Conditioning task switching behavior

Task switching with probabilistic reward schemes

Previous research has shown that transitions in reward prospect influence (voluntary) task switching behavior. Specifically, an increase in reward prospect appears to enhance flexibility, as indicated by a higher voluntary switch rate (VSR), compared to situations where the reward prospect remains high. In contrast, when participants are randomly rewarded in the previous task, they tend to stick with this task, resulting in a lower VSR. The present study further explores the impact of probabilistic reward schemes on task switching. Two tasks were associated with distinct probabilities of receiving a reward for correct responses (high vs. low probability). This design allows for more refined predictions regarding VSR based on the results summarized above. In three experiments with voluntary and cued task switching, we observed that participants switched tasks less frequently when they were rewarded on the previous trial, regardless of whether the task had a high or low reward probability. This pattern suggests the use of a win-stay, lose-shift (WSLS) strategy, where participants are more likely to repeat their choice after receiving a reward. However, reward had no impact on switch costs. These results are discussed in the broader context of decision-making research, particularly in relation to strategies like WSLS and possibly different levels of cognitive processes affected by our manipulation and that of studies investigating transitions of reward prospect.

A shared temporal window of integration across cognitive control and reinforcement learning paradigms: A correlational study

Cognitive control refers to the ability to override prepotent response tendencies to achieve goal-directed behavior. On the other hand, reinforcement learning refers to the learning of actions through feedback and reward. Although cognitive control and reinforcement learning are often viewed as opposing forces in driving behavior, recent theories have emphasized possible similarities in their underling processes. With this study, we aimed to investigate whether a similar time window of integration could be observed during the learning of control on the one hand, and the learning rate in reinforcement learning paradigms on the other. To this end, we performed a correlational analysis on a large public dataset (n = 522) including data from two reinforcement learning tasks, i.e., a probabilistic selection task and a probabilistic Wisconsin Card Sorting Task (WCST), and data from a classic conflict task (i.e., the Stroop task). Results showed expected correlations between the time scale of control indices and learning rate in the probabilistic WCST. Moreover, the learning-rate parameters of the two reinforcement learning tasks did not correlate with each other. Together, these findings suggest a reliance on a shared learning mechanism between these two traditionally distinct domains, while at the same time emphasizing that value updating processes can still be very task-specific. We speculate that updating processes in the Stroop and WCST may be more related because both tasks require task-specific updating of stimulus features (e.g., color, word meaning, pattern, shape), as opposed to stimulus identity.

It's Hard to Prepare for Task Novelty: Cueing the Novelty of Upcoming Tasks Does Not Facilitate Task Performance

Rapidly learning new tasks, such as using new technology or playing a new game, is ubiquitous in our daily lives. Previous studies suggest that our brain relies on different networks for rapid task learning versus retrieving known tasks from memory, and behavioral studies have shown that novel versus practiced tasks may rely on different task configuration processes. Here, we investigated whether explicitly informing about the novelty of an incoming task would help participants prepare for different task configuration processes, such as pre-adjusting working memory gating functions. We hypothesized that if different task configuration processes can be prepared for, a pre-cue informing about the novelty of the upcoming task should lead to better task performance. Across four experiments, participants were first trained on a subset of tasks, followed by a test session in which pre-cues were provided in some blocks but not others. After comparing task performance between cued and uncued blocks, our results provided no evidence supporting the benefit of cueing for both practiced and novel tasks, suggesting that people cannot prepare for different task configuration processes in the absence of concrete task information.

The benefit of choice on task performance: Reduced difficulty effects in free-choice versus forced-choice tasks

We investigated how self-determined (free) versus imposed (forced) choices influence task performance. To this end, we examined how changes in perceptual and central decision-processing difficulties affect task performance in an environment where free-choice and forced-choice tasks were intermixed. In Experiments 1 (N = 43) and 2 (N = 42), perceptual processing difficulty was varied by altering colored dot proportions (easy vs. hard color discrimination task). In Experiment 3 (N = 58), decision-processing difficulty was adjusted by changing the rotation degree of letters (easy vs. hard letter rotation task). Across all experiments, both free-choice and forced-choice performance were more impaired with harder stimuli, but this effect was generally less pronounced in freely chosen tasks. Specifically, this was evident from significant interactions between processing mode (free vs. forced) and difficulty (easy vs. hard) in the mean reaction times (RTs) for the tasks with the difficulty manipulation. Thus, processing in free-choice tasks is generally less affected by environmental changes (i.e., variation in information difficulties). We discuss how the benefit of self-determined choices over imposed choices can be explained by motivational and performance-optimization accounts, while also considering the finding that participants adjusted their task choices toward tasks with easier stimuli (i.e., significant main effect of task difficulty on choosing the task with the difficulty manipulation). Specifically, we discuss how having control over task choices might lead to more stable information processing and allow people to choose more difficult tasks when this increased difficulty has a relatively small impact on their performance.

Discovering nurse mode: A phenomenological study of nursing student role micro-transitions

AIM

To explore the experiences of undergraduate nursing students in navigating daily micro-transitions between nursing and non-nursing roles.

BACKGROUND

Nursing students develop professional role identity through socialization, experience, and practice while simultaneously managing pre-existing personal roles. This dynamic creates a training ground for future sustainable practice.

DESIGN

Qualitative, cross-sectional, interpretive phenomenological design with hermeneutics.

