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Neuro-computational mechanisms of action-outcome learning under moral conflict

Alessandra D. Nostro, Kalliopi Ioumpa, Riccardo Paracampo, Selene Gallo, Laura Fornari, Lorenzo De Angelis, Alessandro Gentile, Michael Spezio, Christian Keysers, View ORCID ProfileValeria Gazzola
doi: https://doi.org/10.1101/2020.06.10.143891
Alessandra D. Nostro
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
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Kalliopi Ioumpa
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
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Riccardo Paracampo
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
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Selene Gallo
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
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Laura Fornari
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
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Lorenzo De Angelis
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
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Alessandro Gentile
5GoDataDriven, Amsterdam, The Netherlands
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Michael Spezio
3Psychology, Neuroscience, & Data Science, Scripps College, Claremont, CA USA
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Christian Keysers
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
2Dept of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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Valeria Gazzola
1Netherlands Institute for Neuroscience, KNAW, Amsterdam, The Netherlands
2Dept of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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  • ORCID record for Valeria Gazzola
  • For correspondence: v.gazzola@nin.knaw.nl
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Abstract

Learning to predict how our actions result in conflicting outcomes for self and others is essential for social functioning, but remains poorly understood. We test whether Reinforcement Learning Theory captures how participants learn to choose between two symbols that define a moral conflict between financial gain to self and pain for others. Computational modelling and fMRI imaging show that participants have dissociable representations for self-gain and pain to others. Signals in dorsal rostral cingulate and insulae track more closely with outcomes than prediction errors, while the opposite is true for the ventral rostral cingulate. Cognitive computational models estimated a valuational preference parameter that captured individual variability of choice in this moral conflict task. Participants’ valuational preferences predicted how much they chose to spend to reduce another person’s pain in an independent task. Learning separate representations for self and others allows participants to rapidly adapt to changes in contingencies during conflicts.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted June 12, 2020.
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Neuro-computational mechanisms of action-outcome learning under moral conflict
Alessandra D. Nostro, Kalliopi Ioumpa, Riccardo Paracampo, Selene Gallo, Laura Fornari, Lorenzo De Angelis, Alessandro Gentile, Michael Spezio, Christian Keysers, Valeria Gazzola
bioRxiv 2020.06.10.143891; doi: https://doi.org/10.1101/2020.06.10.143891
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Neuro-computational mechanisms of action-outcome learning under moral conflict
Alessandra D. Nostro, Kalliopi Ioumpa, Riccardo Paracampo, Selene Gallo, Laura Fornari, Lorenzo De Angelis, Alessandro Gentile, Michael Spezio, Christian Keysers, Valeria Gazzola
bioRxiv 2020.06.10.143891; doi: https://doi.org/10.1101/2020.06.10.143891

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