Emotional processes are central to behavior, yet their deeply subjective nature has been a challenge for neuroscientific study as well as for psychiatric diagnosis. Here we explore the relationships between subjective feelings and their underlying brain circuits from a computational perspective. We apply recent insights from systems neuroscience- approaching subjective behavior as the result of mental computations instantiated in the brain-to the study of emotions. We develop the hypothesis that emotions are the product of neural computations whose motor role is to reallocate bodily resources mostly gated by smooth muscles. This "emotor" control system is analagous to the more familiar motor control computations that coordinate skeletal muscle movements. To illustrate this framework, we review recent research on "confidence." Although familiar as a feeling, confidence is also an objective statistical quantity: an estimate of the probability that a hypothesis is correct. This model-based approach helped reveal the neural basis of decision confidence in mammals and provides a bridge to the subjective feeling of confidence in humans. These results have important implications for psychiatry, since disorders of confidence computations appear to contribute to a number of psychopathologies. More broadly, this computational approach to emotions resonates with the emerging view that psychiatric nosology may be best parameterized in terms of disorders of the cognitive computations underlying complex behavior.

Original languageEnglish
Pages (from-to)391-401
Number of pages11
JournalDialogues in Clinical Neuroscience
Issue number4
StatePublished - 2015


  • Computational psychiatry
  • Decision confidence
  • Decision making
  • Model-based neuroscience
  • RDoC
  • Research domain criteria


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