Item-specific priming of voluntary task switches

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.

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.

Exploring the carry-over of top-down attentional settings in dynamic conditions

A top-down attentional set can persist from a relevant task to an irrelevant task, influencing allocation of attentional resources, visual search, and performance. While this "carry-over" effect has been found across numerous experiments, past studies have utilised paradigms that present similar tasks to the same spatial location. The present research explored whether attentional settings persist in more dynamic situations. In Experiment 1, participants played a computer game that encouraged a horizontal, vertical, or random spread of search. After 10 or 30 s, they moved 90° to their right and monitored a driving video for hazards. Eye movements to the videos were not affected by the characteristics of the preceding game, revealing no carry-over of attentional settings. One possible explanation for this was the visuospatial shift between the tasks. To explore this further, Experiment 2 adopted a similar paradigm to previous research; participants searched horizontal, vertical, or random letter strings before completing an image search. In one block the tasks were presented to the same screen, and in one block the tasks were presented to different screens (incorporating a 90° visuospatial shift mid-trial). Carry-over was found in the one-screen block, with a significantly wider horizontal search and a narrower vertical search in the pictures after a horizontal letter search. However, there was no carry-over from the letter to the picture task in the two-screen block. This indicates the flexibility of attentional control in dynamic situations, and it is suggested that persistence of attentional settings will be most costly under stable conditions.

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.

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.

Brain connectivity modulation by Bayesian surprise in relation to control demand drives cognitive flexibility via control engagement

Human control is characterized by its flexibility and adaptability in response to the conditional probability in the environment. Previous studies have revealed that efficient conflict control could be attained by predicting and adapting to the changing control demand. However, it is unclear whether cognitive flexibility could also be gained by predicting and adapting to the changing control demand. The present study aimed to explore this issue by combining the model-based analyses of behavioral and neuroimaging data with a probabilistic cued task switching paradigm. We demonstrated that the Bayesian surprise (i.e. unsigned precision-weighted prediction error [PE]) negatively modulated the connections among stimulus processing brain regions and control regions/networks. The effect of Bayesian surprise modulation on these connections guided control engagement as reflected by the control PE effect on behavior, which in turn facilitated cognitive flexibility. These results bridge a gap in the literature by illustrating the neural and behavioral effect of control demand prediction (or PE) on cognitive flexibility and offer novel insights into the source of switch cost and the mechanism of cognitive flexibility.

The Role of Effector-Specific Task Representations in Voluntary Task Switching

There has been an increasing interest in uncovering the mechanisms underpinning how people decide which task to perform at a given time. Many studies suggest that task representations are crucial in guiding such voluntary task selection behavior, which is primarily reflected in a bias to select task repetitions over task switches. However, it is not yet clear whether the task-specific motor effectors are also a crucial component of task representations when deciding to switch tasks. Across three experiments using different voluntary task switching (VTS) procedures, we show that a greater overlap in task representations with a task-to-finger mapping than task-to-hand mapping increases participants' switching behavior (Exp. 1 and Exp. 2), but not when they were instructed to randomly select tasks (Exp. 3). Thus, task-specific stimulus-response associations can change the way people mentally represent tasks and influence switching behavior, suggesting that motor effectors should be considered as a component of task representations in biasing cognitive flexibility.

Instructing item-specific switch probability: expectations modulate stimulus-action priming

Both active response execution and passive listening to verbal codes (a form of instruction) in single prime trials lead to item-specific repetition priming effects when stimuli re-occur in single probe trials. This holds for task-specific classification (stimulus-classification, SC priming, e.g., apple-small) and action (stimulus-action, SA priming, e.g., apple-right key press). To address the influence of expectation on item-specific SC and SA associations, we tested if item-specific SC and SA priming effects were modulated by the instructed probability of re-encountering individual SC or SA mappings (25% vs. 75% instructed switch probability). Importantly, the experienced item-specific switch probability was always 50%. In Experiment 1 (N = 78), item-specific SA/SC switch  expectations affected SA, but not SC priming effects exclusively following active response execution. Experiment 2 (N = 40) was designed to emphasize SA priming by only including item-specific SC repetitions. This yielded stronger SA priming for 25% vs. 75% expected switch probability, both following response execution as in Experiment 1 and also following verbally coded SA associations. Together, these results suggest that SA priming effects, that is, the encoding and retrieval of SA associations, is modulated by item-specific switch expectation. Importantly, this expectation effect cannot be explained by item-specific associative learning mechanisms, as stimuli were primed and probed only once and participants experienced item-specific repetitions/switches equally often across stimuli independent of instructed switch probabilities. This corroborates and extends previous results by showing that SA priming effects are modulated by  expectation not only based on experienced item-specific switch probabilities, but also on mere instruction.

Mind wandering at encoding, but not at retrieval, disrupts one-shot stimulus-control learning

The one-shot pairing of a stimulus with a specific cognitive control process, such as task switching, can bind the two together in memory. The episodic control-binding hypothesis posits that the formation of temporary stimulus-control bindings, which are held in event-files supported by episodic memory, can guide the contextually appropriate application of cognitive control. Across two experiments, we sought to examine the role of task-focused attention in the encoding and implementation of stimulus-control bindings in episodic event-files. In Experiment 1, we obtained self-reports of mind wandering during encoding and implementation of stimulus-control bindings. Results indicated that, whereas mind wandering during the implementation of stimulus-control bindings does not decrease their efficacy, mind wandering during the encoding of these control-state associations interferes with their successful deployment at a later point. In Experiment 2, we complemented these results by using trial-by-trial pupillometry to measure attention, again demonstrating that attention levels at encoding predict the subsequent implementation of stimulus-control bindings better than attention levels at implementation. These results suggest that, although encoding stimulus-control bindings in episodic memory requires active attention and engagement, once encoded, these bindings are automatically deployed to guide behavior when the stimulus recurs. These findings expand our understanding of how cognitive control processes are integrated into episodic event files.

Proactive and reactive metacontrol in task switching

While cognitive control enables the selection of goal-relevant responses, metacontrol enables the selection of context-appropriate control operations. In task switching, metacontrol modulates task-switching efficiency by retrieving the associations between a contextual cue and a particular cognitive control demand. While the automatic retrieval of cognitive control is appealing due to its time and energy efficiency, the effects of different contextual cues have been shown in separate studies and appear to have different characteristics. Here, we devised a single task-switching paradigm to test whether we can observe both list-wide and item-specific metacontrol within subjects. In two experiments, we demonstrated reduced switch costs in lists associated with a high probability of switching as compared with lists with a low probability of switching (i.e., a list-wide switch probability [LWSP] effect). Similarly, we observed an analogous item-specific switch probability (ISSP) effect such that items associated with a high probability of switching incurred smaller switch costs as compared with items associated with a low probability of switching. We also confirmed that both list-wide and item-specific switch probability effects were not dependent on lower-level stimulus-response associations. However, the LWSP and the ISSP effects were uncorrelated, suggesting a lack of dependence. Together, these findings suggest that there are two distinct modes of metacontrol that are deployed in a context-sensitive manner in order to adapt to specific cognitive demands.