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Psychological Research

, Volume 83, Issue 1, pp 1–12 | Cite as

Reappraising cognitive control: normal reactive adjustments following conflict processing are abolished by proactive emotion regulation

  • Qian YangEmail author
  • Wim Notebaert
  • Gilles Pourtois
Original Article
  • 140 Downloads

Abstract

The congruency sequence effect (CSE) reflected by the influence of the congruency of the previous trial on the current one translates improved cognitive control (CC). Yet, it remains debated whether reactive or proactive control processes mostly contribute to this effect. To address this question, we administered a Stroop task controlling for effects of feature repetition and contingency learning to a large group of participants, where we manipulated the frequency of incongruent trials in a block-wise fashion to induce either proactive (high-conflict frequency) or reactive (low-conflict frequency) control. Moreover, as the presentation of trial-by-trial evaluative feedback could influence control processes operating at a local level, we compared effect of evaluative vs. neutral feedback on the CSE, for each control mode separately. We tested the prediction that CSE should be influenced by conflict frequency and feedback type concurrently. Results showed that when evaluative feedback was used, the CSE was increased if conflict frequency was low, confirming that the CSE stemmed from reactive control mainly. If conflict frequency was high, a different sequence effect was observed. The use of neutral feedback abolished the modulation of the CSE by conflict frequency. Moreover, correlation results showed that reappraisal, corresponding to a proactive emotion regulation strategy, was negatively related to the CSE in this condition, suggesting that proactive control can alleviate the reactive dominance of the CSE. Altogether, these results suggest that CC is flexible, and its expression depends on the subtle balance between proactive and reactive control processes.

Notes

Acknowledgements

This work was supported by a Grant (201606990022) from the China Scholarship Council (CN) and co-funding (BOF) Grant (BOFCHN2017000101) from Ghent University awarded to Qian Yang.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Ghent University and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

426_2018_1099_MOESM1_ESM.docx (13 kb)
Supplementary material 1 (DOCX 13 KB)

