Title |
Neurobiological underpinnings of reward anticipation and outcome evaluation in gambling disorder
|
---|---|
Published in |
Frontiers in Behavioral Neuroscience, March 2014
|
DOI | 10.3389/fnbeh.2014.00100 |
Pubmed ID | |
Authors |
Jakob Linnet |
Abstract |
Gambling disorder is characterized by persistent and recurrent maladaptive gambling behavior, which leads to clinically significant impairment or distress. The disorder is associated with dysfunctions in the dopamine system. The dopamine system codes reward anticipation and outcome evaluation. Reward anticipation refers to dopaminergic activation prior to reward, while outcome evaluation refers to dopaminergic activation after reward. This article reviews evidence of dopaminergic dysfunctions in reward anticipation and outcome evaluation in gambling disorder from two vantage points: a model of reward prediction and reward prediction error by Wolfram Schultz et al. and a model of "wanting" and "liking" by Terry E. Robinson and Kent C. Berridge. Both models offer important insights on the study of dopaminergic dysfunctions in addiction, and implications for the study of dopaminergic dysfunctions in gambling disorder are suggested. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 20% |
Unknown | 4 | 80% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Unknown | 92 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 21 | 23% |
Researcher | 14 | 15% |
Student > Master | 11 | 12% |
Student > Bachelor | 10 | 11% |
Student > Doctoral Student | 6 | 6% |
Other | 7 | 8% |
Unknown | 24 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 32 | 34% |
Neuroscience | 13 | 14% |
Medicine and Dentistry | 5 | 5% |
Agricultural and Biological Sciences | 4 | 4% |
Computer Science | 2 | 2% |
Other | 4 | 4% |
Unknown | 33 | 35% |