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Chapter 12 - Trust and Brain Dynamics

Insights from Task-Based and Task-Free Neuroimaging Investigations

from Part III - Neurocharacteristic Level of Trust

Published online by Cambridge University Press:  09 December 2021

By
Yan Wu  and
Frank Krueger
Edited by
Frank Krueger
Frank Krueger
Affiliation:
George Mason University, Virginia
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Summary

Interpersonal trust is a vital element in the social functioning of our relationships with persons, groups, and organizations. In the past two decades, an increase in task-based and task-free (resting-state) functional magnetic resonance imaging (fMRI) studies have been observed that explored the neuropsychological signatures of trust. In this book chapter, we compared the commonalities and differences between task-based fMRI (tb-fMRI) and task-free fMRI (tf-fMRI) approaches for studying trust and explored how these two approaches can make unique contributions to our understanding of the psychoneurobiological underpinnings of trust. Overlapping brain regions for both approaches have been identified in large-scale domain-general networks – reward (e.g., ventral striatum), salience (e.g., anterior insula), executive-control (i.e., lateral prefrontal cortex), and default-mode (i.e., temporoparietal junction) networks – supporting the underlying motivational, affective, and cognitive aspects of trust. While task-based research investigates dominantly those brain networks in building trust over time at the group level, task-free trust research has identified those networks in predicting trust preferences at the individual level. Future research would benefit from a combination of these two approaches for a broader understanding of the driving psychoneurobiological mechanisms of trust.

Keywords

interpersonal trusttask-based fMRItask-free fMRIdomain-general brain networkstrust propensitytrust dynamics
Type
Chapter
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The Neurobiology of Trust , pp. 293 - 312
Publisher: Cambridge University Press
Print publication year: 2021

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References

Aimone, J. A., Houser, D., & Weber, B. (2014). Neural signatures of betrayal aversion: An fMRI study of trust. Proceedings. Biological Sciences, 281(1782), 1–6. https://doi.org/10.1098/rspb.2013.2127Google Scholar
Andellini, M., Cannatà, V., Gazzellini, S., Bernardi, B., & Napolitano, A. (2015). Test-retest reliability of graph metrics of resting state MRI functional brain networks: A review. Journal of Neuroscience Methods, 253, 183–192. https://doi.org/10.1016/j.jneumeth.2015.05.020Google Scholar
Azeez, A. K., & Biswal, B. B. (2017). A review of resting-state analysis methods. Neuroimaging Clinics of North America, 27(4), 581–592. https://doi.org/10.1016/j.nic.2017.06.001Google Scholar
Baumgartner, T., Heinrichs, M., Vonlanthen, A., Fischbacher, U., & Fehr, E. (2008). Oxytocin shapes the neural circuitry of trust and trust adaptation in humans. Neuron, 58(4), 639–650. https://doi.org/10.1016/j.neuron.2008.04.009CrossRefGoogle ScholarPubMed
Beaty, R. E., Kenett, Y. N., Christensen, A. P., et al. (2018). Robust prediction of individual creative ability from brain functional connectivity. Proceedings of the National Academy of Sciences, 115(5), 1087–1092. https://doi.org/10.1073/pnas.1713532115Google Scholar
Belfi, A. M., Koscik, T. R., & Tranel, D. (2015). Damage to the insula is associated with abnormal interpersonal trust. Neuropsychologia, 71, 165–172. https://doi.org/10.1016/j.neuropsychologia.2015.04.003Google Scholar
Bellucci, G., Chernyak, S. V., Goodyear, K., Eickhoff, S. B., & Krueger, F. (2017). Neural signatures of trust in reciprocity: A coordinate-based meta-analysis. Human Brain Mapping, 38(3), 1233–1248. https://doi.org/10.1002/hbm.23451Google Scholar
