Explore the vast range of titles available.

Cognitive flexibility refers to the ability to quickly reconfigure our mind, as 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.

During task‐switching paradigms, both event‐related potentials and time‐frequency analyses show switch and mixing effects at frontal and parietal sites. Switch and mixing effects are associated with increased power in broad frontoparietal networks, typically stronger in the theta band (~4–8 Hz). However, it is not yet known whether mixing and switch costs rely upon common or distinct networks. In this study, we examine proactive and reactive control networks linked to task switching and mixing effects, and whether strength of connectivity in these networks is associated with behavioural outcomes. Participants (n = 197) completed a cued‐trials task‐switching paradigm with concurrent electroencephalography, after substantial task practice to establish strong cue‐stimulus–response representations. We used inter‐site phase clustering, a measure of functional connectivity across electrode sites, to establish cross‐site connectivity from a frontal and a parietal seed. Distinct theta networks were activated during proactive and reactive control periods. During the preparation interval, mixing effects were associated with connectivity from the frontal seed to parietal sites, and switch effects with connectivity from the parietal seed to occipital sites. Lateralised occipital connectivity was common to both switch and mixing effects. After target onset, frontal and parietal seeds showed a similar pattern of connectivity across trial types. These findings are consistent with distinct and common proactive control networks and common reactive networks in highly practised task‐switching performers. During task‐switching paradigms, both event‐related potentials and time‐frequency analyses show switch and mixing effects at frontal and parietal sites. However, it is not yet known whether mixing and switch costs rely upon common or distinct networks. During the preparation interval, mixing effects were associated with connectivity from the frontal seed to parietal sites, and switch effects with connectivity from the parietal seed to occipital sites.

While it is well accepted that the human brain shifts between internal and external monitoring both during tasks and at rest, no task‐switching studies have focused on brain changes when switching from and to self‐referential processing. Using a cued task‐switching design, we explored the preparatory fMRI activation associated with switching not only within externally oriented tasks, but also within self‐referential tasks, as well as between these two domains. We found that preparing to perform internal tasks activated the default mode network, while preparing for external tasks activated regions of the dorsal attention network (DAN). Switch preparation activated left‐lateralised DAN regions with ventrolateral peaks as well as dorsal precuneus, posterior cingulate and supplementary motor area. These results show a dynamic pattern of communication across networks associated with external and internal domain processing and common preparatory activation in working memory and executive control regions. In particular, the dorsal precuneus was consistently engaged in task‐switch preparation, suggesting a key role of this region in cognitive control, in the context of switching across external and internal domains. We used a cued task switching fMRI study to investigate switches between internally and externally oriented tasks. Switch preparation was associated with activation of frontoparietal areas (especially dorsal precuneus), including regions belonging to the default mode and dorsal attention networks.

In the present study, we introduce a novel, self-organized task-switching paradigm that can be used to study more directly the determinants of switching. Instead of instructing participants to randomly switch between tasks, as in the classic voluntary task-switching paradigm (Arrington & Logan, 2004 ), we instructed participants to optimize their task performance in a voluntary task-switching environment in which the stimulus associated with the previously selected task appeared in each trial after a delay. Importantly, the stimulus onset asynchrony (SOA) increased further with each additional repetition of this task, whereas the stimulus needed for a task switch was always immediately available. We conducted two experiments with different SOA increments (i.e., Exp. 1 a = 50 ms, Exp. 1 b = 33 ms) to see whether this procedure would induce switching behavior, and we explored how people trade off switch costs against the increasing availability of the stimulus needed for a task repetition. We observed that participants adapted their behavior to the different task environments (i.e., SOA increments) and that participants switched tasks when the SOA in task switches approximately matched the switch costs. Moreover, correlational analyses indicated relations between individual switch costs and individual switch rates across participants. Together, these results demonstrate that participants were sensitive to the increased availability of switch stimuli in deciding whether to switch or to repeat, which in turn demonstrates flexible adaptive task selection behavior. We suggest that performance limitations in task switching interact with the task environment to influence switching behavior.

