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Neural substrates on the judgment of sequential benefits and losses

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Abstract

People need to adapt to situations where they experience sequential benefits (or losses) to ensure survival. This study investigated the neural substrates involved in judgments of sequential benefits and losses. A total of 29 healthy volunteers participated in this study, in which they were asked to participate in a game of purchasing stocks while a magnetic resonance imaging scan was performed. This game had two main types of trials: (1) participants received four sequential financial benefits (or losses), and (2) participants received an equal amount of benefits (or losses) immediately. The results showed greater activation of the orbitofrontal cortex (OFC) when four benefits were received sequentially than when an equal amount of benefits was received immediately. This indicates that the OFC plays a crucial role in the process of mental integration of sequential benefits and interpretation of their valuations. It also showed greater activation of the dorsal striatum when four sequental losses were received than when an equal amount of losses was received immediately. However, it cannot be concluded that activation of the dorsal striatum reflects the differences between sequential and immediate losses, because previous studies have not confirmed this perspective. Therefore, it is necessary to clarify the function of the striatum in processing these losses.

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Notes

  1. It is possible that the response time for the game of luck indicates participants’ satisfaction. We examined the relationship between the response time for the game of luck and satisfaction scores using Pearson’s correlation coefficients. The results were as follows: for the 2-day 2 condition, N = 1296, r = −0.09, p < 0.01, and for the 5-day 5 condition, N = 1,296, r = −0.04, ns. Although the results showed a significant negative, weak correlation for the 2-day 2 condition, a strong correlation was not found between the response time for the game of luck and the participants’ satisfaction scores.

References

  • Akitsuki, Y., Sugiura, M., Watanabe, J., Yamashita, K., Sassa, Y., Awata, S., & Kawashima, R. (2003). Context-dependent cortical activation in response to financial reward and penalty: An event-related fMRI study. NeuroImage, 19, 1674–1685.

    Article  PubMed  Google Scholar 

  • Ariely, D. (1998). Combining experiences over time: The effects of duration, intensity changes and on-papers line measurements on retrospective pain evaluation. Journal of Behavioral Decision Making, 11, 19–45.

    Article  Google Scholar 

  • Balodis, I. M., & Potenza, M. N. (2015). Anticipatory reward processing in addicted populations: A focus on the monetary incentive delay task. Biological Psychiatry, 77, 434–444. https://doi.org/10.1016/j.biopsych.2014.08.020

    Article  PubMed  Google Scholar 

  • Balodis, I. M., Kober, H., Worhunsky, P. D., Stevens, M. C., Pearlson, G. D., & Potenza, M. N. (2012). Diminished frontostriatal activity during processing of monetary rewards and losses in pathological gambling. Biological Psychiatry, 71, 749–757. https://doi.org/10.1016/j.biopsych.2012.01.006

    Article  PubMed  PubMed Central  Google Scholar 

  • Bartra, O., McGuire, J. T., & Kable, J. W. (2013). The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value. NeuroImage, 76, 412–427. https://doi.org/10.1016/j.neuroimage.2013.02.063

    Article  PubMed  Google Scholar 

  • Bechara, A., & Damasio, A. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and Economic Behavior, 52, 336–372.

    Article  Google Scholar 

  • Bray, S., Shimojo, S., & O'Doherty, J. P. (2010). Human medial orbitofrontal cortex is recruited during experience of imagined and real rewards. Journal of Neurophysiology, 103, 2506–2512.

    Article  PubMed  Google Scholar 

  • Breiter, H. C., Aharon, I., Kahneman, D., Dale, A., & Shizgal, P. (2001). Functional imaging of neural responses to monetary gains and losses. Neuron, 30, 619–639.

    Article  PubMed  Google Scholar 

  • Christopoulos, G. I., Tobler, P. N., Bossaerts, P., Dolan, R. J., & Schultz, W. (2009). Neural correlates of value, risk, and risk aversion contributing to decision making under risk. Journal of Neuroscience, 29, 12574–12583.

