Parsing state mindfulness effects on neurobehavioral markers of cognitive control: A within-subject comparison of focused attention and open monitoring.

Over the past two decades, scientific interest in understanding the relationship between mindfulness and cognition has accelerated. However, despite considerable investigative efforts, pervasive methodological inconsistencies within the literature preclude a thorough understanding of whether or how mindfulness influences core cognitive functions. The purpose of the current study is to provide an initial "proof-of-concept" demonstration of a new research strategy and methodological approach designed to address previous limitations. Specifically, we implemented a novel fully within-subject state induction protocol to elucidate the neurobehavioral influence of discrete mindfulness states-focused attention (FA) and open monitoring (OM), compared against an active control-on well-established behavioral and ERP indices of executive attention and error monitoring assessed during the Eriksen flanker task. Bayesian mixed modeling was used to test preregistered hypotheses pertaining to FA and OM effects on flanker interference, the stimulus-locked P3, and the response-locked ERN and Pe. Results yielded strong but unexpected evidence that OM selectively produced a more cautious and intentional response style, characterized by higher accuracy, slower RTs, and reduced P3 amplitude. Follow-up exploratory analyses revealed that trait mindfulness moderated the influence of OM, such that individuals with greater trait mindfulness responded more cautiously and exhibited higher trial accuracy and smaller P3s. Neither FA nor OM modulated the ERN or Pe. Taken together, our findings support the promise of our approach, demonstrating that theoretically distinct mindfulness states are functionally dissociable among mindfulness-naive participants and that interactive variability associated with different operational facets of mindfulness (i.e., state vs. trait) can be modeled directly.

On the psychometric evaluation of cognitive control tasks: An Investigation with the Dual Mechanisms of Cognitive Control (DMCC) battery.

The domain of cognitive control has been a major focus of experimental, neuroscience, and individual differences research. Currently, however, no theory of cognitive control successfully unifies both experimental and individual differences findings. Some perspectives deny that there even exists a unified psychometric cognitive control construct to be measured at all. These shortcomings of the current literature may reflect the fact that current cognitive control paradigms are optimized for the detection of within-subject experimental effects rather than individual differences. In the current study, we examine the psychometric properties of the Dual Mechanisms of Cognitive Control (DMCC) task battery, which was designed in accordance with a theoretical framework that postulates common sources of within-subject and individual differences variation. We evaluated both internal consistency and test-retest reliability, and for the latter, utilized both classical test theory measures (i.e., split-half methods, intraclass correlation) and newer hierarchical Bayesian estimation of generative models. Although traditional psychometric measures suggested poor reliability, the hierarchical Bayesian models indicated a different pattern, with good to excellent test-retest reliability in almost all tasks and conditions examined. Moreover, within-task, between-condition correlations were generally increased when using the Bayesian model-derived estimates, and these higher correlations appeared to be directly linked to the higher reliability of the measures. In contrast, between-task correlations remained low regardless of theoretical manipulations or estimation approach. Together, these findings highlight the advantages of Bayesian estimation methods, while also pointing to the important role of reliability in the search for a unified theory of cognitive control.

The multi-angle extended three-dimensional activities (META) stimulus set: A tool for studying event cognition.

To study complex human activity and how it is perceived and remembered, it is valuable to have large-scale, well-characterized stimuli that are representative of such activity. We present the Multi-angle Extended Three-dimensional Activities (META) stimulus set, a structured and highly instrumented set of extended event sequences performed in naturalistic settings. Performances were captured with two color cameras and a Kinect v2 camera with color and depth sensors, allowing the extraction of three-dimensional skeletal joint positions. We tracked the positions and identities of objects for all chapters using a mixture of manual coding and an automated tracking pipeline, and hand-annotated the timings of high-level actions. We also performed an online experiment to collect normative event boundaries for all chapters at a coarse and fine grain of segmentation, which allowed us to quantify event durations and agreement across participants. We share these materials publicly to advance new discoveries in the study of complex naturalistic activity.

A Representational Similarity Analysis of Cognitive Control during Color-Word Stroop.

