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Cited by 67Neural and Behavioral Psychology StudiesJury Decision Making ProcessesDecision-Making and Behavioral Economics

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

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Park, Seongmin A., Goïame, Sidney, O'Connor, David A., Dreher, Jean-Claude·2017·PLOS Biology
DOI 10.1371/journal.pbio.2001958PMC PMC5489145
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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.

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  • Optimal integration of opinions should consider judgments, confidence, and average objective accuracy of agents.

    “Optimal integration of opinions, whether from human or artificial agents, should consider the following factors: their judgments, their confidence in the correctness of their opinions, and the average objective accuracy of the agents in similar situations in the past.”

    From Enhancing human-AI collaboration: The case of colonoscopy (2024) · cites this paper as [47]

    The Discussion (page not available) says participants integrated their own judgments with a group's judgments, weighting them by credibility estimated from their own confidence and group size. The paper does not say they considered agents’ average objective accuracy in similar past situations, and its findings concern human jurors rather than artificial agents. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

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  1. [1]Danchin E, Giraldeau LA, Valone TJ, Wagner RH. Public Information: From Nosy Neighbours to Cultural Evolution. Am Assoc Adv Sci. 2004; 305: 487– 491. doi: 10.1126/science.1098254 15273386 · DOI
  2. [2]Davis JH. Group decision and social interaction: A theory of social decision schemes. Psychol Rev. 1973; 80: 97– 125. doi: 10.1037/h0033951 · DOI
  3. [3]Degroot MH, Degroot MH. Reaching a Consensus. J Am Stat Assoc. 1974; 69: 118– 121. doi: 10.2307/2285509 · DOI
  4. [4]Asch SE. Group forces in the modification and distortion of judgments. 1952 pp. 450– 501. doi: 10.1037/10025-016 · DOI
  5. [7]Insko CA, Smith RH, Alicke MD, Wade J, Taylor S. Conformity and Group Size: The Concern with Being Right and the Concern with Being Liked. Personal Soc Psychol Bull. 1985; 11: 41– 50. doi: 10.1177/0146167285111004 · DOI
  6. [8]Pouget A, Drugowitsch J, Kepecs A. Confidence and certainty: distinct probabilistic quantities for different goals. Nat Neurosci. 2016; 19: 366– 374. doi: 10.1038/nn.4240 26906503 PMC5378479 · DOI · Paper page
  7. [9]Heyes C. Who Knows? Metacognitive Social Learning Strategies. Trends Cogn Sci. 2015; xx: 1– 10. doi: 10.1016/j.tics.2015.12.007 26778808 · DOI
  8. [10]Bahrami B, Olsen K, Latham PE, Roepstorff A, Rees G, Frith CD. Optimally Interacting Minds. Science (80-). 2010; 329: 1081– 1085. doi: 10.1126/science.1185718 20798320 PMC3371582 · DOI · Paper page
  9. [11]Shea N, Boldt A, Bang D, Yeung N, Heyes C, Frith CD. Supra-personal cognitive control and metacognition. Trends Cogn Sci. 2014; 18: 186– 193. doi: 10.1016/j.tics.2014.01.006 24582436 PMC3989995 · DOI · Paper page
  10. [12]Nagel SS, Neef M. Deductive Modeling to Determine an Optimum Jury Size and Fraction Required to Convict. Washingt Univ Law Q. 1975; 1975: 933– 978.
  11. [13]Thomas EJ, Fink CF. Effects of group size. Psychol Bull. 1963; 60: 371– 384. doi: 10.1037/h0047169 13981061 · DOI
  12. [14]Saks MJ. Smaller the Jury, the Greater the Unpredictability. Judicature. 1996; 79: 263– 265.
  13. [15]Saks MJ, Marti MW. A Meta-Analysis of the effects of jury size. Law Hum Behav. 1997; 21: 451– 467. doi: 10.1023/A:1024819605652 · DOI
  14. [16]Galton F. Vox Populi. Nature. 1907; 1949: 450– 451.
  15. [17]Fleenor JW. The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economics, Societies and Nations. Pers Psychol. 2006; 59: 982– 985. doi: 10.1111/j.1744-6570.2006.00060_10.x · DOI
  16. [20]Raafat RM, Chater N, Frith C. Herding in humans. Trends Cogn Sci. 2009; 13: 420– 428. doi: 10.1016/j.tics.2009.08.002 19748818 · DOI · Paper page
  17. [21]Day RL, MacDonald T, Brown C, Laland KN, Reader SM. Interactions between shoal size and conformity in guppy social foraging. Anim Behav. 2001; 62: 917– 925. doi: 10.1006/anbe.2001.1820 · DOI
  18. [22]Couzin ID. Collective cognition in animal groups. Trends Cogn Sci. 2009; 13: 36– 43. doi: 10.1016/j.tics.2008.10.002 19058992 · DOI
  19. [23]Baddeley M. Herding, social influence and economic decision-making: socio-psychological and neuroscientific analyses. Philos Trans R Soc B Biol Sci. 2010; 365: 281– 290. doi: 10.1098/rstb.2009.0169 20026466 PMC2827453 · DOI · Paper page