Bellucci, G., Feng, C., Camilleri, J., Eickhoff, S. B., & Krueger, F. (2018). The role of the anterior insula in social norm compliance and enforcement: Evidence from coordinate-based and functional connectivity meta-analyses. Neuroscience & Biobehavioral Reviews, 92, 378–389. https://doi.org/10.1016/j.neubiorev.2018.06.024Google Scholar
Bellucci, G., Hahn, T., Deshpande, G., & Krueger, F. (2019). Functional connectivity of specific resting-state networks predicts trust and reciprocity in the trust game. Cognitive, Affective & Behavioral Neuroscience, 19(1), 165–176. https://doi.org/10.3758/s13415-018-00654-3Google Scholar
Bellucci, G., Molter, F., & Park, S. Q. (2019). Neural representations of honesty predict future trust behavior. Nature Communications, 10(1), Article 5184. https://doi.org/10.1038/s41467-019-13261-8Google Scholar
Berg, J., Dickhaut, J., & McCabe, K. (1995). Trust, reciprocity, and social history. Games and Economic Behavior, 10(1), 122–142. https://doi.org/10.1006/game.1995.1027CrossRefGoogle Scholar
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine, 34(4), 537–541. https://doi.org/10.1002/mrm.1910340409Google Scholar
Bohnet, I., Greig, F., Herrmann, B., & Zeckhauser, R. (2008). Betrayal aversion: Evidence from Brazil, China, Oman, Switzerland, Turkey, and the United States. American Economic Review, 98(1), 294–310. https://doi.org/10.1257/aer.98.1.294CrossRefGoogle Scholar
Bohnet, I., & Zeckhauser, R. (2004). Trust, risk and betrayal. Journal of Economic Behavior & Organization, 55(4), 467–484. https://doi.org/10.1016/j.jebo.2003.11.004Google Scholar
Boksem, M. A. S., Mehta, P. H., Van den Bergh, B., et al. (2013). Testosterone inhibits trust but promotes reciprocity. Psychological Science, 24(11), 2306–2314. https://doi.org/10.1177/0956797613495063Google Scholar
Bos, P. A., Terburg, D., & Van Honk, J. (2010). Testosterone decreases trust in socially naive humans. Proceedings of the National Academy of Sciences, 107(22), 9991–9995. https://doi.org/10.1073/pnas.0911700107Google Scholar
Bressler, S. L., & Menon, V. (2010). Large-scale brain networks in cognition: Emerging methods and principles. Trends in Cognitive Sciences, 14(6), 277–290. https://doi.org/10.1016/j.tics.2010.04.004Google Scholar
Bush, K., & Cisler, J. (2013). Decoding neural events from fMRI BOLD signal: A comparison of existing approaches and development of a new algorithm. Magnetic Resonance Imaging, 31(6), 976–989. https://doi.org/10.1016/j.mri.2013.03.015Google Scholar
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., et al. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(5), 365–376. https://doi.org/10.1038/nrn3475Google Scholar
Camerer, C., & Weigelt, K. (1988). Experimental tests of a sequential equilibrium reputation model. Econometrica, 56(1), 1–36. https://doi.org/10.2307/1911840Google Scholar
Cole, D. M., Smith, S. M., & Beckmann, C. F. (2010). Advances and pitfalls in the analysis and interpretation of resting-state fMRI data. Frontiers in Systems Neuroscience, 4(8), 1–8. https://doi.org/10.3389/fnsys.2010.00008Google Scholar
Cole, M. W., Ito, T., Bassett, D. S., & Schultz, D. H. (2016). Activity flow over resting-state networks shapes cognitive task activations. Nature Neuroscience, 19(12), 1718–1726. https://doi.org/10.1038/nn.4406Google Scholar
Crawford, J. R., & Garthwaite, P. H. (2008). On the “optimal” size for normative samples in neuropsychology: Capturing the uncertainty when normative data are used to quantify the standing of a neuropsychological test score. Child Neuropsychology, 14(2), 99–117. https://doi.org/10.1080/09297040801894709Google Scholar
Cuthbert, B. N., & Insel, T. R. (2013). Toward the future of psychiatric diagnosis: The seven pillars of RDoC. BMC Medicine, 11(1), Article 126. https://doi.org/10.1186/1741-7015-11-126Google Scholar