METHODS

Seventeen undergraduate nursing students participated online in semi-structured, audiovisual-recorded interviews until data saturation was reached.

RESULTS

Three main themes emerged: 1) Strategies for Getting In and Out of Nurse Mode, 2) Cultivating Mindful Nursing Practice, and 3) Nursing Student Socialization and Immersion. Findings indicated that nursing students noticed benefits in their personal and professional lives as they developed this skill. Findings also suggested that students need support from their educators to ensure they are not trapped in nurse mode while learning to navigate nurse role identity.

CONCLUSIONS

Understanding and supporting nursing students in managing role micro-transitions are crucial. Findings indicated a functional need for nursing students to understand and apply knowledge and skills regarding a) when to initiate a role micro-transition and b) how to complete a micro-transition effectively between a nursing and non-nursing role. Educational strategies and support systems addressing this need may improve future nursing professionals' quality of life and clinical practice.

Contextual control demands determine whether stability and flexibility trade off against each other

Cognitive stability, the ability to focus on a current task, and cognitive flexibility, the ability to switch between different tasks, are traditionally conceptualized as opposing end-points on a one-dimensional continuum. This assumption obligates a stability-flexibility trade-off - greater stability equates to less flexibility, and vice versa. In contrast, a recent cued task-switching study suggested that stability and flexibility can be regulated independently, evoking a two-dimensional perspective where trade-offs are optional (Geddert & Egner, Journal of Experimental Psychology: General, 151, 3009-3027, 2022). This raises the question of under what circumstances trade-offs occur. We here tested the hypothesis that trade-offs are guided by cost-of-control considerations whereby stability and flexibility trade off in contexts that selectively promote stability or flexibility, but not when neither or both are promoted. This proposal was probed by analyzing whether a trial-level metric of a stability-flexibility trade-off, an interaction between task-rule congruency and task sequence, varied as a function of a broader block-level context that independently varied demands on stability or flexibility by manipulating the proportion of incongruent and switch trials, respectively. In Experiment 1, we reanalyzed data from Geddert and Egner, Journal of Experimental Psychology: General, 151, 3009-3027, (2022); Experiment 2 was a conceptual replication with a design tweak that controlled for potential confounds due to local trial history effects. The experiments produced robust evidence for independent stability and flexibility adaptation, and for a context-dependent expression of trial-level stability-flexibility trade-offs that generally conformed to the cost-of-control predictions. The current study thus documents that stability-flexibility trade-offs are not obligatory but arise in contexts where either stability or flexibility are selectively encouraged.

Learned switch readiness via concurrent activation of task sets: Evidence from task specificity and memory load

Cognitive flexibility increases when switch demands increase. In task switching experiments, repeated pairing of flexibility-demanding situations with specific contexts leads subjects to become more prepared to adapt to changing task demands in those contexts. One form of such upregulated cognitive flexibility has been demonstrated with a list-wide switch probability (LWSP) effect, where switch costs are smaller in lists with frequent switches than in lists with rare switches. According to a recent proposal, the LWSP effect is supported by a concurrent activation mechanism whereby both task rules are kept available simultaneously in working memory. We conducted four experiments to test two key features in this concurrent activation account of LWSP effects. First, we asked whether the LWSP effects are limited to only the trained tasks, and second, we asked whether concurrent working memory load would reduce the LWSP effects. In Experiment 1, we replicated and extended previous findings that the LWSP manipulation modulates both performance (switch costs) and voluntary switch rates, indicating that context-driven increases in flexibility are generalizable so long as the task-sets remain the same. Results of Experiments 2 and 3 showed that novel tasks do not benefit from the concurrent activation of the two other tasks, suggesting that the LWSP effect is task specific. Experiment 4 showed that holding additional information in working memory reduces the LWSP effect. While these findings support the hypothesis of concurrent activation underlying the increased flexibility in the LWSP effect, caveats remain; additional research is needed to further test this account.

The influence of reward and loss outcomes after free- and forced-tasks on voluntary task choice

In four experiments, we investigated the impact of outcomes and processing mode (free versus forced) on subsequent voluntary task-switching behavior. Participants freely chose between two tasks or were forced to perform one, and the feedback they received randomly varied after correct performance (reward or no-reward; loss or no-loss). In general, we reasoned that the most recently applied task goal is usually the most valued one, leading people to prefer task repetitions over switches. However, the task values might be additionally biased by previous outcomes and the previous processing mode. Indeed, negatively reinforcing tasks with no-reward or losses generally resulted in more subsequent switches. Additionally, participants demonstrated a stronger attachment to free- compared to forced-tasks, as indicated by more switches when the previous task was forced, suggesting that people generally value free over forced-choice task goals. Moreover, the reward manipulation had a greater influence on switching behavior following free- compared to forced-tasks in Exp. 1 and Exp. 3, suggesting a stronger emphasis on evaluating rewarding outcomes associated with free-task choices. However, this inflationary effect on task choice seemed to be limited to reward and situations where task choice and performance more strongly overlap. Specifically, there was no evidence that switching behavior was differentially influenced after free-and forced-task as a function of losses (Exp. 2) or reward when task choice and task performance were separated (Exp. 4). Overall, the results provide new insights into how the valuation of task goals based on choice freedom and outcome feedback can influence voluntary task choices.