  20. [25]Boorman ED, Behrens TE, Rushworth MF. Counterfactual choice and learning in a Neural Network centered on human lateral frontopolar cortex. Platt ML, editor. PLoS Biol. 2011; 9: e1001093 doi: 10.1371/journal.pbio.1001093 21738446 PMC3125157 · DOI
  21. [26]Klucharev V, Hytonen K, Rijpkema M, Smidts A, Fernandez G. Reinforcement learning signal predicts social conformity. Neuron. 2009/ 1/ 17 2009; 61: 140– 151. doi: 10.1016/j.neuron.2008.11.027 19146819 · DOI · Paper page
  22. [28]Wu H, Luo Y, Feng C. Neuroscience and Biobehavioral Reviews Neural signatures of social conformity: A coordinate-based activation likelihood estimation meta-analysis of functional brain imaging studies. Neurosci Biobehav Rev. 2016; 71: 101– 111. doi: 10.1016/j.neubiorev.2016.08.038 27592151 · DOI
  23. [29]Frith CD. The role of metacognition in human social interactions. Philos Trans R Soc B Biol Sci. 2012; 367: 2213– 2223. doi: 10.1098/rstb.2012.0123 22734064 PMC3385688 · DOI · Paper page
  24. [30]Boldt A, Yeung N. Shared Neural Markers of Decision Confidence and Error Detection. J Neurosci. 2015; 35: 3478– 3484. doi: 10.1523/JNEUROSCI.0797-14.2015 25716847 PMC4339357 · DOI · Paper page
  25. [31]Folke T, Jacobsen C, Fleming SM, De Martino B, Martino De B, Fleming SM, et al Explicit representation of confidence informs future value-based decisions. Nat Hum Behav. 2016; 1: 2 doi: 10.1038/s41562-016-0002 · DOI
  26. [32]Ernst MO, Banks MS. Humans integrate visual and haptic information in a statistically optimal fashion. Nature. 2002; 415: 429– 33. doi: 10.1038/415429a 11807554 · DOI · Paper page
  27. [33]O’Reilly JX, Schuffelgen U, Cuell SF, Behrens TEJ, Mars RB, Rushworth MFS. Dissociable effects of surprise and model update in parietal and anterior cingulate cortex. Proc Natl Acad Sci. 2013/ 8/ 30 2013; 110: E3660– E3669. doi: 10.1073/pnas.1305373110 23986499 PMC3780876 · DOI
  28. [34]Toelch U, Dolan RJ. Informational and Normative Influences in Conformity from a Neurocomputational Perspective. Trends Cogn Sci. 2015; 19: 579– 589. doi: 10.1016/j.tics.2015.07.007 26412096 · DOI
  29. [35]Meyniel F, Sigman M, Mainen ZF. Confidence as Bayesian Probability: From Neural Origins to Behavior. Neuron. 2015; 88: 78– 92. doi: 10.1016/j.neuron.2015.09.039 26447574 · DOI · Paper page
  30. [36]de Gardelle V, Mamassian P. Weighting mean and variability during confidence judgments. PLoS One. 2015; 10: e0120870 doi: 10.1371/journal.pone.0120870 25793275 PMC4368758 · DOI
  31. [37]Doya K, Ishii S, Pouget A, Rao RPN. Bayesian Brain: Probabilistic Approaches to Neural Coding [Internet]. Book. 2007 doi: 10.7551/mitpress/9780262042383.001.0001 · DOI
  32. [38]Lebreton M, Abitbol R, Daunizeau J, Pessiglione M. Automatic integration of confidence in the brain valuation signal. Nat Neurosci. 2015; 18: 1159– 1167. doi: 10.1038/nn.4064 26192748 · DOI · Paper page
  33. [39]Fleming SM, Thomas CL, Dolan RJ. Overcoming status quo bias in the human brain. Proc Natl Acad Sci U S A. 2010; 107: 6005– 9. doi: 10.1073/pnas.0910380107 20231462 PMC2851882 · DOI
  34. [40]Shannon C. A mathematical theory of communication. Bell Syst Tech Journalputing …. 1948; 27: 379– 423. doi: 10.1145/584091.584093 · DOI
  35. [41]Shenhav A, Straccia MA, Cohen JD, Botvinick MM. Anterior cingulate engagement in a foraging context reflects choice difficulty, not foraging value. Nat Neurosci. 2014; 17: 1249– 54. doi: 10.1038/nn.3771 25064851 PMC4156480 · DOI
  36. [42]Shenhav A, Botvinick MM, Cohen JD. The expected value of control: An integrative theory of anterior cingulate cortex function. Neuron. 2013; 79: 217– 240. doi: 10.1016/j.neuron.2013.07.007 23889930 PMC3767969 · DOI · Paper page
  37. [43]Shenhav A, Cohen JD, Botvinick MM. Dorsal anterior cingulate cortex and the value of control. Nat Neurosci. 2016; 19: 1286– 1291. doi: 10.1038/nn.4384 27669989 · DOI
  38. [44]Kolling N, Wittmann MK, Behrens TEJ, Boorman ED, Mars RB, Rushworth MFS. Value, search, persistence and model updating in anterior cingulate cortex. Nat Neurosci. 2016; 19: 1280– 1285. doi: 10.1038/nn.4382 27669988 PMC7116891 · DOI
  39. [45]Kolling N, Behrens T, Wittmann M, Rushworth M. Multiple signals in anterior cingulate cortex. Curr Opin Neurobiol. 2016; 37: 36– 43. doi: 10.1016/j.conb.2015.12.007 26774693 PMC4863523 · DOI · Paper page
  40. [48]Izuma K. The neural basis of social influence and attitude change. Curr Opin Neurobiol. 2013/ 4/ 24 2013; 23: 456– 462. doi: 10.1016/j.conb.2013.03.009 23608704 · DOI
  41. [49]Chung D, Christopoulos GI, King-Casas B, Ball SB, Chiu PH. Social signals of safety and risk confer utility and have asymmetric effects on observers’ choices. Nat Neurosci. 2015; 18: 912– 916. doi: 10.1038/nn.4022 25984890 PMC4447111 · DOI
