The neural computation of human prosocial choices in complex motivational states

Please always quote using this URN: urn:nbn:de:bvb:20-opus-265852
  • Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor ofMotives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modeling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants' choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors .show moreshow less

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Metadaten
Author: Anne Saulin, Ulrike Horn, Martin Lotze, Jochen Kaiser, Grit Hein
URN:urn:nbn:de:bvb:20-opus-265852
Document Type:Journal article
Faculties:Medizinische Fakultät / Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie
Language:English
Parent Title (English):NeuroImage
Year of Completion:2022
Volume:247
Article Number:118827
Source:NeuroImage (2022) 247:118827. https://doi.org/10.1016/j.neuroimage.2021.118827
DOI:https://doi.org/10.1016/j.neuroimage.2021.118827
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:fMRI; hierarchical drift-diffusion modeling; motivation; social decision-making; social neuroscience
Release Date:2022/05/03
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2021
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International