Contrast effects or loss aversion? Comment on Usher and McClelland (2004)

Psychological Review

Volumn 112, Issue 1, 2005, Pages 253-255

  Busemeyer, Jerome R ^a   Townsend, James T ^a   Diederich, Adele ^b,d   Barkan, Rachel ^c  

^a INDIANA UNIVERSITY   (United States)

^b International University   (Germany)

^c BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

^d UNIVERSITY OF BREMEN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; HUMAN; METHODOLOGY; PSYCHOLOGICAL MODEL; PSYCHOLOGICAL THEORY; PSYCHOLOGY; REVIEW; STATISTICS;

CHOICE BEHAVIOR; HUMANS; MODELS, PSYCHOLOGICAL; PSYCHOLOGICAL THEORY; PSYCHOLOGY;

EID: 12344261685     PISSN: 0033295X     EISSN: None     Source Type: Journal    
DOI: 10.1037/0033-295X.112.1.253     Document Type: Review

References (17)

1. Anderson, J. A. (1997). An introduction to neural networks. Cambridge, MA: MIT Press.
2. Barkan, R., & Busemeyer, J. R. (2003). Modeling dynamic inconsistency with a changing reference point. Journal of Behavioral Decision Making, 16, 235-255.
3. Brown, J., Bullock, D., & Grossberg, S. (1999). How the basal ganglia use parallel excitatory and inhibitory learning pathways to selectively respond to unexpected rewarding cues. Journal of Neuroscience, 19, 10502-10511.
4. Busemeyer, J. R., & Johnson, J. G. (2004). Computational models of decision making. In D. Koehler & N. Harvey (Eds.), Handbook of judgment and decision making (pp. 133-154). Oxford, England: Blackwell.
5. Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A dynamic cognition approach to decision making. Psychological Review, 100, 432-459.
6. Diederich, A. (2003). Decision making under conflict: Decision time as a measure of conflict strength. Psychonomic Bulletin & Review, 10, 167-175.
7. Grossberg, S. (1988). Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Networks, 1, 17-61.
8. Grossberg, S., & Gutowski, W. E. (1987). Neural dynamics of decision making under risk: Affective balance and cognitive-emotional interactions. Psychological Review, 94, 300-318.
9. Guo, F. Y., & Holyoak, K. J. (2002). Understanding similarity in choice behavior: A connectionist model. In W. D. Gray & C. D. Schunn (Eds.), Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society (pp. 393-398). Mahwah, NJ: Erlbaum.
10. Houk, J. C., Adams, J. L., & Barto, A. G. (1995). A model of how the basal ganglia generate and use neural signals that predict reinforcement. In J. C. Houk, J. L. Davis, & D. G. Beiser (Eds.), Models of information processing in the basal ganglia (pp. 249-270). Cambridge, MA: MIT Press.
11. Roe, R., Busemeyer, J. R., & Townsend, J. T. (2001). Multialternative decision field theory: A dynamic connectionist model of decision-making. Psychological Review, 108, 370-392.
12. Simonson, I. (1989). Choice based on reasons: The case of attraction and compromise effects. Journal of Consumer Research, 16, 158-174.
13. Townsend, J. T., & Busemeyer, J. R. (1989). Approach-Avoidance: Return to dynamic decision behavior. In C. Izawa (Ed.), Current issues in cognitive processes: The Tulane Flowerree Symposium on Cognition (pp. 107-133). Hillsdale, NJ: Erlbaum.
14. Tversky, A. (1972). Elimination by aspects: A theory of choice. Psychological Review, 79, 281-299.
15. Tversky, A., & Simonson, I. (1993). Context dependent preferences. Management Science, 39, 1179-1189.
16. Usher, M., & McClelland, J. L. (2004). Loss aversion and inhibition in dynamical models of multialternative choice. Psychological Review, 111, 757-769.
17. Wedell, D. (2003). [The interrelationship of different decoy effects on risky choice]. Unpublished raw data, University of South Carolina.