    Article  PubMed  Google Scholar 

  • Eickhoff, S. B., Stephan, K. E., Mohlberg, H., Grefkes, C., Fink, G. R., Amunts, K., & Zilles, K. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. NeuroImage, 25, 1325–1335.

    Article  PubMed  Google Scholar 

  • Eickhoff, S. B., Heim, S., Zilles, K., & Amunts, K. (2006). Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps. NeuroImage, 32, 570–582.

    Article  PubMed  Google Scholar 

  • Eickhoff, S. B., Paus, T., Caspers, S., Grosbras, M.-H., Evans, A. C., Zilles, K., & Amunts, K. (2007). Assignment of functional activations to probabilistic cytoarchitectonic areas revisited. NeuroImage, 36, 511–521.

    Article  PubMed  Google Scholar 

  • Elliott, R., Friston, K. J., & Dolan, R. J. (2000). Dissociable neural responses in human reward systems. Journal of Neuroscience, 20, 6159–6165.

    Article  PubMed  Google Scholar 

  • Elliott, R., Agnew, Z., & Deakin, J. F. W. (2008). Medial orbitofrontal cortex codes relative rather than absolute value of financial rewards in humans. European Journal of Neuroscience, 27, 2213–2218.

    Article  PubMed  Google Scholar 

  • Feinberg, D. A., Moeller, S., Smith, S. M., Auerbach, E., Ramanna, S., Glasser, M. F., & Yacoub, E. (2010). Multiplexed echo planar imaging for sub-second whole brain fMRI and fast diffusion imaging. PLoS One, 5, e15710.

    Article  PubMed  PubMed Central  Google Scholar 

  • Filbey, F. M., Dunlop, J., & Myers, U. S. (2013). Neural effects of positive and negative incentives during marijuana withdrawal. PLoS One, 8, e61470. https://doi.org/10.1371/journal.pone.0061470

    Article  PubMed  PubMed Central  Google Scholar 

  • Flandin, G., & Friston, K. J. (2019). Analysis of family-wise error rates in statistical parametric mapping using random field theory. Human Brain Mapping, 40, 2052–2054.

    Article  PubMed  Google Scholar 

  • Friston, K. J., Holmes, A., Poline, J. -B., Price, C. J., & Frith, C. D. (1996). Detecting activations in pet and fMRI: Levels of inference and power. NeuroImage, 4, 223–235.

    Article  PubMed  Google Scholar 

  • Friston, K. J., Holmes, A. P., & Worsley, K. J. (1999). How many subjects constitute a study? NeuroImage, 10, 1–5.

    Article  PubMed  Google Scholar 

  • Haber, S. N., & Knutson, B. (2010). The reward circuit: Linking primate anatomy and human imaging. Neuropsychopharmacology, 35, 4–26.

    Article  PubMed  Google Scholar 

  • Hardin, M. G., Pine, D. S., & Ernst, M. (2009). The influence of context valence in the neural coding of monetary outcomes. NeuroImage, 48, 249–257. https://doi.org/10.1016/j.neuroimage.2009.06.050

    Article  PubMed  Google Scholar 

  • Hsee, C. K., & Abelson, R. P. (1991). The velocity relation: Satisfaction as a function of the first derivative of outcome over time. Journal of Personality and Social Psychology, 60, 341–347.

    Article  Google Scholar 

  • Kahneman, D., & Tversky, A. (1979). Intuitive prediction: Biases and corrective procedures. Management Science, 12, 313–327.

    Google Scholar 

  • Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001). Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience, 21, RC159.

    Article  PubMed  Google Scholar 

  • Knutson, B., Fong, G. W., Bennett, S. M., Adams, C. M., & Hommer, D. (2003). A region of mesial prefrontal cortex tracks monetarily rewarding outcomes: Characterization with rapid event-related fMRI. NeuroImage, 18, 263–272. https://doi.org/10.1016/S1053-8119(02)00057-5

    Article  PubMed  Google Scholar 

  • Kohls, G., Perino, M. T., Taylor, J. M., Madva, E. N., Cayless, S. J., Troiani, V., & Schultz, R. T. (2013). The nucleus accumbens is involved in both the pursuit of social reward and the avoidance of social punishment. Neuropsychologia, 51, 2062–2069. https://doi.org/10.1016/j.neuropsychologia.2013.07.020

    Article  PubMed  PubMed Central  Google Scholar 

  • Kringelbach, M. L., & Rolls, E. T. (2004). The functional neuroanatomy of the human orbitofrontal cortex: Evidence from neuroimaging and neuropsychology. Progress in Neurobiology, 72, 341–372.

