The congruency sequence effect (CSE) describes the finding that congruency effects in classic probes of selective attention (like the Stroop, Simon, and flanker tasks) are smaller following an ...incongruent than following a congruent trial. The past two decades have generated a large literature on determinants and boundary conditions for the CSE and similar, congruency-proportion based modulations of congruency effects. A prolonged and heated theoretical discussion has been guided primarily by a historically motivated dichotomy between "top-down control" versus "associative bottom-up" explanations for these effects. In the present article, I attempt to integrate and contextualize the major empirical findings in this field by arguing that CSEs (and related effects) are best understood as reflecting a composite of multiple levels of learning that differ in their level of abstraction. Specifically, learning does not only involve the trial-by-trial encoding, binding, and cued retrieval of specific stimulus-response associations, but also of more abstract trial features. Moreover, these more abstract trial or event features can be both external, such as the spatial and temporal context in which a stimulus occurs, as well as internal, like the experience of difficulty, and the attentional control settings that were employed in dealing with the stimulus. From this perspective, top-down control and bottom-up priming processes work in concert rather than in opposition. They represent different levels of abstraction in the same learning scheme and they serve a single, common goal: forming memory ensembles that will facilitate fast and appropriate responding to recurring stimuli or events in the environment.
Conflict adaptation—a conflict-triggered improvement in the resolution of conflicting stimulus or response representations—has become a widely used probe of cognitive control processes in both ...healthy and clinical populations. Previous fMRI studies have localized activation foci associated with conflict resolution to dorsolateral PFC (dlPFC). The traditional group analysis approach employed in these studies highlights regions that are, on average, activated during conflict resolution, but does not necessarily reveal areas mediating individual differences in conflict resolution, because between-subject variance is treated as noise. Here, we employed a complementary approach to elucidate the neural bases of variability in the proficiency of conflict-driven cognitive control. We analyzed two independent fMRI data sets of face–word Stroop tasks by using individual variability in the behavioral expression of conflict adaptation as the metric against which brain activation was regressed while controlling for individual differences in mean RT and Stroop interference. Across the two experiments, a replicable neural substrate of individual variation in conflict adaptation was found in ventrolateral PFC (vlPFC), specifically, in the right inferior frontal gyrus,
(BA 47). Unbiased regression estimates showed that variability in activity in this region accounted for ∼40% of the variance in behavioral expression of conflict adaptation across subjects, thus documenting a heretofore unsuspected key role for vlPFC in mediating conflict-driven adjustments in cognitive control. We speculate that vlPFC plays a primary role in conflict control that is supplemented by dlPFC recruitment under conditions of suboptimal performance.
Visual cognition is limited by computational capacity, because the brain can process only a fraction of the visual sensorium in detail, and by the inherent ambiguity of the information entering the ...visual system. Two mechanisms mitigate these burdens: attention prioritizes stimulus processing on the basis of motivational relevance, and expectations constrain visual interpretation on the basis of prior likelihood. Of the two, attention has been extensively investigated while expectation has been relatively neglected. Here, we review recent work that has begun to delineate a neurobiology of visual expectation, and contrast the findings with those of the attention literature, to explore how these two central influences on visual perception overlap, differ and interact.
Negative emotional stimuli activate a broad network of brain regions, including the medial prefrontal (mPFC) and anterior cingulate (ACC) cortices. An early influential view dichotomized these ...regions into dorsal–caudal cognitive and ventral–rostral affective subdivisions. In this review, we examine a wealth of recent research on negative emotions in animals and humans, using the example of fear or anxiety, and conclude that, contrary to the traditional dichotomy, both subdivisions make key contributions to emotional processing. Specifically, dorsal–caudal regions of the ACC and mPFC are involved in appraisal and expression of negative emotion, whereas ventral–rostral portions of the ACC and mPFC have a regulatory role with respect to limbic regions involved in generating emotional responses. Moreover, this new framework is broadly consistent with emerging data on other negative and positive emotions.
