Reward and decision making in corticobasal ganglia networks
著者
書誌事項
Reward and decision making in corticobasal ganglia networks
（Annals of the New York Academy of Sciences, v. 1104）
Blackwell Pub. on behalf of the New York Academy of Sciences, c2007
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注記
Includes bibliographical references and index
"This volume is the result of a conference entitled Reward and Decision-Making in Cortico-basal Gangila Networks held at the UCLA Conference Center, Lake Arrowhead, California, on June 1-4, 2006. "--contents p.
内容説明・目次
内容説明
The neural bases of decision-making processes are currently generating considerable experimental and theoretical interest. Several recent developments in neuroscience, psychology, and economics have helped to focus thinking on this issue: the computational description of cortico-striatal networks in terms of reinforcement learning models, recognition that midbrain dopaminergic activity could reflect an error correction learning signal, improvements in imaging technology, the recognition that multiple controllers of actions and of values contribute to the development of adaptive behavior, and the recognition that theories of value derived from economics can provide a principled means of incorporating intangible factors such as risk, uncertainty, and temporal discounting into computational models of neural system.
The contributions to this volume are forward-looking assessments of the current and future issues likely to be faced by researchers in this area. Four current issues are specifically addressed:
- the degree to which distinct behavioral and psychological capacities map onto discrete neural systems;
- the relationship between midbrain dopamine activity and reward in terms of phasic and tonic activity, prefrontal and striatal targets, and whether and what limits exist in terms of learning;
- whether there are multiple prediction error signals distinguishing between, for example, reward and punishment, instrumental versus Pavlovian conditioning, goals and habits, learning with different discount factors, real versus fictive learning; and
- the relationship between economics and neuroscience, which has recently emerged in a marriage to form the new field of neuroeconomics. Will this marriage be productive for the long term or swiftly head for divorce?
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目次
Overview.
1. Learning About Multiple Attributes of Reward in Pavlovian Conditioning: Andrew R. Delamater and Stephen Oakeshott.
2. Should I Stay or Should I Go? Transformation of Time-discounted Rewards in Orbitofrontal Cortex and Associated Brain Circuits: M.R. Roesch, D.J. Calu, K.A. Burke, and G. Schoenbaum.
3. Model-based fMRI and its Application to Reward-learning and Decision Making: John P. O'Doherty, Alan Hampton and Hackjin Kim.
4. Splitting the Difference: How Does the Brain Code Reward Episodes?: Brian Knutson and G. Elliott Wimmer.
5. Reward-related Responses in the Human Striatum: Mauricio R. Delgado.
6. Integration of Cognitive and Motivational Information in the Primate Lateral Prefrontal Cortex: Masamichi Sakagami and Masataka Watanabe.
7. Mechanisms of Reinforcement Learning and Decision Making in the Primate Dorsolateral Prefrontal Cortex: Daeyeol Lee and Hyojung Seo.
8. Resisting the Power of Temptations: The Right Prefrontal Cortex and Self-control: Daria Knoch and Ernst Fehr.
9. Adding Prediction Risk to the Theory of Reward Learning: Kerstin Preuschoff and Peter Bossaerts.
10. Still at the Choice-point: Action Selection and Initiation in Instrumental Conditioning: Bernard W. Balleine and Sean B. Ostlund.
11. Plastic Corticostriatal Circuits for Action Learning: What's Dopamine Got to Do with It?: Rui Costa.
12. Striatal Contributions to Reward and Decision Making: Making Sense of Regional Variations in a Reiterated Processing Matrix: Jeffery R. Wickens, Christopher S. Budd, Brian I. Hyland, and Gordon W. Arbuthnott.
13. Multiple Representations of Belief States and Action Values in Cortico-basal Ganliga Loops: Kazuyuki Samejima and Kenji Doya.
14. Basal Ganglia Mechanisms of Reward-oriented Eye Movement: Okihide Hikosaka.
15. Contextual Control of Choice Performance: Behavioral, Neurobiological, and Neuro-chemical Influences: J.E. Haddon and S. Killcross.
16. A "Good Parent" Function for Dopamine: Transient Modulation of Learning and Performance During Early Stages of Training: Jon C Horvitz, Won Yung Choi, Cecile Morvan, Yaniv Eyny and Peter Balsam.
17. Serotonin and the Evaluation of Future Rewards: Theory, Experiments, and Possible Neural Mechanisms: Nicolas Schweighofer, Saori C. Tanaka, and Kenji Doya.
18. Receptor Theory and Biological Constraints on Value: Gregory S. Berns, C. Monica Capra, and Charles Noussair.
19. Reward Prediction Error Computation in the Pedunculopontine Tegmental Nucleus Neurons: Yasushi Kobayashi and Kenichi Okada.
20. A Computational Model of Craving and Obsession: David Redish and Adam Johnson.
21. Calculating the Cost of Acting in Prefrontal Cortex: Mark E. Walton, Peter H. Rudebeck, David M. Bannerman, and Matthew F. S. Rushworth.
22. Cost, Benefit, Tonic, Phasic: What Do Response Rates Tell Us About Dopamine and Motivation?: Yael Niv.
Index of Contributors
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