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Execution-based and verbal code-based stimulus–response associations: proportion manipulations reveal conflict adaptation processes in item-specific priming

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Abstract

Stimulus–response (S–R) associations consist of two independent components: Stimulus–classification (S–C) and stimulus–action (S–A) associations. Here, we examined whether these S–C and S–A associations were modulated by cognitive control operations. In two item-specific priming experiments, we systematically manipulated the proportion of trials in which item-specific S–C and/or S–A mappings repeated or switched between the single encoding (prime) and single retrieval (probe) instance of each stimulus (i.e., each stimulus appeared only twice). Thus, we assessed the influence of a list-level proportion switch manipulation on the strength of item-specific S–C and S–A associations. Participants responded slower and committed more errors when item-specific S–C or S–A mappings switched rather than repeated between prime and probe (i.e., S–C/S–A switch effects). S–C switch effects were larger when S–C repetitions rather than switches were frequent on the list-level. Similarly, S–A switch effects were modulated by S–A switch proportion. Most importantly, our findings rule out contingency learning and temporal learning as explanations of the observed results and point towards a conflict adaptation mechanism that selectively adapts the encoding and/or retrieval for each S–R component. Finally, we outline how cognitive control over S–R associations operates in the context of item-specific priming.

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Data availability

The data of the reported experiments as well as experiment files and syntaxes are available via the Open Science Framework: https://osf.io/t752u/; https://doi.org/10.17605/OSF.IO/T752U.

Notes

  1. For the sake of simplicity, we will for now speak of a cognitive control process without implying either of the theoretical accounts for proportion congruency effects. In the “General discussion” section we will discuss in detail which theory best accounts for our findings.

  2. This must not be confused with assessments of item-specific proportion congruency effects where stimuli are presented multiple times and the proportion of, for instance, congruent versus incongruent trials for each stimulus is manipulated (e.g., stimulus A 75% congruent, stimulus B 25% congruent). In the present experiments, each stimulus was only probed once. The item-specific manipulation we refer to is only related to whether the S–C and S–A mapping for a stimulus repeated or switched between its single prime and probe instance. As each stimulus was only associated with either a single item-specific switch or repetition in S–C and S–A mapping, the respective S–C/S–A switch proportions associated with a single stimulus are always either 0% or 100%. Framed differently, each individual stimulus was contingency unbiased. Repetitions/switches in S–C and S–A mapping occurred for the first and only time during the single probe instance of each stimulus. Thus, item-specific learning of the frequency of switches in S–C and S–A mapping could not occur.

  3. Please note that the prime and probe instances of specific stimuli never occurred on two consecutive trials. Our S–C switch effects, therefore, differ from task switching effects that are observed from trial N-1 and trial N (e.g., Kiesel et al. 2010, for a review). In the present item-specific paradigm, task switching effects are observed independent from the item-specific S–C and S–A switch effects (see Pfeuffer et al. 2017).

  4. CR = classification repetition, CS = classification switch; AR = action repetition, AS = action switch.

  5. Please note that memory recall performance is not informative about whether S-R switch proportion affected S-R encoding and/or retrieval processes, as probe trials occurred in between prime and memory recall trials. Probe S-R repetitions should have supported recall, whereas probe S-R switches should have obstructed it. Thus, it cannot be determined whether differences in recall performance are to be attributed to differences in prime encoding or the respective probe S-R switch condition. Memory recall data can therefore only be used to assess whether participants attended to verbal codes.

  6. Bayesian analyses We observed interactions between classification and proportion switch group, but we did not observe three-way interactions between prime type, classification, and proportion switch group or prime type, action, and proportion switch group. This null effect is theoretically relevant as it might suggest that execution-based and verbal code-based S–C and S–A associations did not differ in terms of how they were influenced by processes of cognitive control. To ascertain the theoretically relevant null effects of these three-way interactions, we conducted additional Bayesian Repeated Measures ANOVAs with default prior scales using JASP (version 0.8.0.0, Love et al. 2015; see Rouder et al. 2009, 2017, for information on Bayesian statistics) on RTs and error rates. To compute the Bayes factors for these three-way interactions, we excluded the influence of the respective main effects or two-way interactions of the factors included in the three-way interaction. We were thus able to assess the evidence in favor of the null hypotheses that the interactions of classification and proportion switch group and action and proportion switch group were not modulated by prime type. The Bayes factor (\({\text{BF}}_{01}\)) indexes how strongly the data is in favor of the null hypothesis. As influences of other effects are already excluded, the reported Bayes factors can directly be interpreted as the likelihood of null effects for the respective three-way interactions. Bayes factors between 1 and 3 are considered anecdotal evidence for the null hypothesis (see Jarosz and Wiley 2014). Bayes factors between 3 and 10 are considered substantial evidence for the null hypothesis and Bayes factors between 10 and 30 are considered strong evidence in favor of the null hypothesis.