    Article  PubMed  Google Scholar 

  • Lane, R. D., Reiman, E. M., Ahern, G. L., & Schwartz, G. E. (1997). Neuroanatomical correlates of happiness, sadness, and disgust. The American Journal of Psychiatry, 154, 926–933. https://doi.org/10.1176/ajp.154.7.926

    Article  PubMed  Google Scholar 

  • Litt, A., Plassmann, H., Shiv, B., & Rangel, A. (2011). Dissociating valuation and saliency signals during decision-making. Cerebral Cortex, 21, 95–102.

    Article  PubMed  Google Scholar 

  • Loewenstein, G., & Prelec, D. (1993). Preferences for sequences of outcomes. Psychological Review, 100, 91–108.

    Article  Google Scholar 

  • Loewenstein, G., & Sicherman, N. (1991). Do workers prefer increasing wage profile? Journal of Labor Economics, 9, 67–84.

    Article  Google Scholar 

  • Louie, K., & Glimcher, P. W. (2012). Efficient coding and the neural representation of value. Annals of the New York Academy of Sciences, 1251, 13–32.

    Article  PubMed  Google Scholar 

  • Louie, K., Grattan, L. E., & Glimcher, P. W. (2011). Reward value-based gain control: Divisive normalization in parietal cortex. Journal of Neuroscience, 31, 10627–10639.

    Article  PubMed  Google Scholar 

  • Moeller, S., Yacoub, E., Olman, C. A., Auerbach, E., Strupp, J., Harel, N., & Uğurbil, K. (2010). Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain FMRI. Magnetic Resonance in Medicine, 63, 1144–1153.

    Article  PubMed  PubMed Central  Google Scholar 

  • Montague, P. R., Dayan, P., & Sejnowski, T. J. (1996). A framework for mesencephalic dopamine systems based on predictive Hebbian learning. Journal of Neuroscience, 16, 1936–1947.

    Article  PubMed  Google Scholar 

  • Mullett, T. L., & Tunney, R. J. (2013). Value representations by rank order in a distributed network of varying context dependency. Brain and Cognition, 82, 76–83.

    Article  PubMed  Google Scholar 

  • Nelson, L. D., & Meyvis, T. (2008). Interrupted consumption: Disrupting adaptation to hedonic experiences. Journal of Marketing Research, 45, 654–664.

    Article  Google Scholar 

  • Nelson, L. D., Meyvis, T., & Galak, J. (2009). Enhancing the television-viewing experience through commercial interruptions. Journal of Consumer Research, 36, 160–172. https://doi.org/10.1086/597030

    Article  Google Scholar 

  • Oldham, S., Murawski, C., Fornito, A., Youssef, G., Yucel, M., & Lorenzetti, V. (2018). The anticipation and outcome phases of reward and loss processing: A neuroimaging meta-analysis of the monetary incentive delay task. Human Brain Mapping, 39, 3398–3418.

    Article  PubMed  PubMed Central  Google Scholar 

  • Peters, J., & Büchel, C. (2010). Neural representations of subjective reward value. Behavioral Brain Research, 213, 135–141.

    Article  Google Scholar 

  • Reiman, E. M., Lane, R. D., Ahern, G. L., & Schwartz, G. E. (1997). Neuroanatomical correlates of externally and internally generated human emotion. The American Journal of Psychiatry, 154, 918–925. https://doi.org/10.1176/ajp.154.7.918

    Article  PubMed  Google Scholar 

  • Rudorf, S., & Hare, T. A. (2014). Interactions between dorsolateral and ventromedial prefrontal cortex underlie context-dependent stimulus valuation in goal-directed choice. Journal of Neuroscience, 34, 15988–15996.

