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Dissociating neural learning signals in human sign- and goal-trackers

Nature Human Behaviour volume 4, pages 201–214 (2020)Cite this article

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Abstract

Individuals differ in how they learn from experience. In Pavlovian conditioning models, where cues predict reinforcer delivery at a different goal location, some animals—called sign-trackers—come to approach the cue, whereas others, called goal-trackers, approach the goal. In sign-trackers, model-free phasic dopaminergic reward-prediction errors underlie learning, which renders stimuli ‘wanted’. Goal-trackers do not rely on dopamine for learning and are thought to use model-based learning. We demonstrate this double dissociation in 129 male humans using eye-tracking, pupillometry and functional magnetic resonance imaging informed by computational models of sign- and goal-tracking. We show that sign-trackers exhibit a neural reward prediction error signal that is not detectable in goal-trackers. Model-free value only guides gaze and pupil dilation in sign-trackers. Goal-trackers instead exhibit a stronger model-based neural state prediction error signal. This model-based construct determines gaze and pupil dilation more in goal-trackers.

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Fig. 1: Assessment of sign- and goal-trackers via eye-tracking.
Fig. 2: Pupil dilation during Pavlovian conditioning in sign-trackers and goal-trackers.
Fig. 3: PIT in sign-trackers versus goal-trackers.
Fig. 4: NAc BOLD response in sign-trackers versus goal-trackers.
Fig. 5: Neural appetitive RPE signals in sign-trackers versus goal-trackers.
Fig. 6: Neural SPE learning signals in sign-trackers versus goal-trackers.

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Data availability

Source data are available for Figs. 1–6 and Supplementary Figs. 2–12. Data sharing will be based on acceptance by the study team that: (1) a valid and timely scientific question, based on a written protocol, has been posed by those seeking to access the data; and (2) the role of the original study team will be fully acknowledged. Please contact the corresponding author via email to request access to the data. Safeguarding of ethical standards will be ensured by submission of a study amendment to the Charité and Dresden ethics committees. Data access for questions of scientific integrity may additionally be regulated via the funder.

Code availability

Experimental code is freely available on request to the corresponding author. Analysis code will be provided with data access.

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Acknowledgements

This work was supported by the German Research Foundation (FOR 1617: grants SCHA 1971/1-2, HE 2597/13-1, HE 2597/13-2, HE 2597/15-1, SCHL 1969/2-2, SCHL 1969/4-1, SM 80/7-1, SM 80/7-2, WI 709/10-1, WI 709/10-2, ZI 1119/3-1, ZI 1119/3-2, RA 1047/2-1 and RA 1047/2-2, and in part by CRC-TR 265). E.F. is a participant in the BIH Charité Clinician Scientist Program funded by the Charité—Universitätsmedizin Berlin and Berlin Institute of Health. Q.J.M.H. acknowledges support from the UCLH NIHR BRC. S.N. received funding from the University of Zurich Grants Office (FK-19-020). We thank N. B. Krömer for helpful feedback and advice on the analyses, S. Kuitunen-Paul for helpful feedback, and M. Rothkirch for help with setting up eye-tracking at the Berlin site. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Cognitive Sciences, University of Potsdam, Potsdam, Germany

    Daniel J. Schad, Michael A. Rapp, Miriam Sebold & Milena Rabovsky

  2. Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Charité—Universitätsmedizin Berlin, Berlin, Germany

    Daniel J. Schad, Maria Garbusow, Miriam Sebold, Eva Friedel, Nina Romanczuk-Seiferth, Henrik Walter, Philipp Sterzer, Florian Schlagenhauf & Andreas Heinz

  3. Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany

    Stephan Nebe, Elisabeth Obst, Christian Sommer, Hans-Ulrich Wittchen, Ulrich S. Zimmermann & Michael N. Smolka

  4. Department of Economics, Zurich Center for Neuroeconomics, University of Zurich, Zurich, Switzerland

    Stephan Nebe

  5. Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

    Lorenz Deserno & Florian Schlagenhauf

  6. Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, United Kingdom

    Lorenz Deserno

  7. Centre for Computational Psychiatry and Ageing Research, Max Planck University College London, London, UK

    Lorenz Deserno

  8. Berlin Institute of Health, Berlin, Germany

    Eva Friedel

  9. Institute of Clinical Psyhology & Psychotherapy, TU-Dresden und Department of Psychiatry, Ludwig-Maximalians-Universität, München, Germany

    Hans-Ulrich Wittchen

  10. Department of Addiction Medicine and Psychotherapy, kbo-Isar-Amper-Klinikum, Munich, Germany

    Ulrich S. Zimmermann

  11. Neuroimaging Center, Technische Universität Dresden, Dresden, Germany

    Michael N. Smolka

  12. Gatsby Computational Neuroscience Unit, University College London, London, UK

    Peter Dayan

  13. Max Planck Institute for Biological Cybernetics, Tübingen, Germany

    Peter Dayan

  14. Center for Addictive Disorders, Hospital of Psychiatry, University of Zürich, Zürich, Switzerland

    Quentin J. M. Huys

  15. Translational Neuromodeling Unit, University of Zürich and Swiss Federal Institute of Technology, Zürich, Switzerland

    Quentin J. M. Huys

  16. Complex Depression Anxiety and Trauma Service, Camden and Islington NHS Foundation Trust, London, UK

    Quentin J. M. Huys

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  1. Daniel J. Schad
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Contributions

Q.J.M.H. conceived of the study idea. M.A.R., E.F., H.-U.W., U.S.Z., H.W., P.S., M.N.S., F.S., A.H. and Q.J.M.H. designed the study. D.J.S., M.G., M.S., S.N., E.O., E.F., U.S.Z., M.N.S., F.S., A.H. and Q.J.M.H. conducted the implementation, pilots and setup. M.G., M.S., S.N. and C.S. acquired the data, with supervision from N.R.-S., H.-U.W., U.S.Z., H.W., P.S., M.N.S., F.S., A.H. and Q.J.M.H. D.J.S. analysed the data, with supervision from M.A.R., P.D. and Q.J.M.H. and input from L.D., M.R., F.S. and A.H. D.J.S., M.A.R., P.D. and Q.J.M.H. wrote the manuscript. All authors read and revised the manuscript and provided critical intellectual contributions.

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Correspondence to Daniel J. Schad.

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Schad, D.J., Rapp, M.A., Garbusow, M. et al. Dissociating neural learning signals in human sign- and goal-trackers. Nat Hum Behav 4, 201–214 (2020). https://doi.org/10.1038/s41562-019-0765-5

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