The temporal dynamics of task processing and choice in a novel multitasking paradigm

This study investigated the temporal dynamics of task performance and voluntary task choice within a multitasking paradigm in which the task-related processing outcomes themselves determined the to-be-performed task. In the novel forced-no-go trials, the stimulus for one task required an overt response, but the stimulus for the other task was associated with a no-go response. Task performance results showed that participants often processed the no-go task's stimulus before switching to the go-task. Dual-task interference effects and switch costs indicated various forms of multitasking interference, with their underlying causes appearing to overlap, as engagement in parallel processing seemed to be limited by switch-related reconfiguration processes. Intermixing free-choice trials, where both stimuli were associated with overt responses, revealed costs associated with switching between processing modes, providing new evidence that the distinctions between free and forced task goals stem from differences in their internal representations rather than alterations in processing due to different presentations in the environment. Task choice results align with this perspective, demonstrating a preference for repeating a free- over a forced-choice task. Furthermore, these free-choice results illuminate the interplay of cognitive (task-repetition bias) and environmental constraints (first-task bias) in shaping task choices: It appears that task-specific information increases goal activations for both task goals concurrently, with participants favoring central processing of the second- over the first-presented task to optimize their behavior when shorter central processing is required (task repetition). Overall, this study offers new insights into the dynamics of task processing and choice in environments requiring the balance of multiple tasks.

Dynamic changes in task preparation in a multi-task environment: The task transformation paradigm

A key element of human flexible behavior concerns the ability to continuously predict and prepare for sudden changes in tasks or actions. Here, we tested whether people can dynamically modulate task preparation processes and decision-making strategies when the identity of a to-be-performed task becomes uncertain. To this end, we developed a new paradigm where participants need to prepare for one of nine tasks on each trial. Crucially, in some blocks, the task being prepared could suddenly shift to a different task after a longer cue-target interval, by changing either the stimulus category or categorization rule that defined the initial task. We found that participants were able to dynamically modulate task preparation in the face of this task uncertainty. A second experiment shows that these changes in behavior were not simply a function of decreasing task expectancy, but rather of increasing switch expectancy. Finally, in the third and fourth experiment, we demonstrate that these dynamic modulations can be applied in a compositional manner, depending on whether either only the stimulus category or categorization rule would be expected to change.

Task performance errors and rewards affect voluntary task choices

Humans are remarkably flexible in adapting their behavior to current demands. It has been suggested that the decision which of multiple tasks to perform is based on a variety of factors pertaining to the rewards associated with each task as well as task performance (e.g., error rates associated with each task and/or error commission on the previous trial). However, further empirical investigation is needed to examine whether task performance still influences task choices if task choices are rewarded but task performance is not. Accordingly, we exposed participants to a novel reward-varying voluntary task switching paradigm where the reward for the performed task gradually decreased while the reward associated for the alternative task was unchanged. Importantly, we rewarded participants' task choices before participants performed the task to investigate the effect of rewards independent from task performance. We examined the effect of (i) reward, (ii) error rates associated with each of the two tasks, and (iii) error commission in the previous trial on voluntary task choices. As expected, we found that participants' task selection was influenced by reward differences between task choices. In addition, error rates associated with a task also influenced task selection, with participants requiring larger reward differences to switch to a task associated with relatively higher error rates, compared to switching to a task with relatively lower error rates. However, errors in n - 1 did not influence participants' probability to switch to the alternative task. These findings contribute to an ongoing discussion on the influence of task performance on task selection.

Reactive and proactive control processes in voluntary task choice

Deciding which task to perform when multiple tasks are available can be influenced by external influences in the environment. In the present study, we demonstrate that such external biases on task-choice behavior reflect reactive control adjustments instead of a failure in control to internally select a task goal. Specifically, in two experiments we delayed the onset of one of two task stimuli by a short (50 ms), medium (300 ms), or long (1,000 ms) stimulus-onset asynchrony (SOA) within blocks while also varying the relative frequencies of short versus long SOAs across blocks (i.e., short SOA frequent vs. long SOA frequent). Participants' task choices were increasingly biased towards selecting the task associated with the first stimulus with increasing SOAs. Critically, both experiments also revealed that the short-to-medium SOA bias was larger in blocks with more frequent long SOAs when participants had limited time to prepare for an upcoming trial. When time to select an upcoming task was extended in Experiment 2, this interaction was not significant, suggesting that the extent to which people rely on reactive control adjustments is additionally modulated by proactive control processes. Thus, the present findings also suggest that voluntary task choices are jointly guided by both proactive and reactive processes, which are likely to adjust the relative activation of different task goals in working memory.

Insights into control over cognitive flexibility from studies of task-switching

Cognitive flexibility denotes the ability to disengage from a current task and shift one's focus to a different activity. An individual's level of flexibility is not fixed; rather, people adapt their readiness to switch tasks to changing circumstances. We here review recent studies in the task-switching literature that have produced new insights into the contextual factors that drive this adaptation of flexibility, as well as proposals regarding the underlying cognitive mechanisms and learning processes. A fast-growing literature suggests that there are several different means of learning the need for, and implementing, changes in one's level of flexibility. These, in turn, have distinct consequences for the degree to which adjustments in cognitive flexibility are transferrable to new stimuli and tasks.