  42. [50]Hill MR, Boorman ED, Fried I. Observational learning computations in neurons of the human anterior cingulate cortex. Nat Commun. 2016; 7: 1– 9. doi: 10.1038/ncomms12722 27598687 PMC5025858 · DOI
  43. [53]Apps MAJ, Sallet J, Kolling N, Al. E, Procyk E, Al. E, et al Social Learning in the Medial Prefrontal Cortex. Trends Cogn Sci. 2017; 21: 36– 43. doi: 10.1016/j.tics.2017.01.008 28173997 · DOI
  44. [55]Donoso M, Collins AGE, Koechlin E. Human cognition. Foundations of human reasoning in the prefrontal cortex. Science (80-). 2014; 344: 1481– 6. 24876345
  45. [56]Koechlin E. Prefrontal executive function and adaptive behavior in complex environments. Current Opinion in Neurobiology. 2016 pp. 1– 6. doi: 10.1016/j.conb.2015.11.004 26687618 · DOI
  46. [57]Charron S, Koechlin E. Divided representation of concurrent goals in the human frontal lobes. Science (80-). 2010; 328: 360– 363. doi: 10.1126/science.1183614 20395509 · DOI
  47. [58]Boorman ED, Behrens TEJ, Woolrich MW, Rushworth MFS. How Green Is the Grass on the Other Side? Frontopolar Cortex and the Evidence in Favor of Alternative Courses of Action. Neuron. 2009; 62: 733– 743. doi: 10.1016/j.neuron.2009.05.014 19524531 · DOI · Paper page
  48. [59]Boorman ED, O’Doherty JP, Adolphs R, Rangel A. The behavioral and neural mechanisms underlying the tracking of expertise. Neuron. 2013; 80: 1558– 1571. doi: 10.1016/j.neuron.2013.10.024 24360551 PMC3878380 · DOI
  49. [60]Dunbar RIM, Shultz S. Evolution in the social brain. Science (80-). 2007; 317: 1344– 7. doi: 10.1126/science.1145463 17823343 · DOI
  50. [61]Semendeferi K, Armstrong E, Schleicher A, Zilles K, Van Hoesen GW. Prefrontal cortex in humans and apes: A comparative study of area 10. Am J Phys Anthropol. 2001; 114: 224– 241. doi: 10.1002/1096-8644(200103)114:3<224::AID-AJPA1022>3.0.CO;2-I 11241188 · DOI
  51. [62]Sallet J, Mars RB, Noonan MP, Andersson JL, O’Reilly JX, Jbabdi S, et al Social network size affects neural circuits in macaques. Science (80-). 2011; 334: 697– 700. doi: 10.1126/science.1210027 22053054 · DOI · Paper page
  52. [63]Campbell-Meiklejohn D, Simonsen A, Frith CD, Daw ND. Independent Neural Computation of Value from Other People’s Confidence. J Neurosci. 2017; 37: 673– 684. doi: 10.1523/JNEUROSCI.4490-15.2016 28100748 PMC6596755 · DOI
  53. [64]Lak A, Costa GM, Romberg E, Koulakov AA, Mainen ZF, Kepecs A. Orbitofrontal cortex is required for optimal waiting based on decision confidence. Neuron. 2014; 84: 190– 201. doi: 10.1016/j.neuron.2014.08.039 25242219 PMC4364549 · DOI · Paper page
  54. [65]Koechlin E, Basso G, Pietrini P, Panzer S, Grafman JH. The role of the anterior prefrontal cortex in human cognition. Nature. 1999; 399: 148– 151. doi: 10.1038/20178 10335843 · DOI
  55. [67]Yamada M, Camerer CF, Fujie S, Kato M, Matsuda T, Takano H, et al Neural circuits in the brain that are activated when mitigating criminal sentences. Nat Commun. 2012/ 3/ 29 2012; 3: 759 doi: 10.1038/ncomms1757 22453832 PMC3316876 · DOI
  56. [68]Kullback S, Leibler RA. On Information and Sufficiency. Ann Math Stat. 1951; 22: 79– 86. doi: 10.1214/aoms/1177729694 · DOI · Paper page
  57. [69]Kumaran D, Banino A, Blundell C, Hassabis D, Dayan P. Computations Underlying Social Hierarchy Learning: Distinct Neural Mechanisms for Updating and Representing Self-Relevant Information. Neuron. 2016; 92: 1135– 1147. doi: 10.1016/j.neuron.2016.10.052 27930904 PMC5158095 · DOI
  58. [70]Niv Y, Daniel R, Geana A, Gershman SJ, Leong YC, Radulescu A, et al Reinforcement Learning in Multidimensional Environments Relies on Attention Mechanisms. J Neurosci. 2015; 35: 8145– 8157. doi: 10.1523/JNEUROSCI.2978-14.2015 26019331 PMC4444538 · DOI · Paper page
  59. [71]Edelson MG, Dudai Y, Dolan RJ, Sharot T. Brain Substrates of Recovery from Misleading Influence. J Neurosci. 2014; 34: 7744– 7753. doi: 10.1523/JNEUROSCI.4720-13.2014 24899698 PMC4044241 · DOI
  60. [72]Eklund A, Nichols TE, Knutsson H. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci U S A. 2016; 113: 7900– 5. doi: 10.1073/pnas.1602413113 27357684 PMC4948312 · DOI · Paper page
  61. [73]Yarkoni T. Big Correlations in Little Studies: Inflated fMRI Correlations Reflect Low Statistical Power—Commentary on Vul et al. (2009). Perspect Psychol Sci. 2009; 4: 294– 298. doi: 10.1111/j.1745-6924.2009.01127.x 26158966 · DOI · Paper page
  62. [75]Tavares RM, Mendelsohn A, Grossman Y, Williams CH, Shapiro M, Trope Y, et al A Map for Social Navigation in the Human Brain. Neuron. 2015; 87: 231– 243. doi: 10.1016/j.neuron.2015.06.011 26139376 PMC4662863 · DOI · Paper page

