but a deficit in post-error performance suggests that these error signals are not being used to rapidly adapt behavior. Thus, it remains unknown if depression-related variance in error signals reflects a meaningful alteration in the use of error or punishment information. However, larger mediofrontal error signals have also been related to another behavioral tendency: increased accuracy in avoidance learning. The integrity of this error-avoidance system remains untested in MDD. In this study, EEG was recorded as 21 symptomatic, drug-free participants with current or past MDD and 24 control participants performed a probabilistic reinforcement learning task. Depressed participants had larger mid-frontal EEG responses to error feedback than controls. The direct relationship between error signal amplitudes and avoidance learning accuracy was replicated. Crucially, this relationship was stronger in depressed participants for high conflict "lose-lose" situations, demonstrating a selective alteration of avoidance learning. This investigation provided evidence that larger error signal amplitudes in depression are associated with increased avoidance learning, identifying a candidate mechanistic model for hypersensitivity to negative outcomes in depression.

Original languageEnglish (US)
Article numberArticle 331
JournalFrontiers in Psychology
Volume2
Issue numberNOV
DOIs
StatePublished - Dec 1 2011

Keywords

  • Anterior
  • Computational psychiatry
  • FRN
  • Major depressive disorder
  • Reinforcement learning
  • Theta

ASJC Scopus subject areas

  • Psychology(all)

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