Recurrent, robust and scalable patterns underlie human approach and avoidance.

PLoS One

Motivation and Emotion Neuroscience Collaboration, Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.

Published: May 2010

AI Article Synopsis

  • The study explores how approach and avoidance behaviors can quantify the value of stimuli, using keypress tasks to assess people's reactions to rewarding or aversive images, like beautiful faces or food.
  • Experiments showed consistent, law-like patterns across different stimuli, indicating individuals balance approach and avoidance behaviors, with findings that align with theories on preference and risk.
  • The conclusions suggest that these patterns reflect underlying psychological principles, indicating a structured way in which people respond to different types of motivation, applicable to theories like prospect theory and utility assessment.

Article 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).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2879576PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0010613PLOS

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