Abstract
Contingency learning can involve learning that the identity of one stimulus in a sequence predicts the identity of the next stimulus. It remains unclear, however, whether such learning speeds responses to the next stimulus only by reducing the threshold for triggering the expected response after stimulus onset or also by preparing the expected response before stimulus onset. To distinguish between these competing accounts, we manipulated the probabilities with which each of two prime arrows (Left and Right) were followed by each of two probe arrows (Up and Down) in a prime-probe task while using force-sensitive keyboards to monitor sub-threshold finger force. Consistent with the response preparation account, two experiments revealed greater force just before probe onset on the response key corresponding to the direction in which the probe was more (versus less) likely to point (e.g., Up vs. Down). Furthermore, mirroring sequential contingency effects in behavior, this pre-probe force effect vanished after a single low-probability trial. These findings favor the response preparation account over the threshold only account. They also suggest the possibility that contingency learning in our tasks indexes trial-by-trial expectations regarding the utility of the prime for predicting the upcoming probe.
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Data availability
The preregistration, task scripts, data analysis scripts, and raw data are available on the Open Science Framework (OSF): Experiment 1 (https://osf.io/jd9ys/) and Experiment 2 (https://osf.io/eyzux/).
Notes
In these studies, contingency learning effects appear when the prime and probe appear simultaneously. Such effects, however, are stronger when the prime appears before the probe (Schmidt & De Houwer, 2016b).
The finding may alternatively be explained by the fact that the relative frequencies with which high- and medium-contingency trials appeared (50% vs. 25%) differed more than the relative frequencies with which medium- and low-frequency trials appeared (25% vs. 17%).
We mistakenly reported this partial-eta-squared value as 0.41 in our pre-registration.
To be consistent with our prior studies of the prime-probe task, we used the same key-hand mapping for all participants, rather than mapping the left and right arrow-direction keys to the left hand and the up and down arrow-direction keys to the right hand in half the participants and using the opposite key-hand mapping in the other half. Using a constant mapping does not lead to a design confound because we use the same mapping in all conditions.
We identified outliers using both correct and error RTs in the analysis of the mean ER data, not only correct RTs as in the analysis of the mean RT data. Thus, these analyses produced slightly different percentages of outliers.
In our pre-registration, we stated that we would analyze force in trials with correct responses to both the prime and the probe. An anonymous reviewer pointed out a valid concern with this approach, however. Excluding trials with an incorrect response to the probe could bias the results to show greater pre-probe force on the high-contingency response key than on the low-contingency response key. Indeed, randomly increasing pre-probe force on the high-contingency response key (e.g., due to guessing) could facilitate a correct probe response such that the trial is included in the analysis. In contrast, randomly increasing pre-probe force on the low-contingency response key could facilitate an incorrect probe response such that the trial is not included. To prevent such a bias, we analyzed pre-probe force regardless of whether the subsequent probe response was correct. We note that this change to our pre-registered analysis plan did not change any of the inferences that we describe below.
The authors thank Alexander Weigard at the University of Michigan for bringing this possibility to their attention.
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Acknowledgements
The authors thank Princess Ativie, Matthew Dunaway, Sophia Hopkins, Katherine Ni, Carlin Pendell, Chloe Saba, and Nancy Villagomez for assistance with data collection.
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This work was funded by discretionary funds to Daniel H. Weissman from the University of Michigan.
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DHW conceptualized the study. Both authors contributed to the design. Material preparation, data collection and analysis were performed by DHW. DHW wrote the first draft of the manuscript and both authors commented on all versions of the paper. All authors read and approved the final manuscript.
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Weissman, D.H., Schmidt, J.R. Proactive response preparation contributes to contingency learning: novel evidence from force-sensitive keyboards. Psychological Research (2024). https://doi.org/10.1007/s00426-024-01940-1
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DOI: https://doi.org/10.1007/s00426-024-01940-1