The Value of Numbers in Economic Rewards

Previous work has identified a distributed network of neural systems involved in appraising the value of rewards, such as when winning $100 versus $1. These studies, however, confounded monetary value and the number used to represent it, which leads to the possibility that some elements in the network may be specialized for processing numeric rather than monetary value. To test this hypothesis, we manipulated numeric magnitude and units to construct a range of economic rewards for simple decisions (e.g., 1¢, $1, 100¢, $100). Consistent with previous research in numerical cognition, results showed that blood-oxygen-level-dependent (BOLD) activity in intraparietal sulcus was correlated with changes in numeric magnitude, independent of monetary value, whereas activity in orbitofrontal cortex was correlated with monetary value, independent of numeric magnitude. Finally, region-of-interest analyses revealed that the BOLD response to numeric magnitude, but not monetary value, described a compressive function. Together, these findings highlight the importance of numerical cognition for understanding how the brain processes monetary rewards.

[1]  E. Miller,et al.  Analog Numerical Representations in Rhesus Monkeys: Evidence for Parallel Processing , 2004, Journal of Cognitive Neuroscience.

[2]  Sabrina M. Tom,et al.  The Neural Basis of Loss Aversion in Decision-Making Under Risk , 2007, Science.

[3]  S. Dehaene,et al.  THREE PARIETAL CIRCUITS FOR NUMBER PROCESSING , 2003, Cognitive neuropsychology.

[4]  Philippe Pinel,et al.  Tuning Curves for Approximate Numerosity in the Human Intraparietal Sulcus , 2004, Neuron.

[5]  C. Padoa-Schioppa,et al.  The representation of economic value in the orbitofrontal cortex is invariant for changes of menu , 2008, Nature Neuroscience.

[6]  Ellen E. Furlong,et al.  Cognitive Constraints on How Economic Rewards Affect Cooperation , 2009, Psychological science.

[7]  Elizabeth M. Brannon,et al.  The Neural Development of an Abstract Concept of Number , 2009, Journal of Cognitive Neuroscience.

[8]  R. Poldrack Region of interest analysis for fMRI. , 2007, Social cognitive and affective neuroscience.

[9]  Michael L. Platt,et al.  Neural correlates of decision variables in parietal cortex , 1999, Nature.

[10]  R. Cohen Kadosh,et al.  Numerical representation in the parietal lobes: abstract or not abstract? , 2009, The Behavioral and brain sciences.

[11]  Emily Bell,et al.  Striatal topography of probability and magnitude information for decisions under uncertainty , 2012, NeuroImage.

[12]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[13]  Dirk J. Heslenfeld,et al.  Activity in human reward-sensitive brain areas is strongly context dependent , 2005, NeuroImage.

[14]  William A. Cunningham,et al.  Distinct Orbitofrontal Regions Encode Stimulus and Choice Valuation , 2009, Journal of Cognitive Neuroscience.

[15]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[16]  S. Dehaene,et al.  A Magnitude Code Common to Numerosities and Number Symbols in Human Intraparietal Cortex , 2007, Neuron.

[17]  E. Rolls,et al.  Decision‐making and Weber's law: a neurophysiological model , 2006, The European journal of neuroscience.

[18]  Daniel Ansari,et al.  Developmental Specialization in the Right Intraparietal Sulcus for the Abstract Representation of Numerical Magnitude , 2010, Journal of Cognitive Neuroscience.

[19]  C. Padoa-Schioppa,et al.  Neurons in the orbitofrontal cortex encode economic value , 2006, Nature.

[20]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[21]  Scott A. Huettel,et al.  Local pattern classification differentiates processes of economic valuation , 2009, NeuroImage.

[22]  Leif D. Nelson,et al.  False-Positive Psychology , 2011, Psychological science.

[23]  R. Adolphs,et al.  Social and monetary reward learning engage overlapping neural substrates. , 2012, Social cognitive and affective neuroscience.

[24]  E. J. Carter,et al.  Functional Imaging of Numerical Processing in Adults and 4-y-Old Children , 2006, PLoS biology.

[25]  P. Glimcher,et al.  The Neurobiology of Decision: Consensus and Controversy , 2009, Neuron.

[26]  Margot J. Taylor,et al.  Is 2+2=4? Meta-analyses of brain areas needed for numbers and calculations , 2011, NeuroImage.

[27]  Bruce Fischl,et al.  Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.

[28]  P. Glimcher,et al.  Reward Value-Based Gain Control: Divisive Normalization in Parietal Cortex , 2011, The Journal of Neuroscience.

[29]  Paul Glimcher,et al.  Physiological utility theory and the neuroeconomics of choice , 2005, Games Econ. Behav..

[30]  Ellen Peters,et al.  Assessing “Economic Value” , 2014, Psychological science.

[31]  Colin Camerer,et al.  Transformation of stimulus value signals into motor commands during simple choice , 2011, Proceedings of the National Academy of Sciences.

[32]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[33]  Andreas Nieder,et al.  Compressed Scaling of Abstract Numerosity Representations in Adult Humans and Monkeys , 2009, Journal of Cognitive Neuroscience.

[34]  Colin Camerer,et al.  Neuroeconomics: decision making and the brain , 2008 .

[35]  Daniel Västfjäll,et al.  Intuitive Numbers Guide Decisions , 2008, Judgment and Decision Making.

[36]  J. O'Doherty,et al.  Dissociating Valence of Outcome from Behavioral Control in Human Orbital and Ventral Prefrontal Cortices , 2003, The Journal of Neuroscience.

[37]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[38]  J. O'Doherty,et al.  Orbitofrontal Cortex Encodes Willingness to Pay in Everyday Economic Transactions , 2007, The Journal of Neuroscience.

[39]  Colin Camerer,et al.  Dissociating the Role of the Orbitofrontal Cortex and the Striatum in the Computation of Goal Values and Prediction Errors , 2008, The Journal of Neuroscience.

[40]  Brian Knutson,et al.  Dissociable neural representations of future reward magnitude and delay during temporal discounting , 2009, NeuroImage.

[41]  C. Büchel,et al.  Overlapping and Distinct Neural Systems Code for Subjective Value during Intertemporal and Risky Decision Making , 2009, The Journal of Neuroscience.

[42]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[43]  Jin Fan,et al.  Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies , 2011, Neuroscience & Biobehavioral Reviews.