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Smokers' brains compute, but ignore, a fictive error signal in a sequential investment task

Nature Neuroscience volume 11, pages 514–520 (2008)Cite this article

Abstract

Addicted individuals pursue substances of abuse even in the clear presence of positive outcomes that may be foregone and negative outcomes that may occur. Computational models of addiction depict the addicted state as a feature of a valuation disease, where drug-induced reward prediction error signals steer decisions toward continued drug use. Related models admit the possibility that valuation and choice are also directed by 'fictive' outcomes (outcomes that have not been experienced) that possess their own detectable error signals. We hypothesize that, in addiction, anomalies in these fictive error signals contribute to the diminished influence of potential consequences. Using a simple investment game and functional magnetic resonance imaging in chronic cigarette smokers, we measured neural and behavioral responses to error signals derived from actual experience and from fictive outcomes. In nonsmokers, both fictive and experiential error signals predicted subjects' choices and possessed distinct neural correlates. In chronic smokers, choices were not guided by error signals derived from what might have happened, despite ongoing and robust neural correlates of these fictive errors. These data provide human neuroimaging support for computational models of addiction and suggest the addition of fictive learning signals to reinforcement learning accounts of drug dependence.

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Figure 1: Schematic representation of fictive error and total earnings on the market task.
Figure 2: Smokers' and nonsmokers' responses to error signals derived from fictive outcomes.
Figure 3: Subjective craving and correlation with neural response to fictive error in unsated and sated smokers.
Figure 4: Responses to error signals derived from experienced outcomes.

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Acknowledgements

We thank B. King-Casas (supported by the National Institute of Mental Health F32 MH078485) and R. Salas for scientific discussion, the Hyperscan Development Team at Baylor College of Medicine for Network Experiment Management Object (NEMO) software implementation (http://www.hnl.bcm.tmc.edu/nemo), X. Cui and J. Li for xjView image viewing and presentation software (http://people.hnl.bcm.tmc.edu/cuixu/xjView) and C. Bracero, J. McGee and S. Moore for technical assistance. This work was supported by the Kane Family Foundation (P.R.M.), the US National Institute on Drug Abuse (R01 DA11723 to P.R.M.), the US National Institute of Neurological Disorders and Stroke (R01 NS045790 to P.R.M.), the Angel Williamson Imaging Center and the American Psychological Association (T32 MH18882 to P.H.C.).

Author information

Author notes

  1. Pearl H Chiu and Terry M Lohrenz: These authors contributed equally to this work.

Authors and Affiliations

  1. Computational Psychiatry Unit, Baylor College of Medicine, One Baylor Plaza, Houston, 77030, Texas, USA

    Pearl H Chiu, Terry M Lohrenz & P Read Montague

  2. Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, 77030, Texas, USA

    Pearl H Chiu, Terry M Lohrenz & P Read Montague

  3. Menninger Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, One Baylor Plaza, Houston, 77030, Texas, USA

    Pearl H Chiu & P Read Montague

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Correspondence to P Read Montague.

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Chiu, P., Lohrenz, T. & Montague, P. Smokers' brains compute, but ignore, a fictive error signal in a sequential investment task. Nat Neurosci 11, 514–520 (2008). https://doi.org/10.1038/nn2067

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