Kalidindi, Kiran and Bowman, H. (2007) Using e-greedy reinforcement learning methods to further understand ventromedial prefrontal patients' deficits on the Iowa Gambling Task. Neural Networks, 20 (6). pp. 676-689. ISSN 0893-6080.
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An important component of decision making is evaluating the expected result of a choice, using past experience. The way past experience is used to predict future rewards and punishments can have profound effects on decision making. The aim of this study is to further understand the possible role played by the ventromedial prefrontal cortex in decision making, using results from the Iowa Gambling Task (IGT). A number of theories in the literature offer potential explanations for the underlying cause of the deficit(s) found in bilateral ventromedial prefrontal lesion (VMF) patients on the IGT. An errordriven e-greedy reinforcement learning method was found to produce a good match to both human normative and VMF patient groups from a number of studies. The model supports the theory that the VMF patients are less strategic (more explorative), which could be due to a working memory deficit, and are more reactive than healthy controls. This last aspect seems consistent with a myopia for future consequences.
|Additional information:||In Press|
|Uncontrolled keywords:||Iowa gambling task, ventromedial prefrontal cortex, orbitofrontal cortex, reinforcement learning, decision making|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group|
|Depositing User:||Mark Wheadon|
|Date Deposited:||24 Nov 2008 18:05|
|Last Modified:||20 Apr 2012 11:38|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/14601 (The current URI for this page, for reference purposes)|
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