Neural correlates of mentalizing-related computations during strategic interactions in humans

Competing successfully against an intelligent adversary requires the ability to mentalize an opponent's state of mind to anticipate his/her future behavior. Although much is known about what brain regions are activated during mentalizing, the question of how this function is implemented has received little attention to date. Here we formulated a computational model describing the capacity to mentalize in games. We scanned human subjects with functional MRI while they participated in a simple two-player strategy game and correlated our model against the functional MRI data. Different model components captured activity in distinct parts of the mentalizing network. While medial prefrontal cortex tracked an individual's expectations given the degree of model-predicted influence, posterior superior temporal sulcus was found to correspond to an influence update signal, capturing the difference between expected and actual influence exerted. These results suggest dissociable contributions of different parts of the mentalizing network to the computations underlying higher-order strategizing in humans.

[1]  B. Bertenthal,et al.  Does Perception of Biological Motion Rely on Specific Brain Regions? , 2001, NeuroImage.

[2]  D. Barraclough,et al.  Learning and decision making in monkeys during a rock-paper-scissors game. , 2005, Brain research. Cognitive brain research.

[3]  Miguel A. Costa-Gomes,et al.  Cognition and Behavior in Normal-Form Games: An Experimental Study , 1998 .

[4]  P. Glimcher,et al.  Activity in Posterior Parietal Cortex Is Correlated with the Relative Subjective Desirability of Action , 2004, Neuron.

[5]  C. Frith,et al.  Development and neurophysiology of mentalizing. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[6]  Colin Camerer,et al.  When Does "Economic Man" Dominate Social Behavior? , 2006, Science.

[7]  T. Allison,et al.  Temporal Cortex Activation in Humans Viewing Eye and Mouth Movements , 1998, The Journal of Neuroscience.

[8]  Jonathan D. Cohen,et al.  An fMRI Investigation of Emotional Engagement in Moral Judgment , 2001, Science.

[9]  Samuel M. McClure,et al.  Temporal Prediction Errors in a Passive Learning Task Activate Human Striatum , 2003, Neuron.

[10]  Andrew G. Barto,et al.  Reinforcement learning , 1998 .

[11]  R. Dolan,et al.  An fMRI study of intentional and unintentional (embarrassing) violations of social norms. , 2002, Brain : a journal of neurology.

[12]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[13]  Mitsuo Kawato,et al.  Multiple Model-Based Reinforcement Learning , 2002, Neural Computation.

[14]  Dale O. Stahl,et al.  Rule Learning in Symmetric Normal-Form Games: Theory and Evidence , 2000, Games Econ. Behav..

[15]  D. Barraclough,et al.  Prefrontal cortex and decision making in a mixed-strategy game , 2004, Nature Neuroscience.

[16]  C. Frith,et al.  Functional imaging of ‘theory of mind’ , 2003, Trends in Cognitive Sciences.

[17]  J. O'Doherty,et al.  Is Avoiding an Aversive Outcome Rewarding? Neural Substrates of Avoidance Learning in the Human Brain , 2006, PLoS biology.

[18]  J. O'Doherty,et al.  Reward representations and reward-related learning in the human brain: insights from neuroimaging , 2004, Current Opinion in Neurobiology.

[19]  Peter Dayan,et al.  Temporal difference models describe higher-order learning in humans , 2004, Nature.

[20]  Teck-Hua Ho,et al.  Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games , 2002, J. Econ. Theory.

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

[22]  Jonathan D. Cohen,et al.  Imaging valuation models in human choice. , 2006, Annual review of neuroscience.

[23]  D. Fudenberg,et al.  The Theory of Learning in Games , 1998 .

[24]  Christopher D. Frith,et al.  Imaging the Intentional Stance in a Competitive Game , 2002, NeuroImage.

[25]  Kevin McCabe,et al.  Neural signature of fictive learning signals in a sequential investment task , 2007, Proceedings of the National Academy of Sciences.

[26]  Daniel Houser,et al.  A functional imaging study of cooperation in two-person reciprocal exchange , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[27]  W. F. Prokasy,et al.  Classical conditioning II: Current research and theory. , 1972 .

[28]  Karl J. Friston,et al.  Spatial registration and normalization of images , 1995 .

[29]  C. Frith,et al.  Movement and Mind: A Functional Imaging Study of Perception and Interpretation of Complex Intentional Movement Patterns , 2000, NeuroImage.

[30]  Nathaniel T. Wilcox,et al.  Theories of Learning in Games and Heterogeneity Bias , 2006 .

[31]  James K Rilling,et al.  The neural correlates of theory of mind within interpersonal interactions , 2004, NeuroImage.

[32]  Karl J. Friston,et al.  Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.

[33]  Uta Frith,et al.  Theory of mind , 2001, Current Biology.

[34]  C. Frith,et al.  Meeting of minds: the medial frontal cortex and social cognition , 2006, Nature Reviews Neuroscience.

[35]  Colin Camerer,et al.  Experience‐weighted Attraction Learning in Normal Form Games , 1999 .

[36]  P. Skudlarski,et al.  The role of the fusiform face area in social cognition: implications for the pathobiology of autism. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.