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Rational regulation of learning dynamics by pupil-linked arousal systems

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Abstract

The ability to make inferences about the current state of a dynamic process requires ongoing assessments of the stability and reliability of data generated by that process. We found that these assessments, as defined by a normative model, were reflected in nonluminance-mediated changes in pupil diameter of human subjects performing a predictive-inference task. Brief changes in pupil diameter reflected assessed instabilities in a process that generated noisy data. Baseline pupil diameter reflected the reliability with which recent data indicate the current state of the data-generating process and individual differences in expectations about the rate of instabilities. Together these pupil metrics predicted the influence of new data on subsequent inferences. Moreover, a task- and luminance-independent manipulation of pupil diameter predictably altered the influence of new data. Thus, pupil-linked arousal systems can help to regulate the influence of incoming data on existing beliefs in a dynamic environment.

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Figure 1: Predictive-inference task sequence and pupillometry.
Figure 2: Task performance.
Figure 3: Reduced Bayesian model.
Figure 4: Relationship between pupil change and change-point probability.
Figure 5: Relationship between pupil diameter and relative uncertainty.
Figure 6: Individual differences in learning rate, hazard rate and pupil diameter.
Figure 7: Pupil metrics predict learning rate.
Figure 8: Effects of the pupil manipulation.

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  • 17 January 2017

    In the version of this article initially published, equation (7) was wrong. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank J. Cohen, S. du Lac, L. Ding, Y. Li and J. Nassar for helpful comments. This work was supported by the US National Institutes of Health (R01 EY015260, F31 MH093099 and T90 DA22763), the McKnight Endowment Fund for Neuroscience, the Burroughs-Wellcome Fund and the Sloan Foundation.

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M.R.N., J.I.G. and B.H. designed the experiment and tasks. M.R.N., K.M.R. and K.P. collected and analyzed data. M.R.N. and R.C.W. developed and applied the reduced Bayesian model. M.R.N. and J.I.G. wrote the manuscript.

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Correspondence to Joshua I Gold.

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The authors declare no competing financial interests.

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Nassar, M., Rumsey, K., Wilson, R. et al. Rational regulation of learning dynamics by pupil-linked arousal systems. Nat Neurosci 15, 1040–1046 (2012). https://doi.org/10.1038/nn.3130

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