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., et al. (2006). Consistent resting-state networks across healthy subjects. Proceedings of the National Academy of Sciences, 103(37), 13848–13853. https://doi.org/10.1073/pnas.0601417103CrossRefGoogle ScholarPubMed
Delgado, M. R., Frank, R. H., & Phelps, E. A. (2005). Perceptions of moral character modulate the neural systems of reward during the trust game. Nature Neuroscience, 8(11), 1611–1618. https://doi.org/10.1038/nn1575Google Scholar
Dosenbach, N. U. F., Nardos, B., Cohen, A. L., et al. (2010). Prediction of individual brain maturity using fMRI. Science, 329(5997), 1358–1361. https://doi.org/10.1126/science.1194144Google Scholar
Dubois, J., & Adolphs, R. (2016). Building a science of individual differences from fMRI. Trends in Cognitive Sciences, 20(6), 425–443. https://doi.org/10.1016/j.tics.2016.03.014Google Scholar
Dubois, J., Galdi, P., Han, Y., Paul, L. K., & Adolphs, R. (2018). Resting-state functional brain connectivity best predicts the personality dimension of openness to experience. Personality Neuroscience, 1, Article e6. https://doi.org/10.1017/pen.2018.8Google Scholar
Durnez, J., Blair, R., & Poldrack, R. A. (2017). Neurodesign: Optimal experimental designs for task fMRI [Preprint]. Neuroscience. https://doi.org/10.1101/119594CrossRefGoogle Scholar
Eckel, C. C., & Wilson, R. K. (2004). Is trust a risky decision? Journal of Economic Behavior & Organization, 55(4), 447–465. https://doi.org/10.1016/j.jebo.2003.11.003Google Scholar
Engelmann, J. B., Meyer, F., Ruff, C. C., & Fehr, E. (2019). The neural circuitry of affect-induced distortions of trust. Science Advances, 5(3), Article eaau3413. https://doi.org/10.1126/sciadv.aau3413Google Scholar
Fareri, D. S., Chang, L. J., & Delgado, M. R. (2012). Effects of direct social experience on trust decisions and neural reward circuitry. Frontiers in Neuroscience, 6, Article 148. https://doi.org/10.3389/fnins.2012.00148Google Scholar
Fehr, E. (2009). On the economics and biology of trust. Journal of the European Economic Association, 7(2–3), 235–266. https://doi.org/10.1162/JEEA.2009.7.2-3.235Google Scholar
Feng, C., Zhu, Z., Cui, Z., et al. (2020). Prediction of trust propensity from intrinsic brain morphology and functional connectome. Human Brain Mapping, Article hbm.25215. https://doi.org/10.1002/hbm.25215Google Scholar
Feng, C., Zhu, Z., Gu, R., Wu, X., Luo, Y.-J., & Krueger, F. (2018). Resting-state functional connectivity underlying costly punishment: A machine-learning approach. Neuroscience, 385, 25–37. https://doi.org/10.1016/j.neuroscience.2018.05.052Google Scholar
Fett, A.-K. J., Shergill, S. S., Gromann, P. M., et al. (2014). Trust and social reciprocity in adolescence: A matter of perspective-taking. Journal of Adolescence, 37(2), 175–184. https://doi.org/10.1016/j.adolescence.2013.11.011Google Scholar
Fett, A.-K. J., Shergill, S. S., Joyce, D. W., et al. (2012). To trust or not to trust: The dynamics of social interaction in psychosis. Brain, 135(3), 976–984. https://doi.org/10.1093/brain/awr359Google Scholar
Finn, E. S., Scheinost, D., Finn, D. M., Shen, X., Papademetris, X., & Constable, R. T. (2017). Can brain state be manipulated to emphasize individual differences in functional connectivity? NeuroImage, 160, 140–151. https://doi.org/10.1016/j.neuroimage.2017.03.064Google Scholar
Fouragnan, E., Chierchia, G., Greiner, S., Neveu, R., Avesani, P., & Coricelli, G. (2013). Reputational priors magnify striatal responses to violations of trust. The Journal of Neuroscience, 33(8), Article 3602. https://doi.org/10.1523/JNEUROSCI.3086-12.2013Google Scholar
Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8(9), 700–711. https://doi.org/10.1038/nrn2201Google Scholar
Friston, K. J., Frith, C. D., Turner, R., & Frackowiak, R. S. J. (1995). Characterizing evoked hemodynamics with fMRI. NeuroImage, 2(2), 157–165. https://doi.org/10.1006/nimg.1995.1018Google Scholar