Progress in understanding the neural bases of cognitive control has been supported by the paradigmatic color-word Stroop task, in which a target response (color name) must be selected over a more automatic, yet potentially incongruent, distractor response (word). For this paradigm, models have postulated complementary coding schemes: dorsomedial frontal cortex (DMFC) is proposed to evaluate the demand for control via incongruency-related coding, whereas dorsolateral PFC (DLPFC) is proposed to implement control via goal and target-related coding. Yet, mapping these theorized schemes to measured neural activity within this task has been challenging. Here, we tested for these coding schemes relatively directly, by decomposing an event-related color-word Stroop task via representational similarity analysis. Three neural coding models were fit to the similarity structure of multivoxel patterns of human fMRI activity, acquired from 65 healthy, young-adult males and females. Incongruency coding was predominant in DMFC, whereas both target and incongruency coding were present with indistinguishable strength in DLPFC. In contrast, distractor information was strongly encoded within early visual cortex. Further, these coding schemes were differentially related to behavior: individuals with stronger DLPFC (and lateral posterior parietal cortex) target coding, but weaker DMFC incongruency coding, exhibited less behavioral Stroop interference. These results highlight the utility of the representational similarity analysis framework for investigating neural mechanisms of cognitive control and point to several promising directions to extend the Stroop paradigm.SIGNIFICANCE STATEMENT How the human brain enables cognitive control - the ability to override behavioral habits to pursue internal goals - has been a major focus of neuroscience research. This ability has been frequently investigated by using the Stroop color-word naming task. With the Stroop as a test-bed, many theories have proposed specific neuroanatomical dissociations, in which medial and lateral frontal brain regions underlie cognitive control by encoding distinct types of information. Yet providing a direct confirmation of these claims has been challenging. Here, we demonstrate that representational similarity analysis, which estimates and models the similarity structure of brain activity patterns, can successfully establish the hypothesized functional dissociations within the Stroop task. Representational similarity analysis may provide a useful approach for investigating cognitive control mechanisms.

Dorsal Anterior Cingulate Cortex Encodes the Integrated Incentive Motivational Value of Cognitive Task Performance.

Humans can seamlessly combine value signals from diverse motivational incentives, yet it is not well understood how these signals are "bundled" in the brain to modulate cognitive control. The dorsal ACC (dACC) is theorized to integrate motivational value dimensions in the service of goal-directed action, although this hypothesis has yet to receive rigorous confirmation. In the present study, we examined the role of human dACC in motivational incentive integration. Healthy young adult men and women were scanned with fMRI while engaged in an experimental paradigm that quantifies the combined effects of liquid (e.g., juice, neutral, saltwater) and monetary incentives on cognitive task performance. Monetary incentives modulated trial-by-trial dACC activation, whereas block-related effects of liquid incentives on dACC activity were observed. When bundled together, incentive-related dACC modulation predicted fluctuations in both cognitive performance and self-report motivation ratings. Statistical mediation analyses suggest that dACC encoded the incentives in terms of their integrated subjective motivational value, and that this value signal was most proximally associated with task performance. Finally, we confirmed that these incentive integration effects were selectively present in dACC. Together, the results support an account in which dACC integrates motivational signals to compute the expected value of goal-directed cognitive control.SIGNIFICANCE STATEMENT How are primary and secondary incentives integrated in the brain to influence goal-directed behavior? Using an innovative experimental fMRI paradigm that combines motivational incentives that have historically been studied independently between species (e.g., monetary rewards for humans, food rewards for animals), we examine the relationship between incentive motivational value and cognitive control allocation. We find evidence that the integrated incentive motivational value of combined incentives is encoded in human dorsal ACC. Further, self-reported motivational shifts mediated the effects of incentive-modulated dorsal ACC activity on task performance, revealing convergence in how self-reported and experimentally induced motivation are encoded in the human brain. Our findings may inform future translational studies examining affective/motivational and cognitive impairments in psychopathology (e.g., anxiety, depression, addiction).

Enhancing task fMRI preprocessing via individualized model-based filtering of intrinsic activity dynamics.