An underlying hypothesis for broad transfer from cognitive training is that the regional brain signals engaged during the training task are related to the transfer tasks. However, it is unclear whether the brain activations elicited from a specific cognitive task can generalize to performance of other tasks, esp. in normal aging where cognitive training holds much promise. In this large dual‐site functional magnetic resonance imaging (fMRI) study, we aimed to characterize the neurobehavioral correlates of task‐switching in normal aging and examine whether the task‐switching‐related fMRI‐blood‐oxygen‐level‐dependent (BOLD) signals, engaged during varieties of cognitive control, generalize to other tasks of executive control and general cognition. We therefore used a hybrid blocked and event‐related fMRI task‐switching paradigm to investigate brain regions associated with multiple types of cognitive control on 129 non‐demented older adults (65–85 years). This large dataset provided a unique opportunity for a data‐driven partial least squares–correlation approach to investigate the generalizability of multiple fMRI‐BOLD signals associated with task‐switching costs to other tasks of executive control, general cognition, and demographic characteristics. While some fMRI signals generalized beyond the scanned task, others did not. Results indicate right middle frontal brain activation as detrimental to task‐switching performance, whereas inferior frontal and caudate activations were related to faster processing speed during the fMRI task‐switching, but activations of these regions did not predict performance on other tasks of executive control or general cognition. However, BOLD signals from the right lateral occipital cortex engaged during the fMRI task positively predicted performance on a working memory updating task, and BOLD signals from the left post‐central gyrus that were disengaged during the fMRI task were related to slower processing speed in the task as well as to lower general cognition. Together, these results suggest generalizability of these BOLD signals beyond the scanned task. The findings also provided evidence for the general slowing hypothesis of aging as most variance in the data were explained by low processing speed and global low BOLD signal in older age. As processing speed shared variance with task‐switching and other executive control tasks, it might be a possible basis of generalizability between these tasks. Additional results support the dedifferentiation hypothesis of brain aging, as right middle frontal activations predicted poorer task‐switching performance. Overall, we observed that the BOLD signals related to the fMRI task not only generalize to the performance of other executive control tasks, but unique brain predictors of out‐of‐scanner performance can be identified. This dual‐site functional magnetic resonance imaging (fMRI) study (n = 129) uses multivariate partial least squares–correlation analysis to examine the relationships between fMRI brain activations from task‐switching and performance on other tasks of executive control functions and general cognition. We found that the brain activations from this fMRI task can predict performance on a broad range of cognitive tasks.

Cognitive task control can be examined in task-switching studies. Performance costs in task switches are usually smaller with compatible stimulus-response modality mappings (visual-manual and auditory-vocal) than with incompatible mappings (visual-vocal and auditory-manual). Modality compatibility describes the modality match of sensory input and of the anticipated response effect (e.g., vocal responses produce auditory effects, so that auditory stimuli are modality-compatible with vocal responses). Fintor et al. ( Psychological Research , 84 (2), 380–388, 2020 ) found that modality compatibility also biased task choice rates in voluntary task switching (VTS). In that study, in each trial participants were presented with a visual or auditory spatial stimulus and were free to choose the response modality (manual vs. vocal). In this free-choice task, participants showed a bias to create more modality-compatible than -incompatible mappings. In the present study, we assessed the generality of Fintor et al.’s ( 2020 ) findings, using verbal rather than spatial stimuli, and more complex tasks, featuring an increased number of stimulus-response alternatives. Experiment 1 replicated the task-choice bias to preferentially create modality-compatible mappings. We also found a bias to repeat the response modality just performed, and a bias to repeat entire stimulus-response modality mappings. In Experiment 2 , we manipulated the response-stimulus interval (RSI) to examine whether more time for proactive cognitive control would help resolve modality-specific crosstalk in this free-choice paradigm. Long RSIs led to a decreased response-modality repetition bias and mapping repetition bias, but the modality-compatibility bias was unaffected. Together, the findings suggest that modality-specific priming of response modality influences task choice.

