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      Integration of individual and social information for decision-making in groups of different sizes

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          Abstract

          When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal. By testing different theoretical models, we showed that a social Bayesian inference model captured changes in judgments better than 2 other models. Our results showed that participants updated their beliefs by appropriately weighting individual and social sources of information according to their respective credibility. When investigating 2 fundamental computations of Bayesian inference, belief updates and credibility estimates of social information, we found that the dorsal anterior cingulate cortex (dACC) computed the level of belief updates, while the bilateral frontopolar cortex (FPC) was more engaged in individuals who assigned a greater credibility to the judgments of a larger group. Moreover, increased functional connectivity between these 2 brain regions reflected a greater influence of group size on the relative credibility of social information. These results provide a mechanistic understanding of the computational roles of the FPC-dACC network in steering judgment adaptation to a group’s opinion. Taken together, these findings provide a computational account of how the human brain integrates individual and social information for decision-making in groups.

          Author summary

          In collective decisions, both the size of groups and the confidence that each member has in their own judgment determine how much a given individual will adapt to the judgment of the group. Here, we show that judgment adaptation during collective decisions—a fundamental brain mechanism needed for fluid functioning of social organizations—can be accounted for by Bayesian inference computations. At the time of judgment adaptation, individuals trade off the credibility inferred from their own confidence levels against the credibility of social information. The dorsal anterior cingulate cortex (dACC) represented belief updates, while the lateral frontopolar cortex (FPC) monitored the changes in credibility assigned to social information. These results provide a neurocomputational understanding of how individuals benefit both from the wisdom of larger groups and from their own confidence.

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          Most cited references53

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          Experimental study of inequality and unpredictability in an artificial cultural market.

          Hit songs, books, and movies are many times more successful than average, suggesting that "the best" alternatives are qualitatively different from "the rest"; yet experts routinely fail to predict which products will succeed. We investigated this paradox experimentally, by creating an artificial "music market" in which 14,341 participants downloaded previously unknown songs either with or without knowledge of previous participants' choices. Increasing the strength of social influence increased both inequality and unpredictability of success. Success was also only partly determined by quality: The best songs rarely did poorly, and the worst rarely did well, but any other result was possible.
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            Puzzlingly High Correlations in fMRI Studies of Emotion, Personality, and Social Cognition.

            Functional magnetic resonance imaging (fMRI) studiesofemotion, personality, and social cognition have drawn much attention in recent years, with high-profile studies frequently reporting extremely high (e.g., >.8) correlations between brain activation and personality measures. We show that these correlations are higher than should be expected given the (evidently limited) reliability of both fMRI and personality measures. The high correlations are all the more puzzling because method sections rarely contain much detail about how the correlations were obtained. We surveyed authors of 55 articles that reported findings of this kind to determine a few details on how these correlations were computed. More than half acknowledged using a strategy that computes separate correlations for individual voxels and reports means of only those voxels exceeding chosen thresholds. We show how this nonindependent analysis inflates correlations while yielding reassuring-looking scattergrams. This analysis technique was used to obtain the vast majority of the implausibly high correlations in our survey sample. In addition, we argue that, in some cases, other analysis problems likely created entirely spurious correlations. We outline how the data from these studies could be reanalyzed with unbiased methods to provide accurate estimates of the correlations in question and urge authors to perform such reanalyses. The underlying problems described here appear to be common in fMRI research of many kinds-not just in studies of emotion, personality, and social cognition.
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              Reaching a Consensus

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysis
                Role: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                28 June 2017
                June 2017
                28 June 2017
                : 15
                : 6
                : e2001958
                Affiliations
                [1 ]Neuroeconomics, Reward and Decision-making Team, Institut des Sciences Cognitives Marc Jeannerod, Centre National de la Recherche Scientifique, Bron, France
                [2 ]Université Claude-Bernard Lyon 1, Villeurbanne, France
                University of Oxford, United Kingdom of Great Britain and Northern Ireland
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-8361-2277
                Article
                pbio.2001958
                10.1371/journal.pbio.2001958
                5489145
                28658252
                6653c61c-db91-44f8-be2d-70fece146985
                © 2017 Park et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 January 2017
                : 25 May 2017
                Page count
                Figures: 6, Tables: 0, Pages: 28
                Funding
                French National Research Agency (ANR) (grant number ANR-14-CE13-0006-01 ‘BRAINCHOICE’). Received by JCD. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. JCD was funded by the EURIAS Fellowship Programme, the European Commission (Marie-Sklodowska-Curie Actions—COFUND Programme—FP7, grant number 502-686353647) and the Hanse-Wissenschaftskolleg (Institute for Advanced Study). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. French National Research Agency (ANR) (grant number ANR-11-IDEX-0007). Received by JCD. This work was performed within the framework of the LABEX ANR-11-LABEX-0042 of Université de Lyon, within the program "Investissements d'Avenir". The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Collaborative Research in Computational Neuroscience (CRCNS) (French National Research Agency [ANR] and National Science Foundation [NSF]) (grant number for the ANR-NSF CRCNS ‘SOCIAL_POMDP’ is ANR-16-NEUC-0003-01). Received by JCD. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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