  7. As an alternative to the assumed modulation of the rate of evidence accumulation of the instance retrieval route, one might suggest that instead the response threshold could have been affected. An overall modulation of the response threshold for both response options (though selectively for actions and classifications) with a decreased response threshold when repetitions were frequent and an increased response threshold when switches were frequent, could not account for the observed pattern of results. Responses on S–C/S–A repetition trials would be speeded when S–C/S–A repetitions are frequent. However, responses on S–C/S–A switch trials would be further slowed down when S–C/S–A switches are frequent. Thus, we would not have observed reduced S–C/S–A switch effects for frequent switches as compared to frequent repetitions in the respective mappings. One would have to assume that participants selectively and item-specifically decreased the response threshold for the action/classification response given in the prime when repetitions were frequent and selectively and item-specifically decreased the response threshold for the opposite action/classification when switches were frequent. As the respective response thresholds that would need to be decreased depend on the action/classification associated with a stimulus during its prime trial and thus change item-specifically, it is hard to fathom how such a mechanism would work and a much more complex model would have to be assumed to accommodate it.

  8. Alternatively, it might also be that only either frequent repetitions or frequent switches of S–R mapping affect the rate of evidence accumulation.

  9. Note that for the present model, it is irrelevant whether the rate of evidence accumulation of the instance retrieval route (i.e., item-specific S–R associations) is influenced by cognitive control processes at encoding or retrieval.

  10. We additionally included RT Ntile as a predictor in the regression, as the overall RT level might also have affected the size of the observed S–C and S–A effects. At least for S–C switch effects, percentile analyses of data we previously collected within the same paradigm typically showed an increase of S–C switch effects with percentile.

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Acknowledgements

This research was supported by a grant of the Deutsche Forschungsgemeinschaft [KI1388/5-1, Andrea Kiesel] and a Grant of the Agence Nationale de la Recherche [SRA ANR-13-FRAL-0007-01, Karolina Moutsopoulou].

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Authors and Affiliations

  1. Cognition, Action, and Sustainability Unit, Department of Psychology, Albert-Ludwigs-University of Freiburg, Engelbergerstrasse 41, 79085, Freiburg, Germany

    Christina U. Pfeuffer & Andrea Kiesel

  2. Université Paris Descartes, Sorbonne Paris Cité, 75006, Paris, France

    Karolina Moutsopoulou & Florian Waszak

  3. Centre National de la Recherche Scientifique, Laboratoire Psychologie de la Perception, UMR 8242, 75006, Paris, France

    Karolina Moutsopoulou & Florian Waszak

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  1. Christina U. Pfeuffer
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  2. Karolina Moutsopoulou
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Correspondence to Christina U. Pfeuffer.

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Appendices

Appendix 1

Experiment 1: Memory recall analysis

Overall, participants recalled 71.6% of the verbally coded prime action mappings and 75.6% of the verbally coded prime classification mappings. One sample t-tests showed that participants´ recall performance for actions was significantly above chance (50%) for both the group with frequent switches, t(36) = 12.60, p < .001, d = 2.02, and the group with frequent repetitions, t(38) = 13.98, p < .001, d = 2.30. Furthermore, performance on classification recall trials was significantly above chance (50%) both when mappings frequently switched, t(36) = 12.55, p < .001, d = 2.01, and when they frequently repeated, t(38) = 12.11, p < .001, d = 1.99.

A 2 × 2 mixed-design ANOVA with the between-subject factor proportion switch group and the within-subject factor mapping type (classification vs. action) showed that participants recalled significantly more classification mappings than action mappings, F(1,74)=12.57, p = .001, η2p  = .15. Memory recall accuracy did not significantly differ between the two proportion switch groups, F < 1, and mapping type and proportion switch group did not significantly interact, F < 1.

Experiment 2: Memory recall analysis

Participants recalled 72.9% of verbally coded action mappings and 76.9% of classification mappings. One sample t-tests showed that participants´ recall performance was significantly above chance (50%) for all four proportion switch groups for both actions, t(29) ≤ 10.01, p ≥ .001, d ≤ 1.83, and classifications, t(29) ≤ 8.75, p ≥ .001, d ≤ 1.60.

A 2 × 2 × 2 mixed-design ANOVA with the between-subject factors classification switch proportion and action switch proportion and the with-subject factor mapping type showed that participants recalled significantly more classification mappings than action mappings, F(1,116)=14.25, p < .001, η2p  = .11. Furthermore, mapping type significantly interacted with both classification switch proportion, F(1,116)=6.14, p = .015, η2p  = .05, and action switch proportion, F(1,116)=6.14, p = .015, η2p  = .05. Participants only recalled significantly more classification than action mappings when classification repetitions were frequent, t(59) = 4.24, p < .001, d = 0.55, but not when classification switches were frequent, t(59) = 0.91, p = .366, d = 0.12. Conversely, participants recalled significantly more classification mappings than action mappings when action switches were frequent, t(59) = 4.79, p < .001, d = 0.62, but not when action repetitions were frequent, t(59) = 0.82, p = .415, d = 0.11. Moreover, the main effect of classification switch proportion was significant, F(1,116)=6.71, p = .011, η2p  = .06, with participants recalling more mappings when classifications frequently repeated rather than switched. All other effects failed to reach significance, Fs ≤ 1.82, ps ≥ .180, η2p  ≤ .02.

