Emotion: Computational Modeling

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.

[1]  Antônio C. Roque-da-Silva,et al.  Anxiety-like behavior in rats: a computational model , 2000, Neural Networks.

[2]  Joseph E LeDoux,et al.  Stimulus generalization of fear responses: effects of auditory cortex lesions in a computational model and in rats. , 1997, Cerebral cortex.

[3]  David Sander,et al.  A systems approach to appraisal mechanisms in emotion , 2005, Neural Networks.

[4]  Y Shoda,et al.  Reconciling processing dynamics and personality dispositions. , 1998, Annual review of psychology.

[5]  R. Davidson Affective neuroscience and psychophysiology: toward a synthesis. , 2003, Psychophysiology.

[6]  T. Dalgleish The emotional brain , 2004, Nature Reviews Neuroscience.

[7]  M. Frank,et al.  Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal. , 2006, Psychological review.

[8]  P. Thagard,et al.  Spiking Phineas Gage: a neurocomputational theory of cognitive-affective integration in decision making. , 2004, Psychological review.

[9]  Roddy Cowie,et al.  Emotion and brain: Understanding emotions and modelling their recognition , 2005, Neural Networks.

[10]  B. Heerebout,et al.  A Computational Study into the Evolution of Dual-Route Dynamics for Affective Processing , 2003, Journal of Cognitive Neuroscience.

[11]  E. Rolls,et al.  Synaptic and spiking dynamics underlying reward reversal in the orbitofrontal cortex. , 2004, Cerebral cortex.

[12]  Jonathan D. Cohen,et al.  Computational modeling of emotion: explorations through the anatomy and physiology of fear conditioning , 1997, Trends in Cognitive Sciences.