    Article  PubMed  Google Scholar 

  • Sescousse, G., Caldu, X., Segura, B., & Dreher, J. C. (2013). Processing of primary and secondary rewards: A quantitative meta-analysis and review of human functional neuroimaging studies. Neuroscience and Biobehavioral Reviews, 37, 681–696. https://doi.org/10.1016/j.neubiorev.2013.02.002

    Article  PubMed  Google Scholar 

  • Seubert, J., Freiher, J., Djordjevic, J., & Lundström, J. N. (2013). Statistical localization of human olfactory cortex. NeuroImage, 66, 333–342.

    Article  PubMed  Google Scholar 

  • Skinner, B. F. (1937). Two types of conditioned reflex: A reply to Konorski and Miller. Journal of General Psychology, 16, 272–279.

    Article  Google Scholar 

  • Skinner, B. F. (1938). The behavior of organisms. Appleton-Century-Crofts.

    Google Scholar 

  • Staddon, J. E. R., & Cerutti, D. T. (2003). Operant conditioning. Annual Review of Psychology, 54, 115–144.

    Article  PubMed  Google Scholar 

  • Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315, 515–518. https://doi.org/10.1126/science.1134239

    Article  PubMed  Google Scholar 

  • Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297–323.

    Article  Google Scholar 

  • Vermeer, A. B. L., Boksem, M. A. S., & Sanfey, A. G. (2014). Neural mechanisms underlying context-dependent shifts in risk preferences. NeuroImage, 103, 355–363. https://doi.org/10.1016/j.neuroimage.2014.09.054

    Article  Google Scholar 

  • Vlaev, I., Chater, N., Stewart, N., & Brown, G. D. A. (2011). Does the brain calculate value? Trends in Cognitive Sciences, 15, 546–554.

    Article  PubMed  Google Scholar 

  • Xu, J., Moeller, S., Auerbach, E. J., Struppe, J., Smith, S. M., Feinberg, D. A., Yacoub, E., & Uğurbil, K. (2013). Evaluation of slice accelerations using multiband echo planar imaging at 3T. NeuroImage, 83, 991–1001.

    Article  PubMed  Google Scholar 

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Author note

This work was supported by Grant-in-Aid for Scientific Research C 18K03020 from the Japan Society for the Promotion of Science. We thank Prof. Hirohisa Watanabe for his help and support throughout the experiment.

Funding

This work was supported by Grant-in-Aid for Scientific Research C 18K03020 from the Japan Society for the Promotion of Science.

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Authors and Affiliations

  1. Department of Multidisciplinary Psychology, Kinjo Gakuin University, 2-1723 Omori, Moriyama-ku, Nagoya, Aichi, 463-8521, Japan

    Masayo Noda

  2. Division of Psychology, Department of Cognitive and Psychological Sciences, Graduate School of Informatics, Nagoya University, Nagoya, Japan

    Hiroki C. Tanabe & Ayumi Yoshioka

  3. Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan

    Ayumi Yoshioka

  4. KONICA MINOLTA, INC., Tokyo, Japan

    Masato Kimura

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Correspondence to Masayo Noda.

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Appendix

Appendix

Appendix Table 5

Table 5 Composition of the target and filler trials. "○" in "Timing to evaluate satisfaction" or "Timing of game of luck" represents that participants were asked to evaluate their satisfaction or that the game of luck was conducted, whereas "×”represents no evaluation or game of luck. The order of "○"and "×" shows their order in the trials. For example, if "○×" is shown, this indicates that on the first day, participants were asked for their evaluation after the price was presented, and then on the second day, participants were not asked for their evaluation after the price was presented
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Appendix Table 6

Table 6 Brain regions associated with rewards or losses for ROI analyses
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Noda, M., Tanabe, H.C., Yoshioka, A. et al. Neural substrates on the judgment of sequential benefits and losses. Cogn Affect Behav Neurosci 23, 997–1013 (2023). https://doi.org/10.3758/s13415-023-01087-3

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