Brain responses recorded during fMRI are thought to reflect both rapid, stimulus-evoked activity and the propagation of spontaneous activity through brain networks. In the current work, we describe a method to improve the estimation of task-evoked brain activity by first "filtering-out the intrinsic propagation of pre-event activity from the BOLD signal. We do so using Mesoscale Individualized NeuroDynamic (MINDy; Singh et al. 2020b) models built from individualized resting-state data to subtract the propagation of spontaneous activity from the task-fMRI signal (MINDy-based Filtering). After filtering, time-series are analyzed using conventional techniques. Results demonstrate that this simple operation significantly improves the statistical power and temporal precision of estimated group-level effects. Moreover, use of MINDy-based filtering increased the similarity of neural activation profiles and prediction accuracy of individual differences in behavior across tasks measuring the same construct (cognitive control). Thus, by subtracting the propagation of previous activity, we obtain better estimates of task-related neural effects.

We need to be braver about the generalizability crisis.

We applaud the effort to draw attention to generalizability concerns in twenty-first-century psychological research. Yet we do not feel that a pessimistic perspective is warranted. We outline a continuum of available methodological tools and perspectives, including incremental steps and meta-analytic approaches that can be readily and easily deployed by researchers to advance generalizability claims in a forward-looking manner.

Developing control-theoretic objectives for large-scale brain dynamics and cognitive enhancement.

The development of technologies for brain stimulation provides a means for scientists and clinicians to directly actuate the brain and nervous system. Brain stimulation has shown intriguing potential in terms of modifying particular symptom clusters in patients and behavioral characteristics of subjects. The stage is thus set for optimization of these techniques and the pursuit of more nuanced stimulation objectives, including the modification of complex cognitive functions such as memory and attention. Control theory and engineering will play a key role in the development of these methods, guiding computational and algorithmic strategies for stimulation. In particular, realizing this goal will require new development of frameworks that allow for controlling not only brain activity, but also latent dynamics that underlie neural computation and information processing. In the current opinion, we review recent progress in brain stimulation and outline challenges and potential research pathways associated with exogenous control of cognitive function.

The Dual Mechanisms of Cognitive Control Project.

We describe an ambitious ongoing study that has been strongly influenced and inspired by Don Stuss's career-long efforts to identify key cognitive processes that characterize executive control, investigate potential unifying dimensions that define prefrontal function, and carefully attend to individual differences. The Dual Mechanisms of Cognitive Control project tests a theoretical framework positing two key control dimensions: proactive and reactive. The framework's central tenets are that proactive and reactive control modes reflect domain-general dimensions of individual variation, with distinctive neural signatures, involving the lateral pFC as a central node within associated brain networks (e.g., fronto-parietal, cingulo-opercular). In the Dual Mechanisms of Cognitive Control project, each participant is scanned while performing theoretically targeted variants of multiple well-established cognitive control tasks (Stroop, cued task-switching, AX-CPT, Sternberg working memory) in three separate imaging sessions, that each encourages utilization of different control modes plus also completes an extensive out-of-scanner individual differences battery. Additional key features of the project include a high spatio-temporal resolution (multiband) acquisition protocol and a sample that includes a substantial subset of monozygotic twin pairs and participants recruited from the Human Connectome Project. Although data collection is still continuing (target n = 200), we provide an overview of the study design and protocol, along with initial results (n = 80) revealing evidence of a domain-general neural signature of cognitive control and its modulation under reactive conditions. Aligned with Don Stuss's legacy of scientific community building, a partial data set has been publicly released, with the full data set released at project completion, so it can serve as a valuable resource.

The role of neural load effects in predicting individual differences in working memory function.

Studies of working memory (WM) function have tended to adopt either a within-subject approach, focusing on effects of load manipulations, or a between-subjects approach, focusing on individual differences. This dichotomy extends to WM neuroimaging studies, with different neural correlates being identified for within- and between-subjects variation in WM. Here, we examined this issue in a systematic fashion, leveraging the large-sample Human Connectome Project dataset, to conduct a well-powered, whole-brain analysis of the N-back WM task. We first demonstrate the advantages of parcellation schemes for dimension reduction, in terms of load-related effect sizes. This parcel-based approach is then utilized to directly compare the relationship between load-related (within-subject) and behavioral individual differences (between-subject) effects through both correlational and predictive analyses. The results suggest a strong linkage of within-subject and between-subject variation, with larger load-effects linked to stronger brain-behavior correlations. In frontoparietal cortex no hemispheric biases were found towards one type of variation, but the Dorsal Attention Network did exhibit greater sensitivity to between over within-subjects variation, whereas in the Somatomotor network, the reverse pattern was observed. Cross-validated predictive modeling capitalizing on this tight relationship between the two effects indicated greater predictive power for load-activated than load-deactivated parcels, while also demonstrating that load-related effect size can serve as an effective guide to feature (i.e., parcel) selection, in maximizing predictive power while maintaining interpretability. Together, the findings demonstrate an important consistency across within- and between-subjects approaches to identifying the neural substrates of WM, which can be effectively harnessed to develop more powerful predictive models.

