Punishment-Based Decision Making Various

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Kindle Edition

395 pages


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Punishment-Based Decision Making  by  Various

Punishment-Based Decision Making by Various
| Kindle Edition | PDF, EPUB, FB2, DjVu, talking book, mp3, ZIP | 395 pages | ISBN: | 10.37 Mb

This collection of articles covers issues in psychology, behavioral economics, and cognitive neuroscience investigating the neural structures and mechanisms underlying approach, and avoidance behavior in the face of rewards and punishments. TheMoreThis collection of articles covers issues in psychology, behavioral economics, and cognitive neuroscience investigating the neural structures and mechanisms underlying approach, and avoidance behavior in the face of rewards and punishments. The objective is to understand the nature of critical differences and asymmetries between the ways that appetitive and aversive outcomes are processed by the brain.

A number of topics are covered, such as the development of economic models integrating costs and benefits into a single value, neuroimaging approaches of appetitive and aversive conditioning, reward-punishment interactions, pain and defensive behavior, the role of dopamine neurons in aversive conditioning, and the interactions between serotonin and dopamine in punishment, pain, and aversion.

The neural bases of reward-punishment interactions are of great interest to a broad readership because of the fundamental role of dopamine and serotonin in a number of motivational and decision processes, and because of their theoretical and clinical implications for understanding dysfunctions of these two systems. Findings in this research field are also important to basic neuroscientists interested in the computational processes of pain and aversive learning and cognitive psychologists working on conditioning/reinforcement.

Punishment-based decision making and reward processing cover a wide range of topics and levels of analysis, from basic neural mechanisms and computational models of appetitive and aversive conditioning, to the system neuroscience level.



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