Comparison of probabilistic choice models in humans
- PDF / 318,771 Bytes
- 8 Pages / 610 x 792 pts Page_size
- 3 Downloads / 188 Views
BioMed Central
Open Access
Short paper
Comparison of probabilistic choice models in humans Taiki Takahashi*1, Hidemi Oono2 and Mark HB Radford2 Address: 1Department of Life Sciences, Unit of Cognitive and Behavioral Sciences, School of Arts and Sciences, The University of Tokyo, 21 COE office, 3-8-1 Komaba, Meguro-ku, Tokyo, 153-8902, Japan and 2Department of Behavioral Science, Faculty of Letters, Hokkaido University, N.10, W.7, Kita-ku, Sapporo, 060-0810, Japan Email: Taiki Takahashi* - [email protected]; Hidemi Oono - [email protected]; Mark HB Radford - [email protected] * Corresponding author
Published: 20 April 2007 Behavioral and Brain Functions 2007, 3:20
doi:10.1186/1744-9081-3-20
Received: 11 November 2006 Accepted: 20 April 2007
This article is available from: http://www.behavioralandbrainfunctions.com/content/3/1/20 © 2007 Takahashi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: Probabilistic choice has been attracting attention in psychopharmacology and neuroeconomics. Several parametric models have been proposed for probabilistic choice; entropy model, Prelec's probability weight function, and hyperbola-like probability discounting functions. Methods: In order to examine (i) fitness of the probabilistic models to behavioral data, (ii) relationships between the parameters and psychological processes, e.g., aversion to possible nongain in each probabilistic choice and aversion to unpredictability, we estimated the parameters and AICc (Akaike Information Criterion with small sample correction) of the probabilistic choice models by assessing the points of subjective equality at seven probability values (95%–5%). We examined both fitness of the models parametrized by utilizing AICc, and the relationships between the model parameters and equation-free parameter of aversion to possible non-gain. Results: Our results have shown that (i) the goodness of fitness for group data was [Entropy model>Prelec's function>General hyperbola>Simple hyperbola]; while Prelec's function best fitted individual data, (ii) aversion to possible non-gain and aversion to unpredictability are distinct psychological processes. Conclusion: Entropy and Prelec models can be utilized in psychopharmacological and neuroeconomic studies of risky decision-making.
Background Studies in psychopharmacology, neuroscience, and behavioral economics have revealed that humans and non-human animals discount the value of probabilistic rewards as the receipt becomes more uncertain ("probability discounting", [1-5]). Because pathological gambling and drug misuse are associated with low degree of aversion to uncertainty in probabilistic choice, it is of psychopharmacological interest to examine probabilistic choice models. In neoclassical ec
Data Loading...
