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Recurrent, Robust and Scalable Patterns Underlie Human Approach and Avoidance

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dc.contributor.author Kim, Byoung Woo en_US
dc.contributor.author Kennedy, David N. en_US
dc.contributor.author Lehár, Joseph en_US
dc.contributor.author Lee, Myung Joo en_US
dc.contributor.author Blood, Anne J. en_US
dc.contributor.author Lee, Sang en_US
dc.contributor.author Perlis, Roy H. en_US
dc.contributor.author Smoller, Jordan W. en_US
dc.contributor.author Morris, Robert en_US
dc.contributor.author Fava, Maurizio en_US
dc.contributor.author Breiter, Hans C. en_US
dc.date.accessioned 2012-01-11T21:11:32Z
dc.date.available 2012-01-11T21:11:32Z
dc.date.issued 2010-5-26 en_US
dc.identifier.citation Kim, Byoung Woo, David N. Kennedy, Joseph Lehár, Myung Joo Lee, Anne J. Blood, Sang Lee, Roy H. Perlis, Jordan W. Smoller, Robert Morris, Maurizio Fava, Hans C. Breiter. "Recurrent, Robust and Scalable Patterns Underlie Human Approach and Avoidance" PLoS ONE 5(5): e10613. (2010) en_US
dc.identifier.issn 1932-6203 en_US
dc.identifier.uri http://hdl.handle.net/2144/3215
dc.description.abstract BACKGROUND. Approach and avoidance behavior provide a means for assessing the rewarding or aversive value of stimuli, and can be quantified by a keypress procedure whereby subjects work to increase (approach), decrease (avoid), or do nothing about time of exposure to a rewarding/aversive stimulus. To investigate whether approach/avoidance behavior might be governed by quantitative principles that meet engineering criteria for lawfulness and that encode known features of reward/aversion function, we evaluated whether keypress responses toward pictures with potential motivational value produced any regular patterns, such as a trade-off between approach and avoidance, or recurrent lawful patterns as observed with prospect theory. METHODOLOGY/PRINCIPAL FINDINGS. Three sets of experiments employed this task with beautiful face images, a standardized set of affective photographs, and pictures of food during controlled states of hunger and satiety. An iterative modeling approach to data identified multiple law-like patterns, based on variables grounded in the individual. These patterns were consistent across stimulus types, robust to noise, describable by a simple power law, and scalable between individuals and groups. Patterns included: (i) a preference trade-off counterbalancing approach and avoidance, (ii) a value function linking preference intensity to uncertainty about preference, and (iii) a saturation function linking preference intensity to its standard deviation, thereby setting limits to both. CONCLUSIONS/SIGNIFICANCE. These law-like patterns were compatible with critical features of prospect theory, the matching law, and alliesthesia. Furthermore, they appeared consistent with both mean-variance and expected utility approaches to the assessment of risk. Ordering of responses across categories of stimuli demonstrated three properties thought to be relevant for preference-based choice, suggesting these patterns might be grouped together as a relative preference theory. Since variables in these patterns have been associated with reward circuitry structure and function, they may provide a method for quantitative phenotyping of normative and pathological function (e.g., psychiatric illness). en_US
dc.description.sponsorship National Institute on Drug Abuse (14118, 026002, 026104, DABK39-03-0098, DABK39-03-C-0098); The MGH Phenotype Genotype Project in Addiction and Mood Disorder from the Office of National Drug Control Policy - Counterdrug Technology Assessment Center; MGH Department of Radiology; the National Center for Research Resources (P41RR14075); National Institute of Neurological Disorders and Stroke (34189, 05236) en_US
dc.language.iso en en_US
dc.publisher Public Library of Science en_US
dc.rights Kim et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. en_US
dc.title Recurrent, Robust and Scalable Patterns Underlie Human Approach and Avoidance en_US
dc.type article en_US
dc.identifier.doi 10.1371/journal.pone.0010613 en_US
dc.identifier.pubmedid 20532247 en_US
dc.identifier.pmcid 2879576 en_US


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