Cited by

Sorted by citations

Authors
Park, S. A., Goïame, S., O'Connor, D. A., & Dreher, J.-C.
Affiliations
  • Lyon 1 Université (FR)
  • Centre National de la Recherche Scientifique (FR)
Corresponding author
  • Park, Seongmin A.
  • Dreher, Jean-Claude
ORCID
Venue
PLOS Biology
Publisher
Public Library of Science (PLoS)
Published
2017-06-28
Volume
15
Issue
6
Pages
e2001958
ISSN
  • 1544-9173 (ISSN-L)
  • 1545-7885
DOI
10.1371/journal.pbio.2001958
PMC
PMC5489145
OpenAlex
W2726642124
Cited by
67
References
14
Citations by year
2026: 3 · 2025: 9 · 2024: 11 · 2023: 6 · 2022: 11 · 2021: 12 · 2020: 6 · 2019: 3 · 2018: 6
FWCI
2.29
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS Biology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Science Foundation (ANR-11-IDEX-0007, 16-NEUC-0003-01)
  • European Commission
  • Agence Nationale de la Recherche (LABEX ANR-11-LABEX-0042, ANR-11-IDEX-0007, ANR-16-NEUC-0003, ANR-11-LABEX-0042, 11-LABEX-0042, ANR-11-IDEX, ANR-16, IDEX-0007, ANR-14-CE13-0006, 11 IDEX - 0007)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Social Sciences › Law › Jury Decision Making Processes
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Keywords
belief updating, group decision making, group size, credibility assessment, dorsal anterior cingulate cortex, frontopolar cortex, jury decision-making, neurocomputational model
MeSH terms
Adult, Bayes Theorem, Brain, Brain Mapping, Cerebral Cortex, Cognition, Decision Making, Female, Gyrus Cinguli, Humans, Judgment, Magnetic Resonance Imaging, Male, Nerve Net, Regression Analysis, Prefrontal Cortex, Young Adult

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