The present study investigated the affective modulation of conflict adaptation. In a first step, we conducted a direct replication of a previous study (Schuch & Pütz, 2018). Positive vs. negative mood state was induced by a success–failure manipulation (between-groups, N = 40 per group). In a subsequent task-switching experiment, the congruency sequence effect was assessed in task repetitions and task switches, measuring conflict adaptation within tasks and between tasks, respectively. We found conflict adaptation (averaged across task repetitions and task switches) to be enhanced in negative mood. We did not replicate our previous finding of enhanced conflict adaptation in task switches in positive mood. In a second step, we combined the replication data with the original data set, yielding a larger database with N = 80 per mood group. Using diffusion modeling, we explored the affective modulation of conflict adaptation in task repetitions. Conflict adaptation was reflected in drift rate, consistent with the idea that response conflict triggers an increase in processing selectivity, thereby attenuating the influence of the irrelevant stimulus dimension. Conflict adaptation was also reflected in boundary separation, suggesting that response conflict on the previous trial triggered an increase in response caution. The mood manipulation did not seem to affect processing selectivity (as captured by drift rate) but affected the setting of response caution (as captured by the boundary separation parameter), with faster and more error-prone responding in the negative than positive mood group. We discuss theoretical implications of these findings, and also briefly consider the affective modulations of other cognitive control measures.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Banich, M. T., Mackiewicz, K. L., Depue, B. E., Whitmer, A., Miller, G. A., & Heller, W. (2009). Cognitive control mechanisms, emotion and memory: A neural perspective with implications for psychopathology. Neuroscience and Biobehavioral Reviews, 33, 613–630.
Botvinick, M. M. (2007). Conflict monitoring and decision-making: Reconciling two perspectives on anterior cingulate function. Cognitive, Affective, and Behavioral Neuroscience, 7, 356–366.
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108, 624–652.
Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict monitoring and anterior cingulate cortex: An update. Trends in Cognitive Sciences, 8, 539–546.
Braem, S., Abrahamse, E. L., Duthoo, W., & Notebaert, W. (2014). What determines the specificity of conflict adaptation? A review, critical analysis, and proposed synthesis. Frontiers in Psychology, 5, Article 1134.
Braem, S., King, J. A., Korb, F. M., Krebs, R. M., Notebaert, W., & Egner, T. (2013). Affective modulation of cognitive control is determined by performance-contingency and mediated by ventromedial prefrontal and cingulate cortex. Journal of Neuroscience, 33(43), 16961–16970.
Braem, S., King, J. A., Korb, F. M., Krebs, R. M., Notebaert, W., & Egner, T. (2017). The role of anterior cingulate cortex in the affective evaluation of conflict. Journal of Cognitive Neuroscience, 29, 137–149.
Brown, J. W., Reynolds, J. R., & Braver, T. S. (2007). A computational model of fractionated conflict-control mechanisms in task-switching. Cognitive Psychology, 55(1), 37–85.
Chiew, K. S., & Braver, T. S. (2011). Positive affect versus reward: Emotional and motivational influences on cognitive control. Frontiers in Psychology, 2, 279.
Clore, G. L., & Huntsinger, J. R. (2007). How emotions inform judgment and regulate thought. Trends in Cognitive Sciences, 11, 393–399.
Coan, J. A., & Allen, J. J. B. (Eds.). (2007). The handbook of emotion elicitation and assessment. New York: Oxford University Press.
Davidson, R. J., Jackson, D. C., & Kalin, N. H. (2000). Emotion, plasticity, context and regulation: Perspectives from affective neuroscience. Psychological Bulletin, 126, 890–906.
De Houwer, J., Hermans, D., Rothermund, K., & Wentura, D. (2002). Affective priming of semantic categorisation responses. Cognition and Emotion, 16(5), 643–666.
Dignath, D., Eder, A. B., Steinhauser, M., & Kiesel, A. Conflict monitoring and the affective signaling hypothesis—An integrative review. Psychonomic Bulletin and Review (in press).
Dreisbach, G., & Fischer, R. (2012). The role of affect and reward in the conflict-triggered adjustment of cognitive control. Frontiers in Human Neuroscience, 6, Article 342.
Dreisbach, G., & Fischer, R. (2015). Conflicts as aversive signals for control adaptation. Current Directions in Psychological Science, 24, 255–260.
Durst, M., & Janczyk, M. (2019). Two types of backward crosstalk: Sequential modulations and evidence from the diffusion model. Acta Psychologica, 193, 132–152.
