Stefanie Schuch

A prominent feature of cognitive control is that its deployment is regulated depending on the environmental circumstances. Control upregulation has been widely documented in response-conflict paradigms where congruency effects are reduced both following incongruent trials, and in blocks where incongruent trials are the majority. In two pre-registered task-switching experiments, we investigated whether similar flexible mechanisms are also available when dealing with stimulus-based task conflict. Building up on previous Stroop studies, task conflict was measured as the difference in performance between bivalent congruent and univalent trials, which we name the “valency effect.” If cognitive control is upregulated analogously to what observed with response conflict, valency effects should be reduced following bivalent trials and in majority-bivalent blocks. Furthermore, as cognitive control upregulation has been proposed to be task specific, we assessed whether switching to a new task eliminates the expected modulations of task. The results broadly matched our predictions. First, we observed a reduction of the valency effect following bivalent trials similar to the well-known congruency sequence effect, demonstrating similar patterns of flexible control adjustment to task and response conflict. This valency sequence effect was limited to task repetitions, indicating that local control adjustments are task specific. Furthermore, task conflict was reduced in majority-bivalent blocks, similar to the proportion-congruency effect. This finding extends previous Stroop studies suggesting that control is recruited proactively when dealing with stimulus-based task. The proportion valency effect was limited to task-switch trials, leaving open the question on the precise mechanisms behind sustained control adjustments.

Investigating the interface between motivation and cognitive control, we conducted two task switching experiments (N = 96 each) with reward manipulation where participants switched between three different tasks. We measured N-2 task repetition costs, which denote the performance decrement in N-2 task repetition sequences (ABA) relative to N-2 task switch sequences (CBA), and which are presumed to be a marker of inhibitory control in task switching. Participants in the reward group received performance-contingent reward in the second phase of each experiment, and in the second experiment they were additionally penalized for errors. Reward thresholds were determined individually based on participants’ performance during the first phase of each experiment. Participants in the control group did not receive any reward. The reward manipulation led to faster performance in the reward group relative to the control group. Diffusion modeling revealed that the reward manipulation induced an increase in drift rate parameter, consistent with dopamine-based enhancement of attentional focus under reward. Contrary to our expectations, no robust evidence for a reward-based modulation of N-2 repetition costs was found across the two experiments. N-2 task repetition costs were small in both experiments, and possibly, a larger amount of inhibitory control is needed in order to obtain empirical evidence for a reward-related modulation thereof. However, additional analyses suggested that reward may not interact with inhibitory control on the task level at all.

Evidence-accumulation models are a useful tool for investigating the cognitive processes that give rise to behavioural data patterns in reaction times (RTs) and error rates. In their simplest form, evidence-accumulation models include three parameters: The average rate of evidence accumulation over time (drift rate) and the amount of evidence that needs to be accumulated before a response becomes selected (boundary) both characterise the response-selection process; a third parameter summarises all processes before and after the response-selection process (non-decision time). Researchers often compute experimental effects as simple difference scores between two within-subject conditions and such difference scores can also be computed on model parameters. In the present paper, we report spurious correlations between such model parameter difference scores, both in empirical data and in computer simulations. The most pronounced spurious effect is a negative correlation between boundary difference and non-decision difference, which amounts to r = – .70 or larger. In the simulations, we only observed this spurious negative correlation when either (a) there was no true difference in model parameters between simulated experimental conditions, or (b) only drift rate was manipulated between simulated experimental conditions; when a true difference existed in boundary separation, non-decision time, or all three main parameters, the correlation disappeared. We suggest that care should be taken when using evidence-accumulation model difference scores for correlational approaches because the parameter difference scores can correlate in the absence of any true inter-individual differences at the population level.

A prominent behavioral marker of inhibition in task switching is the “N-2 repetition cost” that denotes the decrement in performance in task sequences with an N-2 task repetition (ABA), relative to task sequences without an N-2 task repetition (CBA). Recently, it has been critized that N-2 repetition costs at least partially reflect interference between task episodes, rather than persisting inhibition, raising doubts about the interpretation of N-2 repetition costs as a measure of inhibition. Here, we aim to generalize these conclusions in two ways. First, we define episodic effects in task switching with respect to the last episode of the same task, which might have occurred several trials back (e.g., in trial N-2, N-3, etc.). Second, we distinguish between episodic interference caused by task-relevant and task-irrelevant features. We present a re-analysis of previously published data, and a new pre-registered experiment, where we manipulated the degree of interference between task episodes in three levels (episodic match of both task-relevant and task-irrelevant features, episodic match of only task-relevant features, episodic mismatch of both kinds of features). We observed empirical evidence for both cognitive mechansims: Episodic interference was indicated by a main effect of episodic condition; task-level inhibition was indicated by N-2 repetition costs, and by a performance benefit with increasing task lag in an exploratory task-lag analysis. We did not observe any significant modulation of N-2 repetition costs by episodic condition, suggesting that if there was such a modulation, this effect appears to be smaller than the individual contributions of episodic interference and inhibition to task performance.