Humans show a pervasive bias for processing self- over other-related information, including in working memory (WM), where people prioritize the maintenance of self- (over other-) associated cues. To ...elucidate the neural mechanisms underlying this self-bias, we paired a self- versus other-associated spatial WM task with fMRI and transcranial direct current stimulation (tDCS) of human participants of both sexes. Maintaining self- (over other-) associated cues resulted in enhanced activity in classic WM regions (frontoparietal cortex), and in superior multivoxel pattern decoding of the cue locations from visual cortex. Moreover, ventromedial PFC (VMPFC) displayed enhanced functional connectivity with WM regions during maintenance of self-associated cues, which predicted individuals' behavioral self-prioritization effects. In a follow-up tDCS experiment, we targeted VMPFC with excitatory (anodal), inhibitory (cathodal), or sham tDCS. Cathodal tDCS eliminated the self-prioritization effect. These findings provide strong converging evidence for a causal role of VMPFC in driving self-prioritization effects in WM and provide a unique window into the interaction between social, self-referential processing and high-level cognitive control processes.
People have a strong tendency to attend to self-related stimuli, such as their names. This self-bias extends to the automatic prioritization of arbitrarily self-associated stimuli held in working memory. Since working memory is central to high-level cognition, this bias could influence how we make decisions. It is therefore important to understand the underlying brain mechanisms. Here, we used neuroimaging and noninvasive neurostimulation techniques to show that the source of self-bias in working memory is the ventromedial PFC, which modulates activity in frontoparietal brain regions to produce prioritized representations of self-associated stimuli in sensory cortex. This work thus reveals a brain circuit underlying the socially motivated (self-referential) biasing of high-level cognitive processing.
The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly ...adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences.
A prominent model of how the brain regulates attention proposes that the anterior cingulate cortex monitors the occurrence of conflict between incompatible response tendencies and signals this ...information to a cognitive control system in dorsolateral prefrontal cortex. Cognitive control is thought to resolve conflict through the attentional biasing of perceptual processing, emphasizing task-relevant stimulus information. It is not known, however, whether conflict resolution is mediated by amplifying neural representations of task-relevant information, inhibiting representations of task-irrelevant information, or both. Here we manipulated trial-by-trial levels of conflict and control during a Stroop task using face stimuli, while recording hemodynamic responses from human visual cortex specialized for face processing. We show that, in response to high conflict, cognitive control mechanisms enhance performance by transiently amplifying cortical responses to task-relevant information rather than by inhibiting responses to task-irrelevant information. These results implicate attentional target-feature amplification as the primary mechanism for conflict resolution through cognitive control.
The past two decades have witnessed an explosion of interest in the cognitive and neural mechanisms of adaptive control processes that operate in selective attention tasks. This has spawned not only ...a large empirical literature and several theories but also the recurring identification of potential confounds and corresponding adjustments in task design to create confound-minimized metrics of adaptive control. The resulting complexity of this literature can be difficult to navigate for new researchers entering the field, leading to suboptimal study designs. To remediate this problem, we present here a consensus view among opposing theorists that specifies how researchers can measure four hallmark indices of adaptive control (the congruency sequence effect, and list-wide, context-specific, and item-specific proportion congruency effects) while minimizing easy-to-overlook confounds.
Early putative indices of adaptive control in conflict tasks have spurred not only a great deal of research but also numerous discussions on what these indices actually measure.Recent studies have shown that adaptive control effects can be observed after controlling for low-level confounds. However, many canonical findings in the literature, for instance concerning the functional neuroanatomy of adaptive control, are based on older, confounded designs, and may thus be subject to revision.This research field is now starting to experience a second wave of studies on adaptive control in conflict tasks employing improved designs that allow us to (re)address old and new questions.
Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly ...understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support "dynamic adaptive coding," flexibly representing changing task sets in a trial-by