Friston, K. J., Li, B., Daunizeau, J., & Stephan, K. E. (2011). Network discovery with DCM. NeuroImage, 56(3), 1202–1221. https://doi.org/10.1016/j.neuroimage.2010.12.039Google Scholar
Fu, C., Yao, X., Yang, X., Zheng, L., Li, J., & Wang, Y. (2019). Trust game database: Behavioral and EEG data from two trust games. Frontiers in Psychology, 10, Article 2656. https://doi.org/10.3389/fpsyg.2019.02656Google Scholar
Gabrieli, J. D. E., Ghosh, S. S., & Whitfield-Gabrieli, S. (2015). Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience. Neuron, 85(1), 11–26. https://doi.org/10.1016/j.neuron.2014.10.047Google Scholar
Gallagher, H. L., & Frith, C. D. (2003). Functional imaging of “theory of mind.” Trends in Cognitive Sciences, 7(2), 77–83. https://doi.org/10.1016/S1364-6613(02)00025-6Google Scholar
Greene, A. S., Gao, S., Scheinost, D., & Constable, R. T. (2018). Task-induced brain state manipulation improves prediction of individual traits. Nature Communications, 9(1), Article 2807. https://doi.org/10.1038/s41467-018-04920-3Google Scholar
Hahn, T., Notebaert, K., Anderl, C., Reicherts, P., et al. (2015). Reliance on functional resting-state network for stable task control predicts behavioral tendency for cooperation. NeuroImage, 118, 231–236. https://doi.org/10.1016/j.neuroimage.2015.05.093Google Scholar
Hahn, T., Notebaert, K., Anderl, C., Teckentrup, V., Kaßecker, A., & Windmann, S. (2015). How to trust a perfect stranger: Predicting initial trust behavior from resting-state brain-electrical connectivity. Social Cognitive and Affective Neuroscience, 10(6), 809–813. https://doi.org/10.1093/scan/nsu122Google Scholar
Haxby, J. V. (2012). Multivariate pattern analysis of fMRI: The early beginnings. NeuroImage, 62(2), 852–855. https://doi.org/10.1016/j.neuroimage.2012.03.016Google Scholar
Heine, L., Soddu, A., Gómez, F., et al. (2012). Resting state networks and consciousness. Frontiers in Psychology, 3, Article 295. https://doi.org/10.3389/fpsyg.2012.00295Google Scholar
Hollerman, J. R., & Schultz, W. (1998). Dopamine neurons report an error in the temporal prediction of reward during learning. Nature Neuroscience, 1(4), 304–309. https://doi.org/10.1038/1124Google Scholar
Hsu, W.-T., Rosenberg, M. D., Scheinost, D., Constable, R. T., & Chun, M. M. (2018). Resting-state functional connectivity predicts neuroticism and extraversion in novel individuals. Social Cognitive and Affective Neuroscience, 13(2), 224–232. https://doi.org/10.1093/scan/nsy002Google Scholar
Hughes, B. L., Ambady, N., & Zaki, J. (2017). Trusting outgroup, but not ingroup members, requires control: Neural and behavioral evidence. Social Cognitive and Affective Neuroscience, 12(3), 372–381. https://doi.org/10.1093/scan/nsw139Google Scholar
Joel, D., Niv, Y., & Ruppin, E. (2002). Actor–critic models of the basal ganglia: New anatomical and computational perspectives. Neural Networks, 15(4–6), 535–547. https://doi.org/10.1016/S0893-6080(02)00047-3Google Scholar
Johnson, N. D., & Mislin, A. A. (2011). Trust games: A meta-analysis. Journal of Economic Psychology, 32(5), 865–889. https://doi.org/10.1016/j.joep.2011.05.007Google Scholar
King-Casas, B., Sharp, C., Lomax-Bream, L., Lohrenz, T., Fonagy, P., & Montague, P. R. (2008). The rupture and repair of cooperation in borderline personality disorder. Science, 321(5890), 806–810. https://doi.org/10.1126/science.1156902Google Scholar
King-Casas, B., Tomlin, D., Anen, C., Camerer, C. F., Quartz, S. R., & Read Montague, P. (2005). Getting to know you: Reputation and trust in a two-person economic exchange. Science, 308(5718), 78–83. https://doi.org/10.1126/science.1108062CrossRefGoogle Scholar
Koscik, T. R., & Tranel, D. (2011). The human amygdala is necessary for developing and expressing normal interpersonal trust. Neuropsychologia, 49(4), 602–611. https://doi.org/10.1016/j.neuropsychologia.2010.09.023CrossRefGoogle ScholarPubMed