Appendix 2

Probe RT analyses corrected for trial transitions and RT level

With the present experiments, effects of trial transitions (e.g., task repetitions/switches between trial N-1 and trial N) could not be controlled for. Especially, trial transitions from frequent (N-1) to frequent (N) conditions occurred more often than, for instance, trial transitions from infrequent (N-1) to infrequent (N) conditions. That is, both probe trials with infrequent and frequent item-specific S–C and S–A mapping combinations were more likely to be preceded by the probe trial of another object with a frequent item-specific S–C and S–A mapping combination. Conversely, probe trials with one specific infrequent item-specific S–C and S–A mapping combination were very unlikely to follow one another. As some accounts of proportion congruency effects suggest that cognitive control might be especially driven by recent events (e.g., King et al. 2012), such trial transitions might have affected the pattern of results in the present study and might partly account for the observed findings.

To account for the influence of trial transitions on item-specific S–C and S–A effects in probe trials, we used a method suggested by Notebaert and Verguts (2007; adapted from a method developed by Kliegl et al. 2004, in the context of word reading). We first conducted regression analyses with the predictors N-1 frequency condition (frequent vs. infrequent condition depending on the proportion switch group), N-1 classification switch condition (item-specific CR vs. CS), N-1 action switch condition (item-specific AR vs. AS), N-1 task transition (repetition vs. switch, e.g., size → size vs. size → mechanism), N-1 task cue transition (repetition vs. switch. e.g., “K + G” → “K + G” vs. “K + G” → “N + M”), and RT NtileFootnote 10 (1–5) and the criterion probe RT (probe 2–4) separately for each participant and the two prime types. Subsequently, we used the residuals of this regression as the dependent variable of a 2 × 2 × 2 × 2 × 2 mixed-design ANOVA with the between-subject factors classification switch proportion and action switch proportion and the within-subject factors prime type, classification, and action. This allowed us to re-conduct the RT analysis while excluding systematic effects of trial transitions and RT level.

We again found a main effect of classification, F(1,116) = 134.25, p < .001, η2p  = .54. RT residuals for classification switches were larger than for classification repetitions. Furthermore, classification again significantly interacted with prime type, F(1,116) = 4.87, p = .029, η2p  = .04. Classification switch effects were larger in executed, t(119) = 10.82, p < .001, d = 0.99, as compared to verbally coded blocks, t(119) = 7.18, p < .001, d = 0.65. The main effect of action reached significance, F(1,116) = 17.02, p < .001, η2p  = .13. RT residuals for action switches were larger than for action repetitions. The interaction of action and prime type showed a non-significant trend, F(1,116) = 3.15, p = .078, η2p  = .03.

Importantly, classification significantly interacted with classification switch proportion, F(1,116) = 19.49, p < .001, η2p  = .14. Classification switch effects were significantly stronger when classification repetitions were frequent, t(59) = 12.20, p < .001, d = 1.57, rather than when classification switches were frequent, t(59) = 5.36, p < .001, d = 0.69. The interaction of action and action switch proportion showed a non-significant trend, F(1,116) = 3.44, p = .066, η2p  = .03. Classification and action switch proportion, F < 1, \({\text{BF}}_{01}\) = 7.04, and action and classification switch proportion, F < 1, \({\text{BF}}_{01}\) = 6.97, did not interact.

The three-way interactions between prime type, classification, and classification switch proportion, F < 1, \({\text{BF}}_{01}\) = 5.01, as well as between prime type, classification, and action switch proportion, F < 1, \({\text{BF}}_{01}\) = 6.17, did not reach significance. Similarly, the three-way interactions between prime type, action, and action switch proportion, F < 1, \({\text{BF}}_{01}\) = 8.14, and between prime type, action, and classification switch proportion, F(1,116) = 1.01, p = .318, η2p  = .01, \({\text{BF}}_{01}\) = 4.04, were not significant.

Additionally, the factors classification and action again significantly interacted, F(1,116) = 7.34, p = .008, η2p  = .06, with a significant effect of action emerging for item-specific classification repetitions, t(119) = 5.02, p < .001, d = 0.46, but not classification switches, t(119) = 1.37, p = .174, d = 0.12. The three-way interaction of classification, action, classification switch proportion only approached significance, F(1,116) = 3.10, p = .081, η2p  = .03.

In contrast to the previous RT analyses, the three-way interaction between prime type, classification, and action now reached significance, F(1,116) = 4.34, p = .040, η2p  = .04. Classification and action significantly interacted in executed, F(1,119) = 11.46, p = .001, η2p  = .09, but not verbally coded blocks, F(1,119) < 1. All other effects failed to reach significance, Fs ≤ 2.21, ps ≥ .139, η2p  ≤ .02.

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Pfeuffer, C.U., Moutsopoulou, K., Waszak, F. et al. Execution-based and verbal code-based stimulus–response associations: proportion manipulations reveal conflict adaptation processes in item-specific priming. Psychological Research 84, 2172–2195 (2020). https://doi.org/10.1007/s00426-019-01220-3

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