From intuitive altruism to rational deliberations - a neuroscience view on the learning process in game theory experiments

What is intuitive: pro-social or anti-social behaviour? To answer this fundamental question, recent studies analyse decision times in game theory experiments under the assumption that intuitive decisions are fast and that deliberation is slow. Lacking any knowledge of the underlying dynamics, such simplistic approach might however lead to erroneous interpretations. Here we model the cognitive basis of strategic cooperative decision making using the Drift Diffusion Model to discern between deliberation and intuition and describe the evolution of the decision making in iterated Prisoner's Dilemma experiments. We find that rational deliberation quickly becomes dominant over an initial intuitive bias towards cooperation, which is fostered by positive interactions as much as frustrated by a negative one. However, this initial pro-social tendency is resilient, as after a pause it resets to the same initial value. These results illustrate the new insight that can be achieved thanks to a quantitative modelling of human behavior.

[1]  Griet Emonds,et al.  Trust as commodity: social value orientation affects the neural substrates of learning to cooperate , 2017, Social cognitive and affective neuroscience.

[2]  Lorne Campbell,et al.  Registered Replication Report , 2016, Perspectives on psychological science : a journal of the Association for Psychological Science.

[3]  Arohi Abhinav Jayaswal Comparison between auditory and visual simple reaction times and its relationship with gender in 1st year MBBS students of Jawaharlal Nehru Medical College, Bhagalpur, Bihar , 2016 .

[4]  David G. Rand Cooperation, Fast and Slow , 2016, Psychological science.

[5]  R. Ratcliff,et al.  Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions. , 2016, Annual review of psychology.

[6]  Todd A. Hare,et al.  A Common Mechanism Underlying Food Choice and Social Decisions , 2015, PLoS Comput. Biol..

[7]  Cendri A. C. Hutcherson,et al.  A Neurocomputational Model of Altruistic Choice and Its Implications , 2015, Neuron.

[8]  Ernst Fehr,et al.  Rethinking fast and slow based on a critique of reaction-time reverse inference , 2015, Nature Communications.

[9]  Angel Sánchez,et al.  A comparative analysis of spatial Prisoner's Dilemma experiments: Conditional cooperation and payoff irrelevance , 2014, Scientific Reports.

[10]  David G. Rand,et al.  Social heuristics shape intuitive cooperation , 2014, Nature Communications.

[11]  Daniel Västfjäll,et al.  Intuition and cooperation reconsidered , 2013, Nature.

[12]  Thomas V. Wiecki,et al.  HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python , 2013, Front. Neuroinform..

[13]  Bingni W. Brunton,et al.  Rats and Humans Can Optimally Accumulate Evidence for Decision-Making , 2013, Science.

[14]  David G. Rand,et al.  Spontaneous giving and calculated greed , 2012, Nature.

[15]  Antonio Cabrales,et al.  Three is a crowd in iterated prisoner's dilemmas: experimental evidence on reciprocal behavior , 2012, Scientific Reports.

[16]  W. Güth,et al.  Being of two minds: Ultimatum offers under cognitive constraints , 2011 .

[17]  Guido Ortona,et al.  Is cooperation instinctive? Evidence from the response times in a public goods game , 2011 .

[18]  Paul M. Parizel,et al.  Comparing the Neural Basis of Decision Making in Social Dilemmas of People With Different Social Value Orientations, a fMRI Study , 2011 .

[19]  Lourdes Araujo,et al.  Social Experiments in the Mesoscale: Humans Playing a Spatial Prisoner's Dilemma , 2010, PloS one.

[20]  Christof Koch,et al.  The drift diffusion model can account for value-based choice response times under high and low time pressure , 2010 .

[21]  J. Shelton,et al.  Comparison between Auditory and Visual Simple Reaction Times , 2010 .

[22]  M. Shadlen,et al.  Decision-making with multiple alternatives , 2008, Nature Neuroscience.

[23]  Erik Wengström,et al.  Fast or Fair? A Study of Response Times , 2008 .

[24]  Roger Ratcliff,et al.  The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks , 2008, Neural Computation.

[25]  Pablo Brañas-Garza,et al.  Response Time Under Monetary Incentives: The Ultimatum Game , 2007 .

[26]  Jonathan D. Cohen,et al.  The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. , 2006, Psychological review.

[27]  Xiao-Jing Wang,et al.  Cortico–basal ganglia circuit mechanism for a decision threshold in reaction time tasks , 2006, Nature Neuroscience.

[28]  P. Glimcher,et al.  Neuroeconomics: The Consilience of Brain and Decision , 2004, Science.

[29]  Ben Greiner,et al.  The Online Recruitment System ORSEE 2.0 - A Guide for the Organization of Experiments in Economics , 2004 .

[30]  Philip L. Smith,et al.  Psychology and neurobiology of simple decisions , 2004, Trends in Neurosciences.

[31]  P. Glimcher The neurobiology of visual-saccadic decision making. , 2003, Annual review of neuroscience.

[32]  U. Fischbacher,et al.  The nature of human altruism , 2003, Nature.

[33]  J. Townsend,et al.  Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment. , 1993, Psychological review.

[34]  N. Srinivasan,et al.  Registered Replication Report : Rand, Greene & Nowak (2012) , 2017 .

[35]  A. Evans,et al.  Reaction times and reflection in social dilemmas: Extreme responses are fast, but not intuitive , 2014 .

[36]  B. Harshbarger An Introduction to Probability Theory and its Applications, Volume I , 1958 .