Emotion: Computational modeling

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

The neural basis of human emotions is difficult to study, because emotions are primarily subjective and nondeterministic. To find basic principles of emotions and their underlying mechanisms, neuroscientists typically study specific emotions, using specific tasks. They use a combination of animal and human preparations, yielding various types of data, from single neuron firing patterns, to activation levels of a whole brain area. The approach, while rigorous, is slow and yields an increasingly complex body of often conflicting data. An integrative approach is needed. As described in this article, computational models of emotion have emerged as a promising tool for integration. Because these models require that all assumptions be made explicit, they offer a new language in which to express and test hypotheses and to explain and predict neural mechanisms.

Original languageEnglish (US)
Title of host publicationEncyclopedia of Neuroscience
PublisherElsevier Ltd.
Pages909-913
Number of pages5
ISBN (Print)9780080450469
DOIs
StatePublished - Jan 1 2009

ASJC Scopus subject areas

  • Neuroscience(all)

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    Fellous, J. M. (2009). Emotion: Computational modeling. In Encyclopedia of Neuroscience (pp. 909-913). Elsevier Ltd.. https://doi.org/10.1016/B978-008045046-9.01845-3