Frontoparietal pattern similarity analyses of cognitive control in monozygotic twins.

The ability to flexibly adapt thoughts and actions in a goal-directed manner appears to rely on cognitive control mechanisms that are strongly impacted by individual differences. A powerful research strategy for investigating the nature of individual variation is to study monozygotic (identical) twins. Evidence of twin effects have been observed in prior behavioral and neuroimaging studies, yet within the domain of cognitive control, it remains to be demonstrated that the neural underpinnings of such effects are specific and reliable. Here, we utilize a multi-task, within-subjects event-related neuroimaging design with functional magnetic resonance imaging to investigate twin effects through multivariate pattern similarity analyses. We focus on fronto-parietal brain regions exhibiting consistently increased activation associated with cognitive control demands across four task domains: selective attention, context processing, multi-tasking, and working memory. Healthy young adult monozygotic twin pairs exhibited increased similarity of within- and cross-task activation patterns in these fronto-parietal regions, relative to unrelated pairs. Twin activation pattern similarity effects were clearest under high control demands, were not present in a set of task-unrelated parcels or due to anatomic similarity, and were primarily observed during the within-trial timepoints in which the control demands peaked. Together, these results indicate that twin similarity in the neural representation of cognitive control may be domain-general but also functionally and temporally specific in relation to the level of control demand. The findings suggest a genetic and/or environmental basis for individual variation in cognitive control function, and highlight the potential of twin-based neuroimaging designs for exploring heritability questions within this domain.

Pattern Similarity Analyses of FrontoParietal Task Coding: Individual Variation and Genetic Influences.

Pattern similarity analyses are increasingly used to characterize coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task functional magnetic resonance imaging (fMRI) dataset to examine individual differences and genetic influences on the coding of working memory load (0-back, 2-back) and perceptual category (Face, Place). Participants were grouped into 105 monozygotic twin, 78 dizygotic twin, 99 nontwin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load coding and in Visual only for perceptual coding. Further, in related pairs, the similarity of load coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key coding and heritability features of brain regions.

Exploring brain-behavior relationships in the N-back task.

Working memory (WM) function has traditionally been investigated in terms of two dimensions: within-individual effects of WM load, and between-individual differences in task performance. In human neuroimaging studies, the N-back task has frequently been used to study both. A reliable finding is that activation in frontoparietal regions exhibits an inverted-U pattern, such that activity tends to decrease at high load levels. Yet it is not known whether such U-shaped patterns are a key individual differences factor that can predict load-related changes in task performance. The current study investigated this question by manipulating load levels across a much wider range than explored previously (N â€‹= â€‹1-6), and providing a more comprehensive examination of brain-behavior relationships. In a sample of healthy young adults (n â€‹= â€‹57), the analysis focused on a distinct region of left lateral prefrontal cortex (LPFC) identified in prior work to show a unique relationship with task performance and WM function. In this region it was the linear slope of load-related activity, rather than the U-shaped pattern, that was positively associated with individual differences in target accuracy. Comprehensive supplemental analyses revealed the brain-wide selectivity of this pattern. Target accuracy was also independently predicted by the global resting-state connectivity of this LPFC region. These effects were robust, as demonstrated by cross-validation analyses and out-of-sample prediction, and also critically, were primarily driven by the high-load conditions. Together, the results highlight the utility of high-load conditions for investigating individual differences in WM function.

Estimation and validation of individualized dynamic brain models with resting state fMRI.

