Cargando…

Neural mechanisms for learning self and other ownership

Sense of ownership is a ubiquitous and fundamental aspect of human cognition. Here we used model-based functional magnetic resonance imaging and a novel minimal ownership paradigm to probe the behavioural and neural mechanisms underpinning ownership acquisition for ourselves, friends and strangers....

Descripción completa

Detalles Bibliográficos
Autores principales: Lockwood, Patricia L., Wittmann, Marco K., Apps, Matthew A. J., Klein-Flügge, Miriam C., Crockett, Molly J., Humphreys, Glyn W., Rushworth, Matthew F. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232114/
https://www.ncbi.nlm.nih.gov/pubmed/30420714
http://dx.doi.org/10.1038/s41467-018-07231-9
_version_ 1783370343145013248
author Lockwood, Patricia L.
Wittmann, Marco K.
Apps, Matthew A. J.
Klein-Flügge, Miriam C.
Crockett, Molly J.
Humphreys, Glyn W.
Rushworth, Matthew F. S.
author_facet Lockwood, Patricia L.
Wittmann, Marco K.
Apps, Matthew A. J.
Klein-Flügge, Miriam C.
Crockett, Molly J.
Humphreys, Glyn W.
Rushworth, Matthew F. S.
author_sort Lockwood, Patricia L.
collection PubMed
description Sense of ownership is a ubiquitous and fundamental aspect of human cognition. Here we used model-based functional magnetic resonance imaging and a novel minimal ownership paradigm to probe the behavioural and neural mechanisms underpinning ownership acquisition for ourselves, friends and strangers. We find a self-ownership bias at multiple levels of behaviour from initial preferences to reaction times and computational learning rates. Ventromedial prefrontal cortex (vmPFC) and anterior cingulate sulcus (ACCs) responded more to self vs. stranger associations, but despite a pervasive neural bias to track self-ownership, no brain area tracked self-ownership exclusively. However, ACC gyrus (ACCg) specifically coded ownership prediction errors for strangers and ownership associative strength for friends and strangers but not for self. Core neural mechanisms for associative learning are biased to learn in reference to self but also engaged when learning in reference to others. In contrast, ACC gyrus exhibits specialization for learning about others.
format Online
Article
Text
id pubmed-6232114
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-62321142018-11-14 Neural mechanisms for learning self and other ownership Lockwood, Patricia L. Wittmann, Marco K. Apps, Matthew A. J. Klein-Flügge, Miriam C. Crockett, Molly J. Humphreys, Glyn W. Rushworth, Matthew F. S. Nat Commun Article Sense of ownership is a ubiquitous and fundamental aspect of human cognition. Here we used model-based functional magnetic resonance imaging and a novel minimal ownership paradigm to probe the behavioural and neural mechanisms underpinning ownership acquisition for ourselves, friends and strangers. We find a self-ownership bias at multiple levels of behaviour from initial preferences to reaction times and computational learning rates. Ventromedial prefrontal cortex (vmPFC) and anterior cingulate sulcus (ACCs) responded more to self vs. stranger associations, but despite a pervasive neural bias to track self-ownership, no brain area tracked self-ownership exclusively. However, ACC gyrus (ACCg) specifically coded ownership prediction errors for strangers and ownership associative strength for friends and strangers but not for self. Core neural mechanisms for associative learning are biased to learn in reference to self but also engaged when learning in reference to others. In contrast, ACC gyrus exhibits specialization for learning about others. Nature Publishing Group UK 2018-11-12 /pmc/articles/PMC6232114/ /pubmed/30420714 http://dx.doi.org/10.1038/s41467-018-07231-9 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Lockwood, Patricia L.
Wittmann, Marco K.
Apps, Matthew A. J.
Klein-Flügge, Miriam C.
Crockett, Molly J.
Humphreys, Glyn W.
Rushworth, Matthew F. S.
Neural mechanisms for learning self and other ownership
title Neural mechanisms for learning self and other ownership
title_full Neural mechanisms for learning self and other ownership
title_fullStr Neural mechanisms for learning self and other ownership
title_full_unstemmed Neural mechanisms for learning self and other ownership
title_short Neural mechanisms for learning self and other ownership
title_sort neural mechanisms for learning self and other ownership
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232114/
https://www.ncbi.nlm.nih.gov/pubmed/30420714
http://dx.doi.org/10.1038/s41467-018-07231-9
work_keys_str_mv AT lockwoodpatricial neuralmechanismsforlearningselfandotherownership
AT wittmannmarcok neuralmechanismsforlearningselfandotherownership
AT appsmatthewaj neuralmechanismsforlearningselfandotherownership
AT kleinfluggemiriamc neuralmechanismsforlearningselfandotherownership
AT crockettmollyj neuralmechanismsforlearningselfandotherownership
AT humphreysglynw neuralmechanismsforlearningselfandotherownership
AT rushworthmatthewfs neuralmechanismsforlearningselfandotherownership