Duthoo, W., Abrahamse, E. L., Braem, S., Boehler, C. N., & Notebaert, W. (2014a). The heterogeneous world of congruency sequence effects: An update. Frontiers in Psychology, 5, 1001.
Duthoo, W., Abrahamse, E. L., Braem, S., Boehler, C. N., & Notebaert, W. (2014b). The congruency sequence effect 3.0: A critical test of conflict adaptation. PLoS One, 9(10), e110462.
Egner, T. (2007). Congruency sequence effects and cognitive control. Cognitive, Affective, and Behavioral Neuroscience, 7, 380–390.
Egner, T. (2017). Conflict adaptation: Past, present, and future of the congruency sequence effect as an index of cognitive control. In T. Egner (Ed.), The Wiley handbook of cognitive control (pp. 64–78). Oxford: Wiley-Blackwell.
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191.
Gerrards-Hesse, A., Spies, K., & Hesse, F. W. (1994). Experimental inductions of emotional states and their effectiveness: A review. British Journal of Psychology, 85, 55–78.
Goschke, T. (2000). Intentional reconfiguration and involuntary persistence in task set switching. In S. Monsell & J. Driver (Eds.), Attention and performance XVIII: Control of cognitive processes in attention, memory and language (pp. 331–335). Cambridge, MA: MIT Press.
Hübner, R., Steinhauser, M., & Lehle, C. (2010). A dual-stage two-phase model of selective attention. Psychological Review, 117, 759–784.
Inzlicht, M., Bartholow, B. D., & Hirsh, J. B. (2015). Emotional foundations of cognitive control. Trends in Cognitive Sciences, 19, 126–132.
Janczyk, M., & Lerche, V. (2019). A diffusion model analysis of the response-effect compatibility effect. Journal of Experimental Psychology: General, 148(2), 237.
Kiesel, A., Kunde, W., & Hoffmann, J. (2006). Evidence for task-specific resolution of response conflict. Psychonomic Bulletin and Review, 13, 800–806.
Kiesel, A., Steinhauser, M., Wendt, M., Falkenstein, M., Jost, K., Philipp, A. M., & Koch, I. (2010). Control and interference in task switching—A review. Psychological Bulletin, 136, 849–874.
Klauer, K. C., Musch, J., & Eder, A. B. (2005). Priming of semantic classifications: Late and response related, or earlier and more central? Psychonomic Bulletin and Review, 12(5), 897–903.
Klinger, M. R., Burton, P. C., & Pitts, G. S. (2000). Mechanisms of unconscious priming: I. Response competition, not spreading activation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(2), 441.
Krohne, H. W., Egloff, B., Kohlmann, C. W., & Tausch, A. (1996). Untersuchungen mit einer deutschen Version der “Positive and Negative Affect Schedule” (PANAS). Diagnostica, 42, 139–156.
Krohne, H. W., Pieper, M., Knoll, N., & Breimer, N. (2002). The cognitive regulation of emotions: The role of success versus failure experience and coping dispositions. Cognition and Emotion, 16, 217–243.
Kuhbandner, C., & Zehetleitner, M. (2011). Dissociable effects of valence and arousal in adaptive executive control. PLoS One, 6(12), e29287.
Lerche, V., & Voss, A. (2018). Speed–accuracy manipulations and diffusion modeling: Lack of discriminant validity of the manipulation or of the parameter estimates? Behavior Research Methods, 50(6), 2568–2585.
Lerche, V., Voss, A., & Nagler, M. (2017). How many trials are required for parameter estimation in diffusion modeling? A comparison of different optimization criteria. Behavior Research Methods, 49(2), 513–537.
Liesefeld, H. R., & Janczyk, M. (2019). Combining speed and accuracy to control for speed-accuracy trade-offs(?). Behavior Research Methods, 51, 40–60.
Martin, L. L., & Clore, G. L. (2001). Theories of mood and cognition: A user’s guidebook. Mahwah, NJ: Erlbaum.
Mitchell, R. L. C., & Phillips, L. H. (2007). The psychological, neurochemical and functional neuroanatomical mediators of the effects of positive and negative mood on executive functions. Neuropsychologia, 45, 617–629.
Notebaert, W., & Verguts, T. (2008). Cognitive control acts locally. Cognition, 106, 1071–1080.
Nummenmaa, L., & Niemi, P. (2004). Inducing affective states with success–failure manipulations: A meta-analysis. Emotion, 4, 207–214.
Pessoa, L. (2009). How do emotion and motivation direct executive control? Trends in Cognitive Sciences, 13, 160–166.