Kosfeld, M., Heinrichs, M., Zak, P. J., Fischbacher, U., & Fehr, E. (2005). Oxytocin increases trust in humans. Nature, 435(7042), 673–676. https://doi.org/10.1038/nature03701CrossRefGoogle ScholarPubMed
Krueger, F., McCabe, K., Moll, J., et al. (2007). Neural correlates of trust. Proceedings of the National Academy of Sciences, 104(50), 20084–20089. https://doi.org/10.1073/pnas.0710103104Google Scholar
Krueger, F., & Meyer-Lindenberg, A. (2019). Toward a model of interpersonal trust drawn from neuroscience, psychology, and economics. Trends in Neurosciences, 42(2), 92–101. https://doi.org/10.1016/j.tins.2018.10.004Google Scholar
Lee, M. H., Smyser, C. D., & Shimony, J. S. (2013). Resting-state fMRI: A review of methods and clinical applications. American Journal of Neuroradiology, 34(10), 1866–1872. https://doi.org/10.3174/ajnr.A3263Google Scholar
Lemmers-Jansen, I. L. J., Fett, A.-K. J., Hanssen, E., Veltman, D. J., & Krabbendam, L. (2019). Learning to trust: Social feedback normalizes trust behavior in first-episode psychosis and clinical high risk. Psychological Medicine, 49(5), 780–790. https://doi.org/10.1017/S003329171800140XGoogle Scholar
Li, N., Ma, N., Liu, Y., et al. (2013). Resting-state functional connectivity predicts impulsivity in economic decision-making. Journal of Neuroscience, 33(11), 4886–4895. https://doi.org/10.1523/JNEUROSCI.1342-12.2013Google Scholar
Linden, D. E. J. (2012). The challenges and promise of neuroimaging in psychiatry. Neuron, 73(1), 8–22. https://doi.org/10.1016/j.neuron.2011.12.014Google Scholar
Lo, A., Chernoff, H., Zheng, T., & Lo, S.-H. (2015). Why significant variables aren’t automatically good predictors. Proceedings of the National Academy of Sciences, 112(45), 13892–13897. https://doi.org/10.1073/pnas.1518285112Google Scholar
Logothetis, N. K. (2008). What we can do and what we cannot do with fMRI. Nature, 453(7197), 869–878. https://doi.org/10.1038/nature06976Google Scholar
Lu, X., Li, T., Xia, Z., et al. (2019). Connectome‐based model predicts individual differences in propensity to trust. Human Brain Mapping, 40(6), 1942–1954. https://doi.org/10.1002/hbm.24503Google Scholar
Montague, P. (2002). Hyperscanning: Simultaneous fMRI during linked social interactions. NeuroImage, 16(4), 1159–1164. https://doi.org/10.1006/nimg.2002.1150Google Scholar
Moretto, G., Sellitto, M., & di Pellegrino, G. (2013). Investment and repayment in a trust game after ventromedial prefrontal damage. Frontiers in Human Neuroscience, 7, Article 593. https://doi.org/10.3389/fnhum.2013.00593Google Scholar
Mwansisya, T. E., Hu, A., Li, Y., et al. (2017). Task and resting-state fMRI studies in first-episode schizophrenia: A systematic review. Schizophrenia Research, 189, 9–18. https://doi.org/10.1016/j.schres.2017.02.026Google Scholar
Nave, G., Camerer, C., & McCullough, M. (2015). Does oxytocin increase trust in humans? A critical review of research. Perspectives on Psychological Science, 10(6), 772–789. https://doi.org/10.1177/1745691615600138Google Scholar
Nostro, A. D., Müller, V. I., Varikuti, D. P., et al. (2018). Predicting personality from network-based resting-state functional connectivity. Brain Structure and Function, 223(6), 2699–2719. https://doi.org/10.1007/s00429-018-1651-zGoogle Scholar
O’Doherty, J., Dayan, P., Schultz, J., Deichmann, R., Friston, K., & Dolan, R. J. (2004). Dissociable roles of ventral and dorsal striatum in instrumental conditioning. Science, 304(5669), 452–454. https://doi.org/10.1126/science.1094285Google Scholar
Ogawa, S., Tank, D. W., Menon, R., et al. (1992). Intrinsic signal changes accompanying sensory stimulation: Functional brain mapping with magnetic resonance imaging. Proceedings of the National Academy of Sciences, 89(13), 5951–5955. https://doi.org/10.1073/pnas.89.13.5951Google Scholar
O’Reilly, J. X., Woolrich, M. W., Behrens, T. E. J., Smith, S. M., & Johansen-Berg, H. (2012). Tools of the trade: Psychophysiological interactions and functional connectivity. Social Cognitive and Affective Neuroscience, 7(5), 604–609. https://doi.org/10.1093/scan/nss055Google Scholar
