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on Neuroeconomics |
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Issue of 2010‒09‒25
three papers chosen by |
| By: | John B. Davis (Department of Economics, Marquette University, and Amsterdam School of Economics, University of Amsterdam) |
| Abstract: | This paper asks whether neuroeconomics will make instrumental use of neuroscience to adjudicate existing disputes in economics or be more seriously informed by neuroscience in ways that might transform economics. The paper pursues the question by asking how neuroscience constructs an understanding of individuals as whole persons. The body of the paper is devoted to examining two approaches: Don Ross’s neurocellular approach to neuroeconomics and Joseph Dumit’s cultural anthropological science organization approach. The accounts are used to identify boundaries on single individual explanations. With that space Andy Clark’s external scaffolding view and Nathaniel Wilcox’s socially distributed cognition view are employed. |
| Keywords: | neuroeconomics, behavioral economics, neurocellular economics |
| JEL: | A12 B41 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:mrq:wpaper:1001&r=neu |
| By: | Kannan, Srinivasan |
| Abstract: | Emergence of “Glass ceiling” like phenomena in the minds of professionals doing research in a multidisciplinary subject needs to be studied. For an example, computational neurosciences(CNS) comprises of neurology, cognitive science, psychology, computer science, physics, mathematics, information technology, radiology, anthropology, sociology, and biology. When a specialist doing research in a multidisciplinary science like computational neuroscience, know less about other disciplines. This at times leads to tension among the members of the multidisciplinary group. This may create an environment where some members feel excluded. This may also lead to a power structure among different professionals. In case of CNS, the biological scientists feel the computational and engineering sciences may use their mathematical power to control them. On the other hand the engineering scientists feel they need to learn more about biology to understand CNS. The highly technical medical specialist such as Electro physiologists were also feeling like the biologists. As computational neurosciences gaining more importance, it is important to understand the interaction among the scientists from different disciplines and its effect on the development of discipline. The present paper is an attempt to study the dynamics of the members of the multidisciplinary group, who have done their short course on CNS. |
| Keywords: | Multidisciplinary Research; Computational Neuroscience; interaction; education; research |
| JEL: | A3 I23 D89 A29 D40 J24 |
| Date: | 2010–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:25090&r=neu |
| By: | Kontek, Krzysztof |
| Abstract: | This paper presents a review of adaptation concepts at the evolutionary, environmental, neural, sensory, mental and mathematical levels, including Helson’s and Parducci’s theories of perception and category judgments. Two kinds of adaptation can be clearly distinguished. The first, known as level adaptation, refers to the shift of the neutral perception level to the average stimulus value. It results in a single reference point and stimuli changes represented in absolute terms. This concept is employed by Prospect Theory, which assumes that gains and losses are perceived as monetary amounts. The second kind of adaptation refers to the adjustment of perception sensitivity to stimuli range. It results in two reference points (minimum and maximum stimulus) and stimuli changes perceived in relative terms. Both range adaptation and range relativity are well documented phenomena and have even been confirmed by the creators of Prospect Theory. This makes room for another decision making theory based on the range relativity approach. As shown by Kontek (2009), such a theory would not require the concept of probability weighting to describe lottery experiments or behavioral paradoxes. |
| Keywords: | Adaptation-Level Theory; Range-Frequency Theory; Prospect Theory |
| JEL: | D81 C91 D87 |
| Date: | 2010–09–19 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:25169&r=neu |