A key challenge for neuroscience is to develop generative, causal models of the human nervous system in an individualized, data-driven manner. Previous initiatives have either constructed biologically-plausible models that are not constrained by individual-level human brain activity or used data-driven statistical characterizations of individuals that are not mechanistic. We aim to bridge this gap through the development of a new modeling approach termed Mesoscale Individualized Neurodynamic (MINDy) modeling, wherein we fit nonlinear dynamical systems models directly to human brain imaging data. The MINDy framework is able to produce these data-driven network models for hundreds to thousands of interacting brain regions in just 1-3 â€‹min per subject. We demonstrate that the models are valid, reliable, and robust. We show that MINDy models are predictive of individualized patterns of resting-state brain dynamical activity. Furthermore, MINDy is better able to uncover the mechanisms underlying individual differences in resting state activity than functional connectivity methods.

Reward motivation and neurostimulation interact to improve working memory performance in healthy older adults: A simultaneous tDCS-fNIRS study.

Several studies have evaluated the effect of anodal transcranial direct current stimulation (tDCS) over the prefrontal cortex (PFC) for the enhancement of working memory (WM) performance in healthy older adults. However, the mixed results obtained so far suggest the need for concurrent brain imaging, in order to more directly examine tDCS effects. The present study adopted a continuous multimodal approach utilizing functional near-infrared spectroscopy (fNIRS) to examine the interactive effects of tDCS combined with manipulations of reward motivation. Twenty-one older adults (mean age = 69.7 years; SD = 5.05) performed an experimental visuo-spatial WM task before, during and after the delivery of 1.5 mA anodal tDCS/sham over the left prefrontal cortex (PFC). During stimulation, participants received performance-contingent reward for every fast and correct response during the WM task. In both sessions, hemodynamic activity of the bilateral frontal, motor and parietal areas was recorded across the entire duration of the WM task. Cognitive functions and reward sensitivity were also assessed with standard measures. Results demonstrated a significant impact of tDCS on both WM performance and hemodynamic activity. Specifically, faster responses in the WM task were observed both during and after anodal tDCS, while no differences were found under sham control conditions. However, these effects emerged only when taking into account individual visuo-spatial WM capacity. Additionally, during and after the anodal tDCS, increased hemodynamic activity relative to sham was observed in the bilateral PFC, while no effects of tDCS were detected in the motor and parietal areas. These results provide the first evidence of tDCS-dependent functional changes in PFC activity in healthy older adults during the execution of a WM task. Moreover, they highlight the utility of combining reward motivation with prefrontal anodal tDCS, as a potential strategy to improve WM efficiency in low performing healthy older adults.

Age-Related Differences in Motivational Integration and Cognitive Control.

Motivational incentives play an influential role in value-based decision-making and cognitive control. A compelling hypothesis in the literature suggests that the motivational value of diverse incentives are integrated in the brain into a common currency value signal that influences decision-making and behavior. To investigate whether motivational integration processes change during healthy aging, we tested older (N = 44) and younger (N = 54) adults in an innovative incentive integration task paradigm that establishes dissociable and additive effects of liquid (e.g., juice, neutral, saltwater) and monetary incentives on cognitive task performance. The results reveal that motivational incentives improve cognitive task performance in both older and younger adults, providing novel evidence demonstrating that age-related cognitive control deficits can be ameliorated with sufficient incentive motivation. Additional analyses revealed clear age-related differences in motivational integration. Younger adult task performance was modulated by both monetary and liquid incentives, whereas monetary reward effects were more gradual in older adults and more strongly impacted by trial-by-trial performance feedback. A surprising discovery was that older adults shifted attention from liquid valence toward monetary reward throughout task performance, but younger adults shifted attention from monetary reward toward integrating both monetary reward and liquid valence by the end of the task, suggesting differential strategic utilization of incentives. These data suggest that older adults may have impairments in incentive integration and employ different motivational strategies to improve cognitive task performance. The findings suggest potential candidate neural mechanisms that may serve as the locus of age-related change, providing targets for future cognitive neuroscience investigations.

Intertemporal Decision-Making Involves Prefrontal Control Mechanisms Associated with Working Memory.