Reinforcement learning of adaptive control strategies

Humans can up- or downregulate the degree to which they rely on task information for goal-directed behaviour, a process often referred to as cognitive control. Adjustments in cognitive control are traditionally studied in response to experienced or expected task-rule conflict. However, recent theories suggest that people can also learn to adapt control settings through reinforcement. Across three preregistered task switching experiments (n = 415), we selectively rewarded correct performance on trials with either more (incongruent) or less (congruent) task-rule conflict. Results confirmed the hypothesis that people rewarded more on incongruent trials showed smaller task-rule congruency effects, thus optimally adapting their control settings to the reward scheme. Using drift diffusion modelling, we further show that this reinforcement of cognitive control may occur through conflict-dependent within-trial adjustments of response thresholds after conflict detection. Together, our findings suggest that, while people remain more efficient at learning stimulus-response associations through reinforcement, they can similarly learn cognitive control strategies through reinforcement.

Principles of cognitive control over task focus and task switching

Adaptive behaviour requires the ability to focus on a task and protect it from distraction (cognitive stability) and to rapidly switch tasks when circumstances change (cognitive flexibility). Burgeoning research literatures have aimed to understand how people achieve task focus and task switch readiness. In this Perspective, I integrate these literatures to derive a cognitive architecture and functional rules underlying the regulation of cognitive stability and flexibility. I propose that task focus and task switch readiness are supported by independent mechanisms. However, I also suggest that the strategic regulation of both mechanisms is governed by shared learning principles: an incremental, online learner that nudges control up or down based on the recent history of task demands (a recency heuristic) and episodic reinstatement when the current context matches a past experience (a recognition heuristic). Finally, I discuss algorithmic and neural implementations of these processes, as well as clinical implications.

Control dilemma: Evidence of the stability-flexibility trade-off

Cognitive control can be applied flexibly when task goals or environments change (i.e., cognitive flexibility), or stably to pursue a goal in the face of distraction (i.e., cognitive stability). Whether these seemingly contradictory characteristics have an inverse relationship has been controversial, as some studies have suggested a trade-off mechanism between cognitive flexibility and cognitive stability, while others have not found such reciprocal associations. This study investigated the possible antagonistic correlation between cognitive flexibility and stability using a novel version of the flexibility-stability paradigm and the classic cued task switching paradigm. In Experiment 1, we showed that cognitive flexibility was inversely correlated with cognitive stability, as increased distractor proportions were associated with decreased cognitive flexibility and greater cognitive stability. Moreover, cognitive flexibility and stability were regulated by a single control system instead of two independent control mechanisms, as the model selection results indicated that the reciprocally regulated model with one integration parameter outperformed all other models, and the model parameter was inversely linked to cognitive flexibility and stability. We found similar results using the classic cued task switching paradigm in Experiment 2. Therefore, a trade-off between cognitive flexibility and stability was observed from the paradigms used in this study.

Learning how to reason and deciding when to decide

Research on human reasoning has both popularized and struggled with the idea that intuitive and deliberate thoughts stem from two different systems, raising the question how people switch between them. Inspired by research on cognitive control and conflict monitoring, we argue that detecting the need for further thought relies on an intuitive, context-sensitive process that is learned in itself.

Transfer of Learned Cognitive Flexibility to Novel Stimuli and Task Sets

Adaptive behavior requires learning about the structure of one's environment to derive optimal action policies, and previous studies have documented transfer of such structural knowledge to bias choices in new environments. Here, we asked whether people could also acquire and transfer more abstract knowledge across different task environments, specifically expectations about cognitive control demands. Over three experiments, participants (Amazon Mechanical Turk workers; N = ~80 adults per group) performed a probabilistic card-sorting task in environments of either a low or high volatility of task rule changes (requiring low or high cognitive flexibility, respectively) before transitioning to a medium-volatility environment. Using reinforcement-learning modeling, we consistently found that previous exposure to high task rule volatilities led to faster adaptation to rule changes in the subsequent transfer phase. These transfers of expectations about cognitive flexibility demands were both task independent (Experiment 2) and stimulus independent (Experiment 3), thus demonstrating the formation and generalization of environmental structure knowledge to guide cognitive control.

Perceptual processing demands influence voluntary task choice

Previous studies have suggested that people are sensitive to anticipated cognitive processing demands when deciding which task to perform, but the influence of perceptual processing demands on voluntary task choice is still unclear. The present study tested whether voluntary task choice behavior may be influenced by unpredictable task-specific perceptual processing demands. Across four experiments using different voluntary task choice procedures, we randomly varied the perceptual discriminability of stimuli (easy vs. hard color discrimination) for one of the two tasks. We reasoned that people could only reactively adjust their task choice behavior to the unpredictable discriminability manipulation if they engaged in some perceptual processing before a task goal becomes sufficiently activated to select the task for further processing. The results confirmed this hypothesis: Task performance data demonstrated the presence of perceptual (discriminability effects) and cognitive (switch costs) processing demands. Participants' choice behavior was affected by both types of processing demands (as reflected in a task repetition bias and a bias to select the color task with easy compared to hard discriminations). Thus, the present findings indicate that both perceptual and cognitive processing demands influence voluntary task choice behavior. We propose that higher-level goal activations interact at least partially with early perceptual processes to influence task choice behavior, suggesting a locus of voluntary choices during or after the perceptual stage within the information-processing stream.