Orrù, G., Pettersson-Yeo, W., Marquand, A. F., Sartori, G., & Mechelli, A. (2012). Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review. Neuroscience & Biobehavioral Reviews, 36(4), 1140–1152. https://doi.org/10.1016/j.neubiorev.2012.01.004Google Scholar
Patanaik, A., Tandi, J., Ong, J. L., Wang, C., Zhou, J., & Chee, M. W. L. (2018). Dynamic functional connectivity and its behavioral correlates beyond vigilance. NeuroImage, 177, 1–10. https://doi.org/10.1016/j.neuroimage.2018.04.049Google Scholar
Patriat, R., Molloy, E. K., Meier, T. B., et al. (2013). The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated. NeuroImage, 78, 463–473. https://doi.org/10.1016/j.neuroimage.2013.04.013Google Scholar
Petersen, S. E., & Dubis, J. W. (2011). The mixed block/event design. NeuroImage, 62(2), 1177–1184. https://doi.org/10.1016/j.neuroimage.2011.09.084Google Scholar
Plitt, M., Barnes, K. A., Wallace, G. L., Kenworthy, L., & Martin, A. (2015). Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism. Proceedings of the National Academy of Sciences, 112(48), E6699–E6706. https://doi.org/10.1073/pnas.1510098112Google Scholar
Power, J. D., Cohen, A. L., Nelson, S. M., et al. (2011). Functional network organization of the human brain. Neuron, 72(4), 665–678. https://doi.org/10.1016/j.neuron.2011.09.006Google Scholar
Raichle, M. E., & Snyder, A. Z. (2007). A default mode of brain function: A brief history of an evolving idea. NeuroImage, 37(4), 1083–1090. https://doi.org/10.1016/j.neuroimage.2007.02.041Google Scholar
Reggente, N., Moody, T. D., Morfini, F., et al. (2018). Multivariate resting-state functional connectivity predicts response to cognitive behavioral therapy in obsessive–compulsive disorder. Proceedings of the National Academy of Sciences, 115(9), 2222–2227. https://doi.org/10.1073/pnas.1716686115Google Scholar
Riedl, R., & Javor, A. (2012). The biology of trust: Integrating evidence from genetics, endocrinology, and functional brain imaging. Journal of Neuroscience, Psychology, and Economics, 5(2), 63–91. https://doi.org/10.1037/a0026318Google Scholar
Rilling, J. K., & Sanfey, A. G. (2011). The neuroscience of social decision making. Annual Review of Psychology, 62(1), 23–48. https://doi.org/10.1146/annurev.psych.121208.131647Google Scholar
Roebroeck, A., Formisano, E., & Goebel, R. (2005). Mapping directed influence over the brain using Granger causality and fMRI. NeuroImage, 25(1), 230–242. https://doi.org/10.1016/j.neuroimage.2004.11.017Google Scholar
Rosazza, C., & Minati, L. (2011). Resting-state brain networks: Literature review and clinical applications. Neurological Sciences, 32(5), 773–785. https://doi.org/10.1007/s10072-011-0636-yCrossRefGoogle ScholarPubMed
Seppänen, R., Blomqvist, K., & Sundqvist, S. (2007). Measuring inter-organizational trust: A critical review of the empirical research in 1990–2003. Industrial Marketing Management, 36(2), 249–265. https://doi.org/10.1016/j.indmarman.2005.09.003Google Scholar
Smitha, K., Akhil Raja, K., Arun, K., et al. (2017). Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks. The Neuroradiology Journal, 30(4), 305–317. https://doi.org/10.1177/1971400917697342Google Scholar
Sporns, O., Honey, C. J., & Kötter, R. (2007). Identification and classification of hubs in brain networks. PLoS ONE, 2(10), Article e1049. https://doi.org/10.1371/journal.pone.0001049Google Scholar
Spreng, R. N., Mar, R. A., & Kim, A. S. N. (2009). The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. Journal of Cognitive Neuroscience, 21(3), 489–510. https://doi.org/10.1162/jocn.2008.21029Google Scholar
Sun, H., Verbeke, W. J. M. I., Pozharliev, R., Bagozzi, R. P., Babiloni, F., & Wang, L. (2019). Framing a trust game as a power game greatly affects interbrain synchronicity between trustor and trustee. Social Neuroscience, 14(6), 635–648. https://doi.org/10.1080/17470919.2019.1566171Google Scholar
