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Research Article

Mice Gamble for Food: Individual Differences in Risky Choices and Prefrontal Cortex Serotonin

Elsa Pittaras1,2, Arnaud Cressant1, Pierre Serreau1, Jessica Bruijel1, Françoise Dellu-Hagedorn3, Jacques Callebert4, Arnaud Rabat2 and Sylvie Granon1*

1Centre de Neuroscience Paris Sud, CNRS 8195, Université Paris Sud, Orsay, France

2Institut de Recherche Biomédicale des Armées, Brétigny-sur-Orge, France

3INCIA, CNRS, Université Bordeaux 2, Bordeaux, France

4Hôpital Lariboisière, Paris, France

*Corresponding Author:
Sylvie Granon
Centre de Neuroscience Paris Sud, CNRS 8195
Université Paris Sud, Orsay, France
E-mail: [email protected]

Received May 23, 2013; Accepted June 19, 2013; Published June 26, 2013

Citation: Pittaras E, Cressant A, Serreau P, Bruijel J, Dellu-Hagedorn F, et al. (2013) Mice Gamble for Food: Individual Differences in Risky Choices and Prefrontal Cortex Serotonin. J Addict Res Ther S4: 011. doi:10.4172/2155-6105.S4-011

Copyright: © 2013 Pittaras E, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: One of the fundamental questions in Neuroscience is to understand how we choose one option instead of another one when we are in uncertain or ambiguous situation. Some decisions have short- and long-term consequences. The Iowa Gambling Task (IGT) is classically used to study decision-making in humans because it mimics real life situations. By developing a new mice model, we aimed at studying behavioral traits and brain circuits that impact on inter-individual differences in decision making processes.

Methods: 72 male C57Bl/6J mice were used to adapt the IGT. We first attempted to adapt the task in operant chambers from rats’ works using long delays as penalties. Our results were not conclusive so we adapted the task to a maze version. Quinine pellets were used as penalties and food pellets as rewards. We also performed behavioral measures of anxiety, novelty exploration, locomotion and social interaction. Finally, we measured levels of monoamines in different brain tissues sampled from the mice subjected to the behavioral task.

Results: We show that transferring directly the protocol of the rat’s gambling task to mice using operant conditioning was not successful presumably because of species particularities, such as lower sensitivity to delay penalties. In the maze version, we found that mice exhibited a clear preference for small but safer rewards that allow the maximization of benefits in the long-term. We observed the progressive emergence of inter-individuals differences and specific behavioral and biochemical traits for each subgroup. Namely, risk-prone mice exhibited lower 5-HT level in the prefrontal cortex compared to the others.

Conclusion: We were thus able to validate a mouse gambling task and to determine individual profile close to the human and rat results. This study allows us to characterize within a healthy population, subgroups with different behavioral and biochemical profiles.

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