Associative learning of social value

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Our decisions are guided by information learnt from our environment. This information may come via personal experiences of reward, but also from the behaviour of social partners1,2. Social learning is widely held to be distinct from other forms of learning in its mechanism and neural implementation; it is often assumed to compete with simpler mechanisms, such as reward-based associative learning, to drive behaviour3. Recently, neural signals have been observed during social exchange reminiscent of signals seen in studies of associative learning4. Here we demonstrate that social information may be acquired using the same associative processes assumed to underlie reward-based learning. We find that key computational variables for learning in the social and reward domains are processed in a similar fashion, but in parallel neural processing streams. Two neighbouring divisions of the anterior cingulate cortex were central to learning about social and reward-based information, and for determining the extent to which each source of information guides behaviour. When making a decision, however, the information learnt using these parallel streams was combined within ventromedial prefrontal cortex. These findings suggest that human social valuation can be realized by means of the same associative processes previously established for learning other, simpler, features of the environment.

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Figure 1: Experimental task and behavioural findings.
Figure 2: Predictions and prediction errors in social and non-social domains.
Figure 3: Agency-specific learning rates dissociate in the ACC.
Figure 4: Combination of expected value of chosen option in VMPFC.


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Acknowledgments We would like to acknowledge funding from the UK MRC (T.E.J.B., M.F.S.R.), the Wellcome Trust (L.T.H.) and the UK EPSRC (M.W.W.). We thank S. Knight for helping with data acquisition, and K. Watkins for help with figure preparation.

Author contributions All four authors contributed to generating the hypothesis and designing the experiment. Where specific roles can be assigned, L.T.H. collected the data, T.E.J.B. and L.T.H. analysed the data, T.E.J.B. and M.W.W. built the model, and M.F.S.R. supervised the project.

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Correspondence to Timothy E. J. Behrens.

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Behrens, T., Hunt, L., Woolrich, M. et al. Associative learning of social value. Nature 456, 245–249 (2008) doi:10.1038/nature07538

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