References

  1. Aarts, E., Roelofs, A., & Van Turennout, M. (2008). Anticipatory activity in anterior cingulate cortex can be independent of conflict and error likelihood. Journal of Neuroscience, 28(18), 4671–4678.  https://doi.org/10.1523/JNEUROSCI.4400-07.2008.Google Scholar
  2. Aarts, K., & Pourtois, G. (2010). Anxiety not only increases, but also alters early error-monitoring functions. Cognitive, Affective, & Behavioral Neuroscience, 10(4), 479–492.  https://doi.org/10.3758/CABN.10.4.479.Google Scholar
  3. Abrahamse, E., Braem, S., Notebaert, W., & Verguts, T. (2016). Grounding cognitive control in associative learning. Psychological Bulletin, 142(7), 693.  https://doi.org/10.1037/bul0000047.Google Scholar
  4. Alexander, W. H., & Brown, J. W. (2010). Computational models of performance monitoring and cognitive control. Topics in Cognitive Science, 2(4), 658–677.  https://doi.org/10.1111/j.1756-8765.2010.01085.x.Google Scholar
  5. Alpay, G., Goerke, M., & Stürmer, B. (2009). Precueing imminent conflict does not override sequence-dependent interference adaptation. Psychological Research PRPF, 73(6), 803.  https://doi.org/10.1007/s00426-008-0196-9.Google Scholar
  6. Appelbaum, L. G., Boehler, C. N., Davis, L. A., Won, R. J., & Woldorff, M. G. (2014). The dynamics of proactive and reactive cognitive control processes in the human brain. Journal of Cognitive Neuroscience, 26(5), 1021–1038.  https://doi.org/10.1162/jocn_a_00542.Google Scholar
  7. Blais, C., & Bunge, S. (2010). Behavioral and neural evidence for item-specific performance monitoring. Journal of Cognitive Neuroscience, 22(12), 2758–2767.  https://doi.org/10.1162/jocn.2009.21365.Google Scholar
  8. Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108(3), 624.  https://doi.org/10.1037/0033-295X.108.3.624.Google Scholar
  9. Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: an update. Trends in Cognitive Sciences, 8(12), 539–546.  https://doi.org/10.1016/j.tics.2004.10.003.Google Scholar
  10. Braem, S., Verguts, T., Roggeman, C., & Notebaert, W. (2012). Reward modulates adaptations to conflict. Cognition, 125(2), 324–332.  https://doi.org/10.1016/j.cognition.2012.07.015.Google Scholar
  11. Braver, T. S. (2012). The variable nature of cognitive control: a dual mechanisms framework. Trends in Cognitive Sciences, 16(2), 106–113.  https://doi.org/10.1016/j.tics.2011.12.010.Google Scholar
  12. Braver, T. S., Cole, M. W., & Yarkoni, T. (2010). Vive les differences! Individual variation in neural mechanisms of executive control. Current Opinion in Neurobiology, 20(2), 242–250.  https://doi.org/10.1016/j.conb.2010.03.002.Google Scholar
  13. Braver, T. S., Gray, J. R., & Burgess, G. C. (2007). Explaining the many varieties of working memory variation: dual mechanisms of cognitive control. In Variation in Working Memory (pp. 76–106). Oxford: Oxford University Press.Google Scholar
  14. Braver, T. S., Paxton, J. L., Locke, H. S., & Barch, D. M. (2009). Flexible neural mechanisms of cognitive control within human prefrontal cortex. Proceedings of the National Academy of Sciences, 106(18), 7351–7356.  https://doi.org/10.1073/pnas.0808187106.Google Scholar
  15. Bugg, J. M. (2012). Dissociating levels of cognitive control: the case of Stroop interference. Current Directions in Psychological Science, 21(5), 302–309.  https://doi.org/10.1177/0963721412453586.Google Scholar
  16. Bugg, J. M., Jacoby, L. L., & Toth, J. P. (2008). Multiple levels of control in the Stroop task. Memory & Cognition, 36(8), 1484–1494.  https://doi.org/10.3758/MC.36.8.1484.Google Scholar
  17. Burgess, G. C., & Braver, T. S. (2010). Neural mechanisms of interference control in working memory: effects of interference expectancy and fluid intelligence. PloS One, 5(9), e12861.  https://doi.org/10.1371/journal.pone.0012861.Google Scholar
