Title |
Nonhuman gamblers: lessons from rodents, primates, and robots
|
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Published in |
Frontiers in Behavioral Neuroscience, January 2014
|
DOI | 10.3389/fnbeh.2014.00033 |
Pubmed ID | |
Authors |
Fabio Paglieri, Elsa Addessi, Francesca De Petrillo, Giovanni Laviola, Marco Mirolli, Domenico Parisi, Giancarlo Petrosino, Marialba Ventricelli, Francesca Zoratto, Walter Adriani |
Abstract |
The search for neuronal and psychological underpinnings of pathological gambling in humans would benefit from investigating related phenomena also outside of our species. In this paper, we present a survey of studies in three widely different populations of agents, namely rodents, non-human primates, and robots. Each of these populations offers valuable and complementary insights on the topic, as the literature demonstrates. In addition, we highlight the deep and complex connections between relevant results across these different areas of research (i.e., cognitive and computational neuroscience, neuroethology, cognitive primatology, neuropsychiatry, evolutionary robotics), to make the case for a greater degree of methodological integration in future studies on pathological gambling. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 40% |
Ireland | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 80% |
Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Germany | 2 | 2% |
Switzerland | 1 | 1% |
United Kingdom | 1 | 1% |
Canada | 1 | 1% |
United States | 1 | 1% |
Unknown | 88 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 30 | 32% |
Student > Ph. D. Student | 18 | 19% |
Student > Doctoral Student | 7 | 7% |
Student > Postgraduate | 6 | 6% |
Student > Master | 6 | 6% |
Other | 10 | 11% |
Unknown | 17 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 24 | 26% |
Neuroscience | 17 | 18% |
Agricultural and Biological Sciences | 8 | 9% |
Medicine and Dentistry | 5 | 5% |
Computer Science | 3 | 3% |
Other | 13 | 14% |
Unknown | 24 | 26% |