Effects of chronic cannabinoid exposure during adolescence on reward preference and mPFC activation in adulthood

Assessing the Variations in Reward Preference for Local Government Employees in Terms of Position, Public Service Motivation, and Public Sector Motivation

Public Performance & Management Review ◽

10.2753/pmr1530-9576370402 ◽

2014 ◽

Vol 37 (4) ◽

pp. 552-576 ◽

Cited By ~ 9

Author(s):

P. Edward French ◽

Melissa C. Emerson

Keyword(s):

Public Sector ◽

Local Government ◽

Public Service ◽

Public Service Motivation ◽

Government Employees ◽

Reward Preference

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A taxonomy of reward preference: Examining country differences

Journal of International Management ◽

10.1016/j.intman.2005.06.004 ◽

2005 ◽

Vol 11 (3) ◽

pp. 357-375 ◽

Cited By ~ 24

Author(s):

Flora F.T. Chiang ◽

Thomas A. Birtch

Keyword(s):

Country Differences ◽

Reward Preference

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Relative reward preference in primate orbitofrontal cortex

Nature ◽

10.1038/19525 ◽

1999 ◽

Vol 398 (6729) ◽

pp. 704-708 ◽

Cited By ~ 751

Author(s):

Léon Tremblay ◽

Wolfram Schultz

Keyword(s):

Orbitofrontal Cortex ◽

Reward Preference

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The IntelliCage System: A Review of Its Utility as a Novel Behavioral Platform for a Rodent Model of Substance Use Disorder

Frontiers in Behavioral Neuroscience ◽

10.3389/fnbeh.2021.683780 ◽

2021 ◽

Vol 15 ◽

Author(s):

Ismail Nurul Iman ◽

Nurul Aiman Mohd Yusof ◽

Ummi Nasrah Talib ◽

Nur Aimi Zawami Ahmad ◽

Anwar Norazit ◽

...

Keyword(s):

Substance Use ◽

Substance Use Disorder ◽

High Throughput Screening ◽

Molecular Mechanisms ◽

Learning System ◽

Substance Addiction ◽

System A ◽

Automated Learning ◽

Cognitive Pattern ◽

Reward Preference

The use of animal models for substance use disorder (SUD) has made an important contribution in the investigation of the behavioral and molecular mechanisms underlying substance abuse and addiction. Here, we review a novel and comprehensive behavioral platform to characterize addiction-like traits in rodents using a fully automated learning system, the IntelliCage. This system simultaneously captures the basic behavioral navigation, reward preference, and aversion, as well as the multi-dimensional complex behaviors and cognitive functions of group-housed rodents. It can reliably capture and track locomotor and cognitive pattern alterations associated with the development of substance addiction. Thus, the IntelliCage learning system offers a potentially efficient, flexible, and sensitive tool for the high-throughput screening of the rodent SUD model.

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