  18. Campbell, J. I., & Thompson, V. A. (2012). MorePower 6.0 for ANOVA with relational confidence intervals and Bayesian analysis. Behavior Research Methods, 44(4), 1255–1265.  https://doi.org/10.3758/s13428-012-0186-0.Google Scholar
  19. Correa, Á., Rao, A., & Nobre, A.C. (2009). Anticipating conflict facilitates controlled stimulus-response selection. Journal of Cognitive Neuroscience, 21(8), 1461–1472.  https://doi.org/10.1162/jocn.2009.21136.Google Scholar
  20. Diener, E., & Emmons, R. A. (1984). The independence of positive and negative affect. Journal of Personality and Social Psychology, 47(5), 1105.  https://doi.org/10.1037/0022-3514.47.5.1105.Google Scholar
  21. Dignath, D., & Eder, A. B. (2015). Stimulus conflict triggers behavioral avoidance. Cognitive, Affective, & Behavioral Neuroscience, 15(4), 822–836.  https://doi.org/10.3758/s13415-015-0355-6.Google Scholar
  22. Dreisbach, G., & Fischer, R. (2012). Conflicts as aversive signals. Brain and Cognition, 78(2), 94–98.  https://doi.org/10.1016/j.bandc.2011.12.003.Google Scholar
  23. Dreisbach, G., & Fischer, R. (2015). Conflicts as aversive signals for control adaptation. Current Directions in Psychological Science, 24(4), 255–260.  https://doi.org/10.1177/0963721415569569.Google Scholar
  24. Duthoo, W., Abrahamse, E. L., Braem, S., Boehler, C. N., & Notebaert, W. (2014). The heterogeneous world of congruency sequence effects: an update. Frontiers in Psychology, 5, 1001.  https://doi.org/10.3389/fpsyg.2014.01001.Google Scholar
  25. Duthoo, W., & Notebaert, W. (2012). Conflict adaptation: it is not what you expect. Quarterly Journal of Experimental Psychology, 65(10), 1993–2007.  https://doi.org/10.1080/17470218.2012.676655.Google Scholar
  26. Egner, T. (2011). Right ventrolateral prefrontal cortex mediates individual differences in conflict-driven cognitive control. Journal of Cognitive Neuroscience, 23(12), 3903–3913.  https://doi.org/10.1162/jocn_a_00064.Google Scholar
  27. Egner, T., Ely, S., & Grinband, J. (2010). Going, going, gone: characterizing the time-course of congruency sequence effects. Frontiers in Psychology, 1, 154.  https://doi.org/10.3389/fpsyg.2010.00154.Google Scholar
  28. Fritz, J., & Dreisbach, G. (2013). Conflicts as aversive signals: conflict priming increases negative judgments for neutral stimuli. Cognitive, Affective, & Behavioral Neuroscience, 13(2), 311–317.  https://doi.org/10.3758/s13415-012-0147-1.Google Scholar
  29. Funes, M. J., Lupiáñez, J., & Humphreys, G. (2010). Sustained vs. transient cognitive control: Evidence of a behavioral dissociation. Cognition, 114(3), 338–347.  https://doi.org/10.1016/j.cognition.2009.10.007.Google Scholar
  30. Geng, J. J. (2014). Attentional mechanisms of distractor suppression. Current Directions in Psychological Science, 23(2), 147–153.  https://doi.org/10.1177/0963721414525780.Google Scholar
  31. Gonthier, C., Braver, T. S., & Bugg, J. M. (2016). Dissociating proactive and reactive control in the Stroop task. Memory & Cognition, 44(5), 778–788.  https://doi.org/10.3758/s13421-016-0591-1.Google Scholar
  32. Gratton, G., Coles, M. G., & Donchin, E. (1992). Optimizing the use of information: Strategic control of activation of responses. Journal of Experimental Psychology: General, 121(4), 480.  https://doi.org/10.1037/0096-3445.121.4.480.Google Scholar
  33. Gross, J. J. (2002). Emotion regulation: Affective, cognitive, and social consequences. Psychophysiology, 39(3), 281–291.  https://doi.org/10.1017/S0048577201393198.Google Scholar
  34. Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348.  https://doi.org/10.1037/0022-3514.85.2.348.Google Scholar
  35. Grützmann, R., Riesel, A., Klawohn, J., Kathmann, N., & Endrass, T. (2014). Complementary modulation of N2 and CRN by conflict frequency. Psychophysiology, 51(8), 761–772.  https://doi.org/10.1111/psyp.12222.Google Scholar
