Neurocomputational mechanisms underlying emotional awareness: Insights afforded by deep active inference and their potential clinical relevance

Ryan Smith, Richard D. Lane, Thomas Parr, Karl J. Friston

Research output: Contribution to journalReview article

3 Scopus citations


Emotional awareness (EA) is recognized as clinically relevant to the vulnerability to, and maintenance of, psychiatric disorders. However, the neurocomputational processes that underwrite individual variations remain unclear. In this paper, we describe a deep (active) inference model that reproduces the cognitive-emotional processes and self-report behaviors associated with EA. We then present simulations to illustrate (seven) distinct mechanisms that (either alone or in combination) can produce phenomena – such as somatic misattribution, coarse-grained emotion conceptualization, and constrained reflective capacity – characteristic of low EA. Our simulations suggest that the clinical phenotype of impoverished EA can be reproduced by dissociable computational processes. The possibility that different processes are at work in different individuals suggests that they may benefit from distinct clinical interventions. As active inference makes particular predictions about the underlying neurobiology of such aberrant inference, we also discuss how this type of modelling could be used to design neuroimaging tasks to test predictions and identify which processes operate in different individuals – and provide a principled basis for personalized precision medicine.

Original languageEnglish (US)
Pages (from-to)473-491
Number of pages19
JournalNeuroscience and Biobehavioral Reviews
Publication statusPublished - Dec 2019



  • Active inference
  • Computational neuroscience
  • Emotional awareness
  • Emotional working memory
  • Somatic misattribution

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Cognitive Neuroscience
  • Behavioral Neuroscience

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