Phillips, L. H., Bull, R., Adams, E., & Fraser, L. (2002). Positive mood and executive function: Evidence from stroop and fluency tasks. Emotion, 2, 12–22.
Ratcliff, R. (1978). A theory of memory retrieval. Psychological Review, 85(2), 59.
Raven, J. C. (1965). Advanced progressive matrices: Sets I and II. London: Lewis.
Raven, J. C. (1976). Standard progressive matrices: Sets A, B, C, D, and E. Oxford: Oxford Psychologists Press.
Rogers, R. D., & Monsell, S. (1995). Costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology: General, 124, 207–231.
Schmiedek, F., Oberauer, K., Wilhelm, O., Süß, H. M., & Wittmann, W. W. (2007). Individual differences in components of reaction time distributions and their relations to working memory and intelligence. Journal of Experimental Psychology: General, 136(3), 414.
Schuch, S., & Koch, I. (2015). Mood states influence cognitive control: The case of conflict adaptation. Psychological Research, 79, 759–772.
Schuch, S., & Pütz, S. (2018). Mood state dissociates conflict adaptation within tasks and across tasks. Journal of Experimental Psychology. Learning, Memory, and Cognition, 44(9), 1487–1499.
Schuch, S., Zweerings, J., Hirsch, P., & Koch, I. (2017). Conflict adaptation in positive and negative mood: Applying a success-failure manipulation. Acta Psychologica, 176, 11–22.
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 cor-tex. Nature Reviews Neuroscience, 12, 154–167.
Ulrich, R., Schröter, H., Leuthold, H., & Birngruber, T. (2015). Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions. Cognitive Psychology, 78, 148–174.
Van Steenbergen, H. (2015). Affective modulation of cognitive control: A biobehavioral perspective. In G. Gendolla, M. Tops, & S. Koole (Eds.), Handbook of biobehavioral approaches to self-regulation (pp. 89–107). Heidelberg: Springer.
Van Steenbergen, H., Band, G. P. H., & Hommel, B. (2010). In the mood for adaptation: How affect regulates conflict-driven control. Psychological Science, 21, 1629–1634.
Van Steenbergen, H., Band, G. P. H., Hommel, B., Rombouts, S. A. R. B., & Nieuwenhuis, S. (2015). Hedonic hotspots regulate cingulate-driven adaptation to cognitive demands. Cerebral Cortex, 25, 1746–1756.
Van Steenbergen, H., Booij, L., Band, G. P. H., Hommel, B., & van der Does, A. J. W. (2012). Affective regulation of cognitive-control adjustments in remitted depressive patients after acute tryptophan depletion. Cognitive, Affective, and Behavioral Neuroscience, 12, 280–286.
Vandierendonck, A. (2017). A comparison of methods to combine speed and accuracy measures of performance: A rejoinder on the binning procedure. Behavior Research Methods, 49, 653–673.
Voss, A., Nagler, M., & Lerche, V. (2013a). Diffusion models in experimental psychology: A practical introduction. Experimental Psychology, 60, 385–402.
Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013b). Cognitive processes in associative and categorical priming: A diffusion model analysis. Journal of Experimental Psychology: General, 142(2), 536.
Voss, A., Rothermund, K., & Voss, J. (2004). Interpreting the parameters of the diffusion model: An empirical validation. Memory and Cognition, 32(7), 1206–1220.
Voss, A., & Voss, J. (2007). Fast-dm: A free program for efficient diffusion model analysis. Behavior Research Methods, 39(4), 767–775.
Voss, A., Voss, J., & Lerche, V. (2015). Assessing cognitive processes with diffusion model analyses: A tutorial based on fast-dm-30. Frontiers in Psychology, 6, 336.
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, 1063–1070.
Wendt, M., & Kiesel, A. (2008). The impact of stimulus-specific practice and task instructions on response congruency effects between tasks. Psychological Research, 72(4), 425–432.
Westermann, R., Spies, K., Stahl, G., & Hesse, F. W. (1996). Relative effectiveness and validity of mood induction procedures: A meta-analysis. European Journal of Social Psychology, 26, 557–580.
Conflict of interest
The authors declare that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.
This research/Stefanie Schuch was supported by a grant within the Priority Program (SPP 1772) from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), Grant No. SCHU 3046/1-2.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Schuch, S., Pütz, S. Mood state and conflict adaptation: an update and a diffusion model analysis. Psychological Research 85, 322–344 (2021). https://doi.org/10.1007/s00426-019-01258-3