  36. Harding, S. D. (1982). Psychological well-being in Great Britain: an evaluation of the Bradburn affect balance scale. Personality and Individual Differences, 3(2), 167–175.  https://doi.org/10.1016/0191-8869(82)90031-9.Google Scholar
  37. Hinault, T., Badier, J. M., Baillet, S., & Lemaire, P. (2017). The sources of sequential modulations of control processes in arithmetic strategies: A magnetoencephalography study. Journal of Cognitive Neuroscience, 29(6), 1033–1043.  https://doi.org/10.1162/jocn_a_01102.Google Scholar
  38. Hommel, B. (2004). Event files: feature binding in and across perception and action. Trends in Cognitive Sciences, 8(11), 494–500.  https://doi.org/10.1016/j.tics.2004.08.007.Google Scholar
  39. Inzlicht, M., Bartholow, B. D., & Hirsh, J. B. (2015). Emotional foundations of cognitive control. Trends in Cognitive Sciences, 19(3), 126–132.  https://doi.org/10.1016/j.tics.2015.01.004.Google Scholar
  40. Karayanidis, F., Mansfield, E. L., Galloway, K. L., Smith, J. L., Provost, A., & Heathcote, A. (2009). Anticipatory reconfiguration elicited by fully and partially informative cues that validly predict a switch in task. Cognitive, Affective, & Behavioral Neuroscience, 9(2), 202–215.  https://doi.org/10.3758/CABN.9.2.202.Google Scholar
  41. Locke, H. S., & Braver, T. S. (2008). Motivational influences on cognitive control: Behavior, brain activation, and individual differences. Cognitive, Affective, & Behavioral Neuroscience, 8(1), 99–112.  https://doi.org/10.3758/CABN.8.1.99.Google Scholar
  42. Meyer, T. J., Miller, M. L., Metzger, R. L., & Borkovec, T. D. (1990). Development and validation of the penn state worry questionnaire. Behaviour Research and Therapy, 28(6), 487–495.  https://doi.org/10.1016/0005-7967(90)90135-6.Google Scholar
  43. Mordkoff, J. T. (2012). Observation: Three reasons to avoid having half of the trials be congruent in a four-alternative forced-choice experiment on sequential modulation. Psychonomic Bulletin & Review, 19(4), 750–757.  https://doi.org/10.3758/s13423-012-0257-3.Google Scholar
  44. Notebaert, W., & Verguts, T. (2008). Cognitive control acts locally. Cognition, 106(2), 1071–1080.  https://doi.org/10.1016/j.cognition.2007.04.011.Google Scholar
  45. Paxton, J. L., Barch, D. M., Racine, C. A., & Braver, T. S. (2008). Cognitive control, goal maintenance, and prefrontal function in healthy aging. Cerebral Cortex, 18(5), 1010–1028.  https://doi.org/10.1093/cercor/bhm135.Google Scholar
  46. Rigoni, D., Braem, S., Pourtois, G., & Brass, M. (2016). Fake feedback on pain tolerance impacts proactive versus reactive control strategies. Consciousness and Cognition, 42, 366–373.  https://doi.org/10.1016/j.concog.2016.04.015.Google Scholar
  47. Rossi, V., & Pourtois, G. (2012). Transient state-dependent fluctuations in anxiety measured using STAI, POMS, PANAS or VAS: a comparative review. Anxiety, Stress & Coping, 25(6), 603–645.  https://doi.org/10.1080/10615806.2011.582948.Google Scholar
  48. Scherbaum, S., Fischer, R., Dshemuchadse, M., & Goschke, T. (2011). The dynamics of cognitive control: evidence for within-trial conflict adaptation from frequency-tagged EEG. Psychophysiology, 48(5), 591–600.  https://doi.org/10.1080/17470218.2012.685080.Google Scholar
  49. Schmidt, J. R., & Weissman, D. H. (2014). Congruency sequence effects without feature integration or contingency learning confounds. PLoS One, 9(7), e102337.  https://doi.org/10.1371/journal.pone.0102337.Google Scholar
  50. Schouppe, N., Braem, S., De Houwer, J., Silvetti, M., Verguts, T., Ridderinkhof, K. R., & Notebaert, W. (2015). No pain, no gain: the affective valence of congruency conditions changes following a successful response. Cognitive, Affective, & Behavioral Neuroscience, 15(1), 251–261.  https://doi.org/10.3758/s13415-014-0318-3.Google Scholar
  51. Schouppe, N., De Houwer, J., Ridderinkhof, R., K., & Notebaert, W. (2012). Conflict: Run! Reduced Stroop interference with avoidance responses. Quarterly Journal of Experimental Psychology, 65(6), 1052–1058.  https://doi.org/10.1080/17470218.2012.685080.Google Scholar