This study examined the reliability (retest and split-half) of four common behavioral measures of cognitive control. In Experiment 1 (N = 96), we examined N – 2 task repetition costs as a marker of task-level inhibition, and the cue-stimulus interval (CSI) effect as a marker of time-based task preparation. In Experiment 2 (N = 48), we examined a Stroop-like face-name interference effect as a measure of distractor interference control, and the sequential congruency effect (“conflict adaptation effect”) as a measure of conflict-triggered adaptation of cognitive control. In both experiments, the measures were assessed in two sessions on the same day, separated by a 10 min-long unrelated filler task. We observed substantial experimental effects with medium to large effect sizes. At the same time, split-half reliabilities were moderate, and retest reliabilities were poor, for most measures, except for the CSI effect. Retest reliability of the Stroop-like effect was improved when considering only trials preceded by congruent trials. Together, the data suggest that these cognitive control measures are well suited for assessing group-level effects of cognitive control. Yet, except for the CSI effect, these measures do not seem suitable for reliably assessing interindividual differences in the strength of cognitive control, and therefore are not suited for correlational approaches. We discuss possible reasons for the discrepancy between robustness at the group level and reliability at the level of interindividual differences.

Evidence-accumulation models are a useful tool for investigating the cognitive processes that give rise to behavioural data patterns in reaction times (RTs) and error rates. In their simplest form, evidence-accumulation models include three parameters: The average rate of evidence accumulation over time (drift rate) and the amount of evidence that needs to be accumulated before a response becomes selected (boundary) both characterise the response-selection process; a third parameter summarises all processes before and after the response-selection process (non-decision time). Researchers often compute experimental effects as simple difference scores between two within-subject conditions and such difference scores can also be computed on model parameters. In the present paper, we report spurious correlations between such model parameter difference scores, both in empirical data and in computer simulations. The most pronounced spurious effect is a negative correlation between boundary difference and non-decision difference, which amounts to r = –.70 or larger. In the simulations, we only observed this spurious negative correlation when either (a) there was no true difference in model parameters between simulated experimental conditions, or (b) only drift rate was manipulated between simulated experimental conditions; when a true difference existed in boundary separation, non-decision time, or all three main parameters, the correlation disappeared. We suggest that care should be taken when using evidence-accumulation model difference scores for correlational approaches, because the parameter difference scores can correlate in the absence of any true inter-individual differences at the population level.

Studies of switching between tasks and studies of error commission have both provided solid behavioral measures of executive control. Nonetheless, a gap remains between these strands of research. In three experiments we sought to reduce this gap by assessing the impact of task errors on N-2 repetition costs, an effect supposedly related to task-set inhibition. Based on previous literature reporting a task-switch benefit following task errors, due to incidental learning of the erroneously executed task-set, we predicted N-2 repetition costs to be decreased after task errors in Trial N-2, relative to correct responses. Furthermore, we predicted this effect to be present only when corrective control mechanisms would not have the time to build up on the post-error trial (i.e., following fast post-error trial only). This hypothesis was tested in a three-tasks paradigm using incongruent stimuli, under the assumption that errors on such trials are partly due to task confusions. Consistent with our predictions, N-2 repetition costs following N-2 errors were found to be reduced when responses in Trial N-1 were fast but were present when the N-1 response was slow. Taken together, our results suggest that task execution leads to associative strengthening of the corresponding task-set, irrespective of response accuracy, and that such automatic strengthening can be counteracted by slowly acting control mechanisms. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The aim of the present study was to examine the interplay of morphological configuration switching and language switching. The morphological configuration is present in word-formation whenever a word contains more than one free morpheme. The morphological configuration is variable both within and between languages for example in two-digit number names (is the decade named first as in twenty-one or the unit named first as in seventeen) and in compound words (is the modifier or the head named first). In the present experiments, participants had to switch between morphological configurations and between languages (German, English, and Spanish). Language-switch cost was measured as the performance difference between language-switch trials and language-repetition trials. In Experiments 1 and 2, participants performed language-comprehension tasks on two-digit numbers and a language-production task on compound words in Experiment 3. All three experiments revealed an under-additive switch cost pattern in which a larger language-switch cost occurred in morphological configuration-repetition trials than in morphological configuration-switch trials. Thus, the present data indicate integration of the morphological configuration and language into one language-related schema-irrespective of the language task (comprehension vs. production) and the type of stimuli (number words vs. compound nouns).

The present research explores decision making in multitasking, investigating how people make optimal decisions between tasks. Empirical evidence suggests that difficulties in task performance (i.e., response conflict within a task) can bias decision making. Here we investigate whether also conflict between task representations can tune choices away from conflict-associated tasks. Using a combined forced/freechoice task-switching design, we tested whether task conflict that arises because of proactive interference of previously activated tasks biases task choice. We compared free-choice decisions between 3 tasks after forced-choice sequences that instigated either high task conflict (task sequences of type ABA, in which persisting inhibition needs to be overcome because one switches back to a just-abandoned task) or low task conflict (task sequences of type CBA). Results of 2 experiments (N = 16; N = 32, preregistered) showed that participants were more likely to switch away from the previously performed task after high than after low task conflict. Furthermore, participants preferably selected the task that suffered least from task conflict and/or proactive interference. In addition, a third experiment (N = 32) confirmed that this bias in task selection could not be explained in terms of randomness heuristics. These results suggest a close link between decision making and performance in multitasking.