The subjective evaluation of task switch cues is related to voluntary task switching

Task switching refers to the effortful mental process of shifting attention between different tasks. While it is well-established that task switching usually comes with an objective performance cost, recent studies have shown that people also subjectively evaluate task switching as negative. An open question is whether this affective evaluation of task switching is also related to actual decision making. In this pre-registered study, we therefore examined whether individual differences in the negative evaluation of task switch cues are related to less voluntary task switching. To this end, participants first performed a cued task switching paradigm where abstract cues signaled task transitions (repetition or alternation). In a second phase, these transition cues were used as prime stimuli in an affective priming procedure to assess participants' affective evaluation of task switching. In a third phase, participants were allowed to freely choose whether to switch or repeat tasks. We found that a more negative evaluation of task switching cues was related to lower switch rates in the voluntary task switching phase. This finding supports neuroeconomic theories of value-based decision making which suggest that people use their subjective value of control to decide whether to engage in (different) tasks.

Grounding Adaptive Cognitive Control in the Intrinsic, Functional Brain Organization: An HD-EEG Resting State Investigation

In a recent study, we used the dynamic temporal prediction (DTP) task to demonstrate that the capability to implicitly adapt motor control as a function of task demand is grounded in at least three dissociable neurofunctional mechanisms: expectancy implementation, expectancy violation and response implementation, which are supported by as many distinct cortical networks. In this study, we further investigated if this ability can be predicted by the individual brain's functional organization at rest. To this purpose, we recorded resting-state, high-density electroencephalography (HD-EEG) in healthy volunteers before performing the DTP task. This allowed us to obtain source-reconstructed cortical activity and compute whole-brain resting state functional connectivity at the source level. We then extracted phase locking values from the parceled cortex based on the Destrieux atlas to estimate individual functional connectivity at rest in the three task-related networks. Furthermore, we applied a machine-learning approach (i.e., support vector regression) and were able to predict both behavioral (response speed and accuracy adaptation) and neural (ERP modulation) task-dependent outcome. Finally, by exploiting graph theory nodal measures (i.e., degree, strength, local efficiency and clustering coefficient), we characterized the contribution of each node to the task-related neural and behavioral effects. These results show that the brain's intrinsic functional organization can be potentially used as a predictor of the system capability to adjust motor control in a flexible and implicit way. Additionally, our findings support the theoretical framework in which cognitive control is conceived as an emergent property rooted in bottom-up associative learning processes.

The self-organized task switching paradigm: Movement effort matters

The self-organized task switching paradigm enables to investigate the link between task performance and task selection in a voluntary task switching setting that benefits task switches over task repetitions. For example, waiting for a repetition-related stimulus onset denotes environmental costs, which are balanced with internal task-switch costs. Here we extent this research by asking whether movement effort also plays a crucial role for task selection. In detail, we investigate how motor-related consequences, i.e., increasing force for task repetitions, influence task-switching behavior. Participants voluntarily switched between a number (i.e., even or odd) or letter task (i.e., vowel or consonant) using a robot system for response execution. With consecutive task repetitions the robot system was harder to move to the response target as we systematically added a damping load. We found that switch rate correlated with cognitive switch costs (i.e., costs in: reaction time, r = -0.741, and error rate, r = -0.545), and motor repetition cost represented by movement-time increment, r = 0.414. Interestingly, switch rate also correlated with individual force maximum, r = -0.480. However, switch rate did not correlate with movement-impulse increment, r = -0.033. Stepwise multiple regression analyses across participants revealed that 66% of variance are explained including all predicting factors. Yet, only cognitive costs and individual force maximum reached significant importance in the regression model. Hence, we extended switch-rate analyses using linear regression on a within-subject level, and thus, keeping individual force maximum constant. We found about 84% of variance explained by motor and cognitive costs. Thereby, movement impulse predicted task selection more than reaction time and more than movement time. Thus, we demonstrated that both cognitive and motor consequences influence task-switch behavior. Furthermore, we showed that task selection is importantly modulated by motor effort related to individual motor skills.

Appealing to the cognitive miser: Using demand avoidance to modulate cognitive flexibility in cued and voluntary task switching

Current cognitive control accounts view goal-directed behavior as striking a balance between two antagonistic control demands: Stability, on the one hand, reflects a rigid, focused state of control and flexibility, while on the other, reflects a relaxed, distractible state, whereby goals can be rapidly updated to meet unexpected changes in demands. In the current study, we sought to test whether the avoidance of cognitive demand could motivate people to dynamically regulate control along the stability-flexibility continuum. In both cued (Experiment 1) and voluntary (Experiment 2) task-switching paradigms, we selectively associated either task-switches or task-repetitions with high cognitive demand (independent of task identity), and measured changes in performance in a following phase after the demand manipulation was removed. Contrasting performance with a control group, across both experiments, we found that selectively associating cognitive demand with task repetitions increased flexibility, but selectively associating cognitive demand with task switches failed to increase stability. The results of the current study provide novel evidence for avoidance-driven modulations of control regulation along the stability-flexibility continuum, while also highlighting some limitations in using task-switching paradigms to examine motivational influences on control adaptation. Data, analysis code, experiment code, and preprint available at osf.io/7rct9/. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Effect of non-instructed instrumental contingency of monetary reward and positive affect in a cognitive control task

