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Trait self-control is predicted by how reward associations modulate Stroop interference

Abstract

Although cognitive control is commonly identified as the basis of self-controlled behavior, correlations found between trait self-control and laboratory measures of cognitive control such as Stroop interference are typically low. Based on the notion that self-control requires the ability to refrain from rewarded behaviors, and inspired by the recent finding that Stroop interference is modulated by reward associations, we propose the idea that the modulation of interference by reward associations (MIRA) is a cognitive marker of trait self-control. Two independent samples of participants completed (1) a modified Stroop task designed to assess MIRA and (2) two common measures of trait self-control: the Brief Self-Control Scale (BSCS) and the Barratt Impulsiveness Scale (BIS-11). MIRA was strongly correlated with the BSCS and moderately correlated with two of the three subscales of the BIS-11. MIRA thus appears to reflect a cognitive endophenotype of individual differences in self-control, and perhaps of related mental disorders.

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References

  1. Bühringer, G., Wittchen, H.-U., Gottlebe, K., Kufeld, C., & Goschke, T. (2008). Why people change? The role of cognitive control processes in the onset and cessation of substance abuse disorders. International Journal of Methods in Psychiatric Research, 17(S1), 4–15.

  2. Claes, L., Vertommen, H., & Braspenning, N. (2000). Psychometric properties of the Dickman Impulsivity Inventory. Personality and Individual Differences, 29, 27–35.

  3. Cohen, J. R., & Lieberman, M. D. (2010). The common neural basis of exerting self-control in multiple domains. In Y. Trope, R. Hassin, & K. N. Oechsner (Eds.), Self-control (pp. 141–160). Oxford: Oxford University Press.

  4. de Ridder, D. T., Lensvelt-Mulders, G., Finkenauer, C., Stok, F. M., & Baumeister, R. F. (2012). Taking stock of self-control: a meta-analysis of how trait self-control relates to a wide range of behaviors. Personality and Social Psychology Review, 16(1), 76–99.

  5. Dickman, S. J. (1990). Functional and dysfunctional impulsivity: personality and cognitive correlates. Journal of Personality and Social Psychology, 58(1), 95–102.

  6. Dreisbach, G., & Fischer, R. (2012). The role of affect and reward in the conflict-triggered adjustment of cognitive control. Frontiers in Human Neuroscience, 6, 342.

  7. Duckworth, A. L., & Kern, M. L. (2011). A meta-analysis of the convergent validity of self-control measures. Journal of Research in Personality, 45(3), 259–268.

  8. Duckworth, A. L., & Seligman, M. E. P. (2005). Self-discipline outdoes IQ in predicting academic performance of adolescents. Psychological Science, 16(12), 939–944.

  9. Goldstein, R. Z., & Volkow, N. D. (2011). Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nature Reviews Neuroscience, 12, 652–669.

  10. Goschke, T. (2014). Dysfunctions of decision-making and cognitive control as transdiagnostic mechanisms of mental disorders: advances, gaps, and needs in current research. International Journal of Methods in Psychiatric Research, 23(S1), 41–57.

  11. Goschke, T., & Bolte, A. (2014). Emotional modulation of control dilemmas: the role of positive affect, reward, and dopamine in cognitive stability and flexibility. Neuropsychologia, 62, 403–423.

  12. Heatherton, T. F., & Wagner, D. D. (2011). Cognitive neuroscience of self-regulation failure. Trends in Cognitive Sciences, 15(3), 132–139.

  13. Hofmann, W., Baumeister, R. F., Förster, G., & Vohs, K. D. (2012a). Everyday temptations: an experience sampling study of desire, conflict, and self-control. Journal of Personality and Social Psychology, 102(6), 1318–1335.

  14. Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), 162–176.

  15. Hofmann, W., Schmeichel, B. J., & Baddeley, A. D. (2012b). Executive functions and self-regulation. Trends in Cognitive Sciences, 16(3), 174–180.

  16. Hofmann, W., Vohs, K. D., & Baumeister, R. F. (2012c). What people desire, feel conflicted about, and try to resist in everyday life. Psychological Science, 23(6), 582–588.

  17. Krebs, R. M., Boehler, C. N., Appelbaum, L. G., & Woldorff, M. G. (2013). Reward associations reduce behavioral interference by changing the temporal dynamics of conflict processing. PLoS One, 8(1), e53894.

  18. Krebs, R. M., Boehler, C. N., Egner, T., & Woldorff, M. G. (2011). The neural underpinnings of how reward associations can both guide and misguide attention. Journal of Neuroscience, 31(26), 9752–9759.

  19. Krebs, R. M., Boehler, C. N., & Woldorff, M. G. (2010). The influence of reward associations on conflict processing in the Stroop task. Cognition, 117(3), 341–347.