Intertemporal decision-making involves simultaneous evaluation of both the magnitude and delay to reward, which may require the integrated representation and comparison of these dimensions within working memory (WM). In the current study, neural activation associated with intertemporal decision-making was directly compared with WM load-related activation. During functional magnetic resonance imaging, participants performed an intermixed series of WM trials and intertemporal decision-making trials both varying in load, with the latter in terms of choice difficulty, via options tailored to each participant's subjective value function for delayed rewards. The right anterior prefrontal cortex (aPFC) and dorsolateral prefrontal cortex (dlPFC) showed activity modulation by choice difficulty within WM-related brain regions. In aPFC, these 2 effects (WM, choice difficulty) correlated across individuals. In dlPFC, activation increased with choice difficulty primarily in patient (self-controlled) individuals, and moreover was strongest when the delayed reward was chosen on the most difficult trials. Finally, the choice-difficulty effects in dlPFC and aPFC were correlated across individuals, suggesting a functional relationship between the 2 regions. Together, these results suggest a more precise account of the relationship between WM and intertemporal decision-making that is specifically tied to choice difficulty, and involves the coordinated activation of a lateral PFC circuit supporting successful self-control.

Age-related changes in neural mechanisms of prospective memory.

The capability to remember and execute intentions in the future - termed prospective memory (PM) - may be of special significance for older adults to enable successful completion of important activities of daily living. Despite the importance of this cognitive function, mixed findings have been obtained regarding age-related decline in PM, and, currently, there is limited understanding of potential contributing mechanisms. In the current study, older (N=41) and younger adults (N=47) underwent task-functional MRI during performance of PM conditions that encouraged either spontaneous retrieval (Focal) or sustained attentional monitoring (Non-focal) to detect PM targets. Older adults exhibited a reduction in PM-related sustained activity within the anterior prefrontal cortex (aPFC) and associated dorsal frontoparietal cognitive control network, due to an increase in non-specific sustained activation in (no-PM) control blocks (i.e., an age-related compensatory shift). Transient PM-trial specific activity was observed in both age groups within a ventral parietal memory network that included the precuneus. However, within a left posterior inferior parietal node of this network, transient PM-related activity was selectively reduced in older adults during the non-focal condition. These age differences in sustained and transient brain activity statistically mediated age-related declines in PM performance, and were potentially linked via age-related changes in functional connectivity between the aPFC and precuneus. Together, they support an account consistent with the Dual Mechanisms of Control framework, in which age-related PM declines are due to neural mechanisms that support proactive cognitive control processes, such as sustained attentional monitoring, while leaving reactive control mechanisms relatively spared.

The Behavioral Relevance of Task Information in Human Prefrontal Cortex.

Human lateral prefrontal cortex (LPFC) is thought to play a critical role in enabling cognitive flexibility, particularly when performing novel tasks. However, it remains to be established whether LPFC representation of task-relevant information in such situations actually contributes to successful performance. We utilized pattern classification analyses of functional MRI activity to identify novelty-sensitive brain regions as participants rapidly switched between performance of 64 complex tasks, 60 of which were novel. In three of these novelty-sensitive regions-located within distinct areas of left anterior LPFC-trial-evoked activity patterns discriminated correct from error trials. Further, these regions also contained information regarding the task-relevant decision rule, but only for successfully performed trials. This suggests that left anterior LPFC may be particularly important for representing task information that contributes to the cognitive flexibility needed to perform successfully in novel task situations.

Reward Motivation Enhances Task Coding in Frontoparietal Cortex.

Reward motivation often enhances task performance, but the neural mechanisms underlying such cognitive enhancement remain unclear. Here, we used a multivariate pattern analysis (MVPA) approach to test the hypothesis that motivation-related enhancement of cognitive control results from improved encoding and representation of task set information. Participants underwent two fMRI sessions of cued task switching, the first under baseline conditions, and the second with randomly intermixed reward incentive and no-incentive trials. Information about the upcoming task could be successfully decoded from cue-related activation patterns in a set of frontoparietal regions typically associated with task control. More critically, MVPA classifiers trained on the baseline session had significantly higher decoding accuracy on incentive than non-incentive trials, with decoding improvement mediating reward-related enhancement of behavioral performance. These results strongly support the hypothesis that reward motivation enhances cognitive control, by improving the discriminability of task-relevant information coded and maintained in frontoparietal brain regions.