In recent years, we observed a strong interest in the influence of motivation and emotion on cognitive control. Prior studies suggest that the instrumental contingency between a response and a rewarding or affective stimulus is particularly important in that context-which is resonating with observations in the associative learning literature. However, despite this overlap, and the relevance of non-instructed learning in real life, the vast majority of studies investigating motivation-cognition interactions use direct instructions to inform participants about the contingencies between responses and stimuli. Thus, there is little experimental insight regarding how humans detect non-instructed contingencies between their actions and motivational or affective outcomes, and how these learned contingencies come to influence cognitive control processes. In an attempt to close this gap, the goal of the present study was to test the effect of non-instructed contingent and non-contingent outcomes (i.e. monetary reward and positive affective stimuli) on cognitive control using the AX-continuous performance task (AX-CPT) paradigm. We found that entirely non-instructed contingencies between responses and positive outcomes (both monetary and affective ones) led to significant performance improvement. The present results open new perspectives for studying the influence of motivation and emotion on cognitive control at the insertion with associative learning.

Selective reinforcement of conflict processing in the Stroop task

Motivation signals have been shown to influence the engagement of cognitive control processes. However, most studies focus on the invigorating effect of reward prospect, rather than the reinforcing effect of reward feedback. The present study aimed to test whether people strategically adapt conflict processing when confronted with condition-specific congruency-reward contingencies in a manual Stroop task. Results show that the size of the Stroop effect can be affected by selectively rewarding responses following incongruent versus congruent trials. However, our findings also suggest important boundary conditions. Our first two experiments only show a modulation of the Stroop effect in the first half of the experimental blocks, possibly due to our adaptive threshold procedure demotivating adaptive behavior over time. The third experiment showed an overall modulation of the Stroop effect, but did not find evidence for a similar modulation on test items, leaving open whether this effect generalizes to the congruency conditions, or is stimulus-specific. More generally, our results are consistent with computational models of cognitive control and support contemporary learning perspectives on cognitive control. The findings also offer new guidelines and directions for future investigations on the selective reinforcement of cognitive control processes.

Meta-control: From psychology to computational neuroscience

Research in the past decades shed light on the different mechanisms that underlie our capacity for cognitive control. However, the meta-level processes that regulate cognitive control itself remain poorly understood. Following the terminology from artificial intelligence, meta-control can be defined as a collection of mechanisms that (a) monitor the progress of controlled processing and (b) regulate the underlying control parameters in the service of current task goals and in response to internal or external constraints. From a psychological perspective, meta-control is an important concept because it may help explain and predict how and when human agents select different types of behavioral strategies. From a cognitive neuroscience viewpoint, meta-control is a useful concept for understanding the complex networks in the prefrontal cortex that guide higher-level behavior as well as their interactions with neuromodulatory systems (such as the dopamine or norepinephrine system). The purpose of the special issue is to integrate hitherto segregated strands of research across three different perspectives: 1) a psychological perspective that specifies meta-control processes on a functional level and aims to operationalize them in experimental tasks; 2) a computational perspective that builds on ideas from artificial intelligence to formalize normative solutions to meta-control problems; and 3) a cognitive neuroscience perspective that identifies neural correlates of and mechanisms underlying meta-control.

The role of dopamine in action control: Insights from medication effects in Parkinson's disease

Parkinson's disease (PD) is a neurological disorder associated primarily with overt motor symptoms. Several studies show that PD is additionally accompanied by impairments in covert cognitive processes underlying goal-directed motor functioning (e.g., action planning, conflict adaptation, inhibition), and that dopaminergic medication may modulate these action control components. In this review we aim to leverage findings from studies in this domain to elucidate the role of dopamine (DA) in action control. A qualitative review of studies that investigated the effects of medication status (on vs. off) on action control in PD suggests a component-specific role for DA in action control, although the expression of medication effects depends on characteristics of both the patients and experimental tasks used to measure action control. We discuss these results in the light of findings from other research lines examining the role of DA in action control (e.g., animal research, pharmacology), and recommend that future studies use multi-method, within-subject approaches to model DA effects on action control across different components as well as underlying striatal pathways (ventral vs. dorsal).

Examining the Trainability and Transferability of Working-Memory Gating Policies

Internal working memory (WM) gating control policies have been suggested to constitute a critical component of task-sets that can be learned and transferred to very similar task contexts (Bhandari and Badre (Cognition, 172, 33–43, 2018). Here, we attempt to expand these findings, examining whether such control policies can be also trained and transferred to other untrained cognitive control tasks, namely to task switching and AX-CPT. To this end, a context-processing WM task was used for training, allowing to manipulate either input (i.e., top-down selective entry of information into WM) or output (i.e., bottom-up selective retrieval of WM) gating control policies by employing either a context-first (CF) or context-last (CL) task structure, respectively. In this task, two contextual cues were each associated with two different stimuli. In CF condition, each trial began with a contextual cue, determining which of the two subsequent stimuli is target relevant. In contrast, in the CL condition the contextual cue appeared last, preceded by a target and non-target stimulus successively. Participants completed a task switching baseline assessment, followed by one practice and six training blocks with the WM context-processing training task. After completing training, task-switching and AX-CPT transfer blocks were administrated, respectively. As hypothesized, compared to CL training condition, CF training led to improved task-switching performance. However, contrary to our predictions, training type did not influence AX-CPT performance. Taken together, the current results provide further evidence that internal control policies are (1) inherent element of task-sets, also in task switching and (2) independent of S-R mappings. However, these results need to be cautiously interpreted due to baseline differences in task-switching performance between the conditions (overall slower RTs in the CF condition). Importantly though, our results open a new venue for the realm of cognitive enhancement, pointing here for the first time to the potential of control policies training in promoting wider transfer effects.

