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“Optimal suppression” as a solution to the paradoxical cost of multitasking: examination of suppression specificity in task switching

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Abstract

Switching between tasks necessitates maintaining tasks in high readiness, yet readiness creates paradoxical interference from these tasks when they are not currently required. “Optimal suppression”, which targets just the interfering information, provides a partial solution to this paradox. By examining the carryover of suppression of a competitor stimulus–response (S–R) set from Trial N − 1 to Trial N, Meiran, Hsieh  and colleagues (Meiran  et al., J Exp Psychol Learn mem cognit 36:992–1002, 2010; Cognit Affect Behav Neurosci 11:292–308, 2011, and Hsieh et al., Acta Psychol 141:316–321, 2012) found that only the competing stimulus–response (S–R) set of rules is suppressed. Specifically, they found that a competitor S–R set in Trial N − 1 incurs cost when it becomes the relevant set in Trial N [competitor becomes relevant (CbR)]. Extending this logic, we predicted performance benefit when the competitor S–R set in Trial N − 1 remains the competitor S–R set in Trial N [competitor remains competitor (CrC)]. Here, we examined the question of whether what is being suppressed when encountering a response conflict is the entire S–R set of rules (e.g., “IF pink PRESS right”, and “IF blue PRESS left”) or an even more specific representation, namely, the currently interfering S–R rule (e.g., just “IF blue PRESS left”). We show that both CbR and CrC interact with Response (i.e., left or right key), suggesting that the system can recognize the exact source of interference (the competing S–R rule), and inhibit only this source.

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Notes

  1. It is important to note that we chose the term ‘carryover’ to communicate the fact that we do not commit ourselves to a decay position where the passage of time is critical. Alternatively, a task control representation is tagged in an episodic trace as one causing interferences, such that its subsequent retrieval would be impaired. According to this position, time per se is unimportant, and what is critical is the ease in which the tagged episode is retrieved. In fact, a temporal distinctiveness analysis (Horoufchin, Philipp, & Koch, 2011) favored episodic retrieval over decaying inhibition, by showing that the paradoxically maladaptive pervasiveness of suppression was increased with temporal distinctiveness between the previous and the current episode (see Hsieh et al. 2012). For that reason, we also use the term ‘suppression’, rather than ‘inhibition’, to indicate a cognitive control mechanism without committing to an inhibitory account.

  2. S–R sets and S–R rules form a hierarchical structure, such that S–R sets are an assembly of two S–R rules. Yet, only one S–R rule of each S–R set is present in a given trial. Therefore, if, on a given trial, an S–R rule elicits a response tendency that is incompatible with the relevant response, the S–R rule would be an interfering S–R rule, and, as a result from the hierarchical structure, the S–R set would be a competing S–R set.

  3. It is important to note that the compatibility of an S–R set is determined by the compatibility of the relevant and irrelevant S–R rules. Specifically, when the irrelevant S–R rule elicits a response that is incompatible with the response that is elicited by the relevant S–R rule, the irrelevant S–R rule is an interfering S–R rule and the S–R set to which the irrelevant S–R rule belongs is a competitor S–R set. However, when the S–R rule is not interfering, this S–R rule and this S–R set are both compatible.

  4. While Sudevan and Taylor, and many others, used paradigms with only two S–R sets, later works used paradigms with K (K = 3 or 4, usually) S–R sets, as we did here. In this case, the Congruency variable does not have only two levels (congruent, incongruent, with 0 or 1 competitor S–R sets), but, instead, is replaced by a variable representing the number of competitor S–R sets, ranging from zero (congruent) to K – 1. From here on, we use the terms “congruent/incongruent” to identify whether there were no competitor rules on a trial (i.e., a congruent trial), or one or more competitors (i.e., an incongruent trial).

  5. In the original work, and publication following it, Meiran et al. (2010) termed this effect "competitor rule suppression". To avoid confusion, we mention here that what Meiran et al. described as “competitor rule” is described here, using our terminology, as “competitor S–R set”. Thus, CbR should actually be termed “competitor S–R set suppression”. Moreover, in what comes next, we introduce another effect that results from set suppression. Therefore, we decided from hereon to give this phenomenon a more theoretically neutral term: CbR, which stands for competitor becomes relevant.

  6. Note that although on a given trial, if an S–R rule is interfering, the S–R set must also be competing. This is due to the fact that the S–R rule is a part of the S–R set, i.e., the hierarchical structure mentioned above. Thus, in two consecutive trials, when the competitor set from Trial N − 1 appears in Trial N (as either a relevant set in CbR or as a competitor in CrC), its competing aspect from Trial N − 1 (i.e., the interfering S–R rule in Trial N − 1) may not appear in Trial N.

  7. In Katzir, Ori, Eyal, & Meiran (2015), the research question focused on emotion effects, and therefore the exclusion criteria related to whether participants followed instructions in the emotion manipulation. Because the current investigation did not include emotion, we included also participants who were previously excluded. We, therefore, excluded only one participant from Experiment 1, who performed with 49% errors.

  8. In a model selection process, BF10 is calculated for all possible models composed out of the combinations between main effects and interactions of the independent variables. For example, in a Bayesian ANOVA that includes two independent variables A and B, there are five possible models: three models that include only main effects (1st: Only A; 2nd: Only B; 3rd: A + B), another model that also includes the interaction (4th: A + B + AB), and the null model. The analysis gives a BF10 for each model separately, and then we select the model with the best fit to the data (see Maxwell & Delaney, 2003, for an equivalent treatment of "standard" ANOVA). This selection is based on the QueryBF of the comparison between the models, namely the ratio between the BF10 of the best model and the next best model. Moreover, to establish the existence of a main effect, we use the BF10 of this effect. However, to establish the existence of an interaction, we use the best fitting model that includes the interaction and compare it to the best fitting model that includes all of the effects present in the former model excluding the interaction (Rouder, Morey, Speckman, & Province, 2012). Thus, a BFcomparison > 1 would indicate evidence favoring the interaction.

  9. The same applies to the CrC analysis, only there the CrC effect is present when comparing Fig. 4b-I to -III (i.e., S–R rule repetition comparison) and not when comparing Fig. 4b-II to b-IV (i.e., S–R rule switch comparison).

  10. We thank Pierre Jolicoeur for raising this possibility (personal communication, May 2017).

  11. Note that in their work about goal shielding, S–R set representations are referred to as task sets (TS), whereas S–R rule representations are referred to as S–R mappings (e.g., Dreisbach & Haider, 2009).

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Acknowledgements

Funding: This study was funded by a research grant from the Bi-National USA–Israel Science Foundation (Grant number 2015-186) to Nachshon Meiran, Michael W. Cole, and Todd S. Braver. Additionally, part of the work on this paper was done while the first author was a post-doc in Wilhelm Hofmann’s group at the University of Cologne. This stay was funded by the Leo Spitzer research grant from the University of Cologne awarded to Wilhelm Hofmann.

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  1. Department of Psychology, University of Cologne, Cologne, Germany

    Maayan Katzir

  2. Department of Psychology, Ben-Gurion University of the Negev, Beer-sheva, Israel

    Maayan Katzir, Bnaya Ori & Nachshon Meiran

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  1. Maayan Katzir
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Katzir, M., Ori, B. & Meiran, N. “Optimal suppression” as a solution to the paradoxical cost of multitasking: examination of suppression specificity in task switching. Psychological Research 82, 24–39 (2018). https://doi.org/10.1007/s00426-017-0930-2

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