  52. Shackman, A. J., Salomons, T. V., Slagter, H. A., Fox, A. S., Winter, J. J., & Davidson, R. J. (2011). The integration of negative affect, pain and cognitive control in the cingulate cortex. Nature Reviews Neuroscience, 12(3), 154.  https://doi.org/10.1038/nrn2994.Google Scholar
  53. Shenhav, A., Cohen, J. D., & Botvinick, M. M. (2016). Dorsal anterior cingulate cortex and the value of control. Nature Neuroscience, 19(10), 1286.  https://doi.org/10.1038/nn.4384.Google Scholar
  54. Soutschek, A., Strobach, T., & Schubert, T. (2014). Motivational and cognitive determinants of control during conflict processing. Cognition and Emotion, 28(6), 1076–1089.  https://doi.org/10.1080/02699931.2013.870134.Google Scholar
  55. Suzuki, K., & Shinoda, H. (2015). Transition from reactive control to proactive control across conflict adaptation: an sLORETA study. Brain and Cognition, 100, 7–14.  https://doi.org/10.1016/j.bandc.2015.09.001.Google Scholar
  56. Torres-Quesada, M., Funes, M. J., & Lupiáñez, J. (2013). Dissociating proportion congruent and conflict adaptation effects in a Simon–Stroop procedure. Acta Psychologica, 142(2), 203–210.  https://doi.org/10.1016/j.actpsy.2012.11.015.Google Scholar
  57. Van Steenbergen, H., Band, G. P., & Hommel, B. (2009). Reward counteracts conflict adaptation: evidence for a role of affect in executive control. Psychological Science, 20(12), 1473–1477.  https://doi.org/10.1111/j.1467-9280.2009.02470.x.Google Scholar
  58. Van Steenbergen, H., Band, G. P., & Hommel, B. (2012). Reward valence modulates conflict-driven attentional adaptation: electrophysiological evidence. Biological Psychology, 90(3), 234–241.  https://doi.org/10.1016/j.biopsycho.2012.03.018.Google Scholar
  59. Van Steenbergen, H., Band, G. P., & Hommel, B. (2015). Does conflict help or hurt cognitive control? Initial evidence for an inverted U-shape relationship between perceived task difficulty and conflict adaptation. Frontiers in Psychology, 6, 974.  https://doi.org/10.3389/fpsyg.2015.00974.Google Scholar
  60. Vocat, R., Pourtois, G., & Vuilleumier, P. (2008). Unavoidable errors: A spatio-temporal analysis of time-course and neural sources of evoked potentials associated with error processing in a speeded task. Neuropsychologia, 46(10), 2545–2555.  https://doi.org/10.1016/j.neuropsychologia.2008.04.006.Google Scholar
  61. Warr, P. B., Barter, J., & Brownbridge, G. (1983). On the independence of positive and negative affect. Journal of Personality and Social Psychology, 44(3), 644–651.  https://doi.org/10.1037/0022-3514.44.3.644.Google Scholar
  62. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063.  https://doi.org/10.1037/0022-3514.54.6.1063.Google Scholar
  63. Weissman, D. H., Jiang, J., & Egner, T. (2014). Determinants of congruency sequence effects without learning and memory confounds. Journal of Experimental Psychology: Human Perception and Performance, 40(5), 2022.  https://doi.org/10.1037/a0037454.
  64. West, R., Choi, P., & Travers, S. (2010). The influence of negative affect on the neural correlates of cognitive control. International Journal of Psychophysiology, 76(2), 107–117.  https://doi.org/10.1016/j.ijpsycho.2010.03.002.Google Scholar
  65. Yang, Q., & Pourtois, G. (2018). Conflict-driven adaptive control is enhanced by integral negative emotion on a short time scale. Cognition and Emotion.  https://doi.org/10.1080/02699931.2018.1434132.Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Cognitive and Affective Psychophysiology Laboratory, Department of Experimental Clinical and Health PsychologyGhent UniversityGhentBelgium
  2. 2.Department of Experimental Psychology and Health PsychologyGhent UniversityGhentBelgium

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