Scaling of the Parameters for Cost Balancing in Self-Organized Task Switching

Previous studies on voluntary task switching using the self-organized task switching paradigm suggest that task performance and task selection in multitasking are related. When deciding between two tasks, the stimulus associated with a task repetition occurred with a stimulus onset asynchrony (SOA) that continuously increased with the number of repetitions, while the stimulus associated with a task switch was immediately available. Thus, the waiting time for the repetition stimulus increased with number of consecutive task repetitions. Two main results were shown: first, switch costs and voluntary switch rates correlated negatively - the smaller the switch costs, the larger the switch rates. Second, participants switched tasks when switch costs and waiting time for the repetition stimulus were similar. In the present study, we varied the SOA that increased with number of task repetitions (SOA increment) and also varied the size of the switch costs by varying the intertrial interval. We examined which combination of SOA increment and switch costs maximizes participants' attempts to balance waiting time and switch costs in self-organized task switching. We found that small SOA increments allow for fine-grained adaptation and that participants can best balance their switch costs and waiting times in settings with medium switch costs and small SOA increments. In addition, correlational analyses indicate relations between individual switch costs and individual switch rates across participants.

Item-specific priming of voluntary task switches

The ability to switch efficiently between different tasks underpins cognitive flexibility and is impaired in various psychiatric disorders. Recent research has suggested that the control processes mediating switching can be subject to learning, because "switch readiness" can become associated with, and primed by, specific stimuli. In cued task switching, items that are frequently associated with the need to switch incur a smaller behavioral switch cost than do items associated with a low probability of switching, known as the item-specific switch probability (ISSP) effect (Chiu & Egner, 2017). However, it remains unknown whether ISSP associations modulate the efficiency of only cued switching or also impact people's voluntary choice to switch tasks. Here, we addressed this question by combining an ISSP manipulation with a protocol that mixed 75% standard cued task trials with 25% free choice trials, allowing us to measure the effect of ISSP on voluntary switch rate (VSR). We observed robust ISSP effects on cued trials, replicating previous findings. Crucially, we also found that the VSR was greater for items associated with a high than with a low switch likelihood. We thus demonstrate that associating specific stimuli with frequent switch requirements not only reduces switch costs but also enhances participants' tendency to switch voluntarily. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Striatal-frontal network activation during voluntary task selection under conditions of monetary reward

During voluntary task selection, a number of internal and external biases may guide such a choice. However, it is not well understood how reward influences task selection when multiple options are possible. To address this issue, we examined brain activation in a voluntary task-switching paradigm while participants underwent fMRI (n = 19). To reinforce the overall goal to choose the tasks randomly, participants were told of a large bonus that they would receive at the end of the experiment for making random task choices. We also examined how occasional, random rewards influenced both task performance and brain activation. We hypothesized that these transient rewards would increase the value of the just-performed task, and therefore bias participants to choose to repeat the same task on the subsequent trial. Contrary to expectations, transient reward had no consistent behavioral effect on subsequent task choice. Nevertheless, the receipt of such rewards did influence activation in brain regions associated with reward processing as well as those associated with goal-directed control. In addition, reward on a prior trial was found to influence activation during task choice on a subsequent trial, with greater activation in a number of executive function regions compared with no-reward trials. We posit that both the random presentation of transient rewards and the overall task bonus for random task choices together reinforced the goal to choose the tasks randomly, which in turn influenced activation in both reward-related regions and those regions involved in abstract goal processing.

Executive functions are cognitive gadgets

Many psychologists and neuroscientists still see executive functions as independent, domain-general, supervisory functions that are often dissociated from more "low-level" associative learning. Here, we suggest that executive functions very much build on associative learning, and argue that executive functions might be better understood as culture-sensitive cognitive gadgets, rather than as ready-made cognitive instincts.

Cortical and subcortical contributions to context-control learning

"Cognitive control" describes our ability to strategically bias information processing in line with internal goals. Traditionally, research has focused on delineating the sources of top-down biasing, implicating the lateral prefrontal cortex. The past two decades, however, have seen increasing interest in the regulation of control, that is, how learning processes guide the context-sensitive application of top-down biasing. Here, we review and synthesize recent research into the cognitive and neural mechanisms of this type of "context-control learning". We first discuss a fast-growing cognitive psychology literature documenting how specific cognitive control states can become associated with, and subsequently triggered by, contextual cues. We then review neuroimaging studies that speak to the neural substrates of contextual adjustments in control, with a particular focus on recent work that explicitly modeled context-control learning processes. We conclude that these studies suggest an important subcortical extension of the traditional frontal control network, as they indicate a key role for the caudate nucleus in forming associations between contextual cues and appropriate control settings.

