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Theory of mind and decision science: Towards a typology of tasks and computational models

Rusch, Tessa and Steixner-Kumar, Saurabh and Doshi, Prashant and Spezio, Michael and Gläscher, Jan (2020) Theory of mind and decision science: Towards a typology of tasks and computational models. Neuropsychologia, 146 . Art. No. 107488. ISSN 0028-3932.

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The ability to form a Theory of Mind (ToM), i.e., to theorize about others’ mental states to explain and predict behavior in relation to attributed intentional states, constitutes a hallmark of human cognition. These abilities are multi-faceted and include a variety of different cognitive sub-functions. Here, we focus on decision processes in social contexts and review a number of experimental and computational modeling approaches in this field. We provide an overview of experimental accounts and formal computational models with respect to two dimensions: interactivity and uncertainty. Thereby, we aim at capturing the nuances of ToM functions in the context of social decision processes. We suggest there to be an increase in ToM engagement and multiplexing as social cognitive decision-making tasks become more interactive and uncertain. We propose that representing others as intentional and goal directed agents who perform consequential actions is elicited only at the edges of these two dimensions. Further, we argue that computational models of valuation and beliefs follow these dimensions to best allow researchers to effectively model sophisticated ToM-processes. Finally, we relate this typology to neuroimaging findings in neurotypical (NT) humans, studies of persons with autism spectrum (AS), and studies of nonhuman primates.

Item Type:Article
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URLURL TypeDescription
Gläscher, Jan0000-0002-1020-7115
Additional Information:© 2020 Published by Elsevier Ltd. Received 30 September 2019, Revised 27 April 2020, Accepted 4 May 2020, Available online 12 May 2020. This review has benefited greatly from the comments of two reviewers. Further, we are grateful for helpful conversations with Martin Hebart, Christoph Korn, Yuqing Lei, Shannon Klotz, Corinne Donnay, Gregory Peterson, Robert Roberts, Jonathan Daume, and members of the L’Arche and Homeboy Industries communities. PD, SSK, MS and JG were funded by a Collaborative Research in Computational Neuroscience grant awarded jointly by the German Ministry of Education and Research (BMBF, 01GQ1603) and the United States National Science Foundation (NSF, 1608278). JG and TR were supported by the Collaborative Research Center TRR 169 “Crossmodal Learning” funded by the German Research Foundation (DFG) and the National Science Foundation of China (NSFC). MS gratefully acknowledges funding from the John Templeton Foundation (Grant 21338) and the Templeton Religion Trust and the Self, Motivation, and Virtue Project. All authors declare no conflict of interest. CRediT authorship contribution statement: Tessa Rusch: Conceptualization, Writing - original draft, Writing - review & editing, Visualization. Saurabh Steixner-Kumar: Conceptualization, Writing - review & editing. Prashant Doshi: Conceptualization, Writing - review & editing. Michael Spezio: Conceptualization, Writing - review & editing, Funding acquisition. Jan Gläscher: Conceptualization, Writing - original draft, Writing - review & editing, Funding acquisition.
Funding AgencyGrant Number
Bundesministerium für Bildung und Forschung (BMBF)01GQ1603
Deutsche Forschungsgemeinschaft (DFG)TRR 169
National Natural Science Foundation of ChinaUNSPECIFIED
John Templeton Foundation21338
Templeton Religion TrustUNSPECIFIED
Subject Keywords:Theory of mind; Computational modeling; Decision making; Interactivity; Uncertainty
Record Number:CaltechAUTHORS:20200512-103140730
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Official Citation:Tessa Rusch, Saurabh Steixner-Kumar, Prashant Doshi, Michael Spezio, Jan Gläscher, Theory of mind and decision science: Towards a typology of tasks and computational models, Neuropsychologia, Volume 146, 2020, 107488, ISSN 0028-3932,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103135
Deposited By: Tony Diaz
Deposited On:12 May 2020 18:35
Last Modified:24 Jun 2020 15:07

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