  20. Logan, G. D., Schachar, R. J., & Tannock, R. (1997). Impulsivity and inhibitory control. Psychological Science, 8(1), 60–64.

  21. MacLeod, C. (1991). Half a century of research on the Stroop effect: an integrative review. Psychological Bulletin, 109(2), 163–203.

  22. Miyake, A., & Friedman, N. P. (2012). The nature and organization of individual differences in executive functions: four general conclusions. Current Directions in Psychological Science, 21(1), 8–14.

  23. Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “‘frontal lobe’” tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100.

  24. Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion of limited resources: does self-control resemble a muscle? Psychological Bulletin, 126(2), 247–259.

  25. Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt Impulsiveness Scale. Journal of Clinical Psychology, 51(6), 768–774.

  26. Robbins, T. W., Gillan, C. M., Smith, D. G., de Wit, S., & Ersche, K. D. (2012). Neurocognitive endophenotypes of impulsivity and compulsivity: towards dimensional psychiatry. Trends in Cognitive Sciences, 16(1), 81–91.

  27. Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A compendium of neuropsychological tests. Administration, norms, and commentary (3rd ed.). Oxford: Oxford University Press.

  28. Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662.

  29. Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271–324.

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Acknowledgments

This research was supported in part by a grant from the Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Centre “Volition and Cognitive Control” (SFB 940/1).

Author information

Correspondence to Max Wolff.

Appendix: Rationale for and consequences of not counterbalancing response–reward mappings

Appendix: Rationale for and consequences of not counterbalancing response–reward mappings

In the following, we explain the rationale for not counterbalancing response–reward mappings between subjects, and clarify the consequences for the central outcome measure of the present study: MIRA values. Individual MIRA values were calculated as RT differences between reward-related (RR) and reward-unrelated (RU) incongruent no-reward trials, and thus reflect the modulation of interference by reward associations. Importantly, reward associations are inevitably confounded with inhibited response buttons: for example, if rewards are given for correct responses on the second button (as was the case for all participants in the present study), then RR stimuli (‘2’ ‘222’ ‘2222’) will require to inhibit a response on the second button, whereas RU stimuli will require to inhibit a response on either the first (‘111’, ‘1111’), third (‘3’, ‘3333’), or fourth (‘4’, ‘444’) button. To control for this confound, earlier studies (Krebs et al., 2010, 2011, 2013) used between-subjects counterbalancing, randomly assigning participants to different response–reward mappings. This ensures the interpretability of across-subjects means of outcome measures: if positive/negative average MIRA values are observed, one can justifiably conclude that interference was increased/decreased by reward associations. The downside of such a design is that it reduces the interpretability of individual differences in outcome measures: differences in individual MIRA values are not only due to individual differences in the modulation of interference by reward associations, but also due to different response–reward mappings. Between-subjects counterbalancing was therefore not suitable for the present study. Instead, the same response–reward mapping was used for all participants to keep the confound of reward associations with inhibited response buttons constant. This design ensures the interpretability of individual differences in outcome measures: a relatively high MIRA value indicates that reward associations led to a relatively strong increase—or weak decrease—of interference. At the same time, it reduces the interpretability of across-subjects means: MIRA values do not only reflect the modulation of interference by reward associations, but also the (arbitrarily chosen) response–reward mapping. In line with this, the sign of MIRA values—which was negative for most participants in the present study—does not allow conclusions on whether interference was increased or decreased by reward associations. At this point, it must be said that for the present study, the interpretability of MIRA values should be considered as limited in the aforementioned sense only under the premise that RTs were actually affected by inhibited response buttons. The validity of this premise is illustrated in Fig. 3, which shows RTs for incongruent no-reward trials as a function of inhibited response buttons: although responses on the first, third, and fourth button were equally reward-unrelated (not associated with reward), RTs differed significantly depending on whether responses were inhibited on the first or third button, t(40) = 2.152, p = 0.038, first or fourth button, t(40) = 2.376, p = 0.022, and third or fourth button, t(40) = 4.708, p < 0.001.

Fig. 3
figure3

RTs for reward-related (RR) and reward-unrelated (RU) incongruent no-reward trials (data from both Experiments combined). Average MIRA values correspond to the vertical distance between the second bar (representing the mean RT for RR trials) and the horizontal dotted line (representing the mean RT for RU trials)

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Wolff, M., Krönke, K. & Goschke, T. Trait self-control is predicted by how reward associations modulate Stroop interference. Psychological Research 80, 944–951 (2016). https://doi.org/10.1007/s00426-015-0707-4

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Keywords

  • Cognitive Control
  • Stroop Task
  • Incongruent Trial
  • Congruent Trial
  • Stroop Interference