Cognitive flexibility is commonly studied using the cued and voluntary task-switching paradigms. Given that the cued task contains more exogenous control processes, and the voluntary choice task includes more endogenous control processes, some control transitions between the cued and voluntary choice trials could exist. However, the transitions between the cued and voluntary choice tasks have been largely ignored by prior works. Thus, to fill this gap in the literature, we used a hybrid task-switching paradigm by mixing a cued task with a voluntary task to probe control transitions. We conducted two experiments; each comprised of trials that were grouped into four types of control transitions (i.e., voluntary → cued, voluntary → voluntary, cued → voluntary, and cued → cued). We found a cost associated with control switch and that the control switch possibly facilitated cognitive flexibility, as indicated by the impaired task switch cost and increased voluntary switch rate compared with the control repeat. In addition, we found an asymmetrical control cost between the transition of cued and voluntary choice tasks, with a larger control cost when switching from a difficult to an easier control mode. We also found that the task repeat and task switch trials had an opposite, asymmetrical control cost pattern and were differently modulated by switch probability. Therefore, the findings of the present study broaden our understanding of cognitive flexibility and provide new insights into its underlying mechanisms.

Language switching has been one of the main tasks to investigate language control, a process that restricts bilingual language processing to the target language. In the current review, we discuss the How (i.e., mechanisms) and Where (i.e., locus of these mechanisms) of language control in language switching. As regards the mechanisms of language control, we describe several empirical markers of language switching and their relation to inhibition, as a potentially important mechanism of language control. From this overview it becomes apparent that some, but not all, markers indicate the occurrence of inhibition during language switching and, thus, language control. In a second part, we turn to the potential locus of language control and the role of different processing stages (concept level, lemma level, phonology, orthography, and outside language processing). Previous studies provide evidence for the employment of several of these processing stages during language control so that either a complex control mechanism involving different processing stages and/or multiple loci of language control have to be assumed. Based on the discussed results, several established and new theoretical avenues are considered.

Adaptive behavior requires finding, and adjusting, an optimal tradeoff between focusing on a current task-set (cognitive stability) and updating that task-set when the environment changes (cognitive flexibility). Such dynamic adjustments of cognitive flexibility are observed in cued task-switching paradigms, where switch costs tend to decrease as the proportion of switch trials over blocks increases. However, the learning mechanisms underlying this phenomenon, here referred to as the list-wide proportion switch effect (LWPSE), are currently unknown. We addressed this question across four behavioral experiments. Experiment 1 replicated the basic LWPSE reported in previous studies. Having participants switch between three instead of two tasks, Experiment 2 demonstrated that the LWPSE is preserved even when the specific alternate task to switch to cannot be anticipated. Experiments 3 a and 3 b tested for the generalization of list-wide switch-readiness to an unbiased “transfer task,” presented equally often as switch and repeat trials, by intermixing the transfer task with biased tasks. Despite the list-wide bias, the LWPSE was only found for biased tasks, suggesting that the modulations of switch costs are task set and/or task stimulus (item)-specific. To evaluate these two possibilities, Experiment 4 employed biased versus unbiased stimuli within biased task sets and found switch-cost modulations for both stimuli sets. These results establish how people adapt their stability-flexibility tradeoff to different contexts. Specifically, our findings show that people learn to associate context-appropriate levels of switch readiness with switch-predictive cues, provided by task sets as well as specific task stimuli.

Successful task-switching performance is thought to rely on inhibitory mechanisms suppressing no-longer-relevant tasks, indexed by the n–2 repetition cost. Recent work has shown that episodic retrieval contributes to this cost, confounding estimates of inhibition. This study examines age-related differences in the contributions of inhibition and episodic retrieval to the n–2 repetition cost using a paradigm that controls episodic interference. We also applied the drift diffusion model (DDM) to estimate latent processes underlying these effects. Results showed robust n–2 repetition costs for younger and older adults in response times which reduced when episodic interference was controlled. However, only younger adults showed this pattern in error rates. The DDM showed n–2 repetition costs and their modulation by episodic retrieval were isolated to drift rates, reflecting changes in evidence accumulation. Only younger adults’ drift rates were affected by episodic retrieval, with n–2 repetition costs reduced under episodic match conditions. Older adults showed n–2 repetition costs in drift rate regardless of episodic match, suggesting age-related differences in episodic retrieval at the latent level. The results provide insight into age-related differences in inhibition, the importance of controlling episodic retrieval effects in task switching, and the value of computational modelling in revealing age-related differences.