Increasing reward prospect promotes cognitive flexibility: Direct evidence from voluntary task switching with double registration

Recent research has suggested that sequential changes in the prospect of performance-contingent rewards may influence the balance between cognitive flexibility and stability: whereas constant high reward prospect seems to promote cognitive stability, increasing reward prospect has been shown to promote flexible behaviour in voluntary task-switching paradigms. Previous studies, however, confounded cognitive flexibility regarding voluntary task choices with control processes during task execution. We present five experiments to dissociate these two processes by means of a double registration procedure, in which task choice is registered prior to task execution. The data yielded clear evidence for reward-driven modulation of the flexibility-stability balance already at the level of task choices, with higher voluntary switch rates when reward prospect increased compared with situations in which reward prospect remained high. This effect was further modulated by the specific type of registration procedure, suggesting that only deliberate task choices are affected by the reward sequence. These results thus confirm that the prospect of performance-contingent reward can indeed promote either cognitive stability or flexibility depending on the immediate reward history.

The affective twitches of task switches: Task switch cues are evaluated as negative

Task switching refers to the demanding cognitive control process that allows us to flexibly switch between different task contexts. It is a seminal observation that task switching comes with a performance cost (i.e., switch cost), but recent theories suggest that task switching could also carry an affective cost. In two experiments, we investigated the affective evaluation of task switching by having participants perform a task-switching paradigm followed by an affective priming procedure. Crucially, the transition cues of the task-switching paradigm, indicating task alternations or task repetitions, were used as primes in the affective priming procedure to assess their affective connotation. We found that task alternation primes were evaluated as more negative than task repetition primes. These findings show that task switching is affectively tagged, and suggest a potential role for emotion regulation processes in cognitive control.

On How to Be Flexible (or Not): Modulation of the Stability-Flexibility Balance

Goal-directed behavior in a constantly changing environment requires a dynamic balance between two antagonistic modes of control: On the one hand, goals need to be maintained and shielded from distraction (stability), and on the other hand, goals need to be relaxed and flexibly updated whenever significant changes occur (flexibility). A dysregulation of this stability-flexibility balance can result in overly rigid or overly distractible behavior, and it is therefore important to understand how this balance is regulated in a context-sensitive, adaptive manner. In the present article, we review recent evidence on how positive affect, reward prospect, and task context modulate the stability-flexibility balance. Two distinct underlying cognitive mechanisms will be discussed: Flexibility may result either from lowering the updating threshold in working memory or from keeping multiple tasks active in working memory. Critically, these two mechanisms allow different (testable) predictions: Whereas lowering the updating threshold should ease the access of new information in working memory and thereby increase flexibility in general, concurrent task activation should only increase flexibility between the respective tasks.

Low and variable correlation between reaction time costs and accuracy costs explained by accumulation models: Meta-analysis and simulations

The underpinning assumption of much research on cognitive individual differences (or group differences) is that task performance indexes cognitive ability in that domain. In many tasks performance is measured by differences (costs) between conditions, which are widely assumed to index a psychological process of interest rather than extraneous factors such as speed-accuracy trade-offs (e.g., Stroop, implicit association task, lexical decision, antisaccade, Simon, Navon, flanker, and task switching). Relatedly, reaction time (RT) costs or error costs are interpreted similarly and used interchangeably in the literature. All of this assumes a strong correlation between RT-costs and error-costs from the same psychological effect. We conducted a meta-analysis to test this, with 114 effects across a range of well-known tasks. Counterintuitively, we found a general pattern of weak, and often no, association between RT and error costs (mean r = .17, range -.45 to .78). This general problem is accounted for by the theoretical framework of evidence accumulation models, which capture individual differences in (at least) 2 distinct ways. Differences affecting accumulation rate produce positive correlation. But this is cancelled out if individuals also differ in response threshold, which produces negative correlations. In the models, subtractions between conditions do not isolate processing costs from caution. To demonstrate the explanatory power of synthesizing the traditional subtraction method within a broader decision model framework, we confirm 2 predictions with new data. Thus, using error costs or RT costs is more than a pragmatic choice; the decision carries theoretical consequence that can be understood through the accumulation model framework. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Getting a grip on cognitive flexibility

Cognitive flexibility refers to the ability to quickly reconfigure our mind, like when we switch between different tasks. This review highlights recent evidence showing that cognitive flexibility can be conditioned by simple incentives typically known to drive lower-level learning, such as stimulus-response associations. Cognitive flexibility can also become associated with, and triggered by, bottom-up contextual cues in our environment, including subliminal cues. Therefore, we suggest that the control functions that mediate cognitive flexibility are grounded in, and guided by, basic associative learning mechanisms, and abide by the same learning principles as more low-level forms of behavior. Such a learning perspective on cognitive flexibility offers new directions and important implications for further research, theory, and applications.

Planning Complexity Registers as a Cost in Metacontrol

Decision-making algorithms face a basic tradeoff between accuracy and effort (i.e., computational demands). It is widely agreed that humans can choose between multiple decision-making processes that embody different solutions to this tradeoff: Some are computationally cheap but inaccurate, whereas others are computationally expensive but accurate. Recent progress in understanding this tradeoff has been catalyzed by formalizing it in terms of model-free (i.e., habitual) versus model-based (i.e., planning) approaches to reinforcement learning. Intuitively, if two tasks offer the same rewards for accuracy but one of them is much more demanding, we might expect people to rely on habit more in the difficult task: Devoting significant computation to achieve slight marginal accuracy gains would not be "worth it." We test and verify this prediction in a sequential reinforcement learning task. Because our paradigm is amenable to formal analysis, it contributes to the development of a computational model of how people balance the costs and benefits of different decision-making processes in a task-specific manner; in other words, how we decide when hard thinking is worth it.