Tang, H., Lu, X., Cui, Z., et al. (2018). Resting-state functional connectivity and deception: Exploring individualized deceptive propensity by machine learning. Neuroscience, 395, 101–112. https://doi.org/10.1016/j.neuroscience.2018.10.036Google Scholar
Tavor, I., Jones, O. P., Mars, R. B., Smith, S. M., Behrens, T. E., & Jbabdi, S. (2016). Task-free MRI predicts individual differences in brain activity during task performance. Science, 352(6282), 216–220. https://doi.org/10.1126/science.aad8127Google Scholar
Tobyne, S. M., Somers, D. C., Brissenden, J. A., Michalka, S. W., Noyce, A. L., & Osher, D. E. (2018). Prediction of individualized task activation in sensory modality-selective frontal cortex with “connectome fingerprinting.” NeuroImage, 183, 173–185. https://doi.org/10.1016/j.neuroimage.2018.08.007CrossRefGoogle ScholarPubMed
Tomasi, D., & Volkow, N. D. (2010). Functional connectivity density mapping. Proceedings of the National Academy of Sciences, 107(21), 9885–9890. https://doi.org/10.1073/pnas.1001414107Google Scholar
Tomlin, D. (2006). Agent-specific responses in the cingulate cortex during economic exchanges. Science, 312(5776), 1047–1050. https://doi.org/10.1126/science.1125596Google Scholar
Tzieropoulos, H. (2013). The trust game in neuroscience: A short review. Social Neuroscience, 8(5), 407–416. https://doi.org/10.1080/17470919.2013.832375Google Scholar
Van den Heuvel, M. P., & Hulshoff Pol, H. E. (2010). Exploring the brain network: A review on resting-state fMRI functional connectivity. European Neuropsychopharmacology, 20(8), 519–534. https://doi.org/10.1016/j.euroneuro.2010.03.008Google Scholar
Van Honk, J., Eisenegger, C., Terburg, D., Stein, D. J., & Morgan, B. (2013). Generous economic investments after basolateral amygdala damage. Proceedings of the National Academy of Sciences, 110(7), 2506–2510. https://doi.org/10.1073/pnas.1217316110Google Scholar
Van Overwalle, F. (2009). Social cognition and the brain: A meta-analysis. Human Brain Mapping, 30(3), 829–858. https://doi.org/10.1002/hbm.20547Google Scholar
Whelan, R., & Garavan, H. (2014). When optimism hurts: Inflated predictions in psychiatric neuroimaging. Biological Psychiatry, 75(9), 746–748. https://doi.org/10.1016/j.biopsych.2013.05.014Google Scholar
Wong, C. W., Olafsson, V., Tal, O., & Liu, T. T. (2012). Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI. NeuroImage, 63(1), 356–364. https://doi.org/10.1016/j.neuroimage.2012.06.035Google Scholar
Worsley, K. J., & Friston, K. J. (1995). Analysis of fMRI time-series revisited – again. NeuroImage, 2(3), 173–181. https://doi.org/10.1006/nimg.1995.1023Google Scholar
Yanagisawa, K., Masui, K., Furutani, K., Nomura, M., Ura, M., & Yoshida, H. (2011). Does higher general trust serve as a psychosocial buffer against social pain? An NIRS study of social exclusion. Social Neuroscience, 6(2), 190–197. https://doi.org/10.1080/17470919.2010.506139Google Scholar
Yarkoni, T., & Braver, T. S. (2010). Cognitive neuroscience approaches to individual differences in working memory and executive control: Conceptual and methodological issues. In Gruszka, A., Matthews, G., & Szymura, B. (Eds.), Handbook of individual differences in cognition (pp. 87–107). Springer. https://doi.org/10.1007/978-1-4419-1210-7_6Google Scholar
Yarkoni, T., & Westfall, J. (2017). Choosing prediction over explanation in psychology: Lessons from machine learning. Perspectives on Psychological Science, 12(6), 1100–1122. https://doi.org/10.1177/1745691617693393Google Scholar
Zuo, X.-N., Kelly, C., Adelstein, J. S., Klein, D. F., Castellanos, F. X., & Milham, M. P. (2010). Reliable intrinsic connectivity networks: Test–retest evaluation using ICA and dual regression approach. NeuroImage, 49(3), 2163–2177. https://doi.org/10.1016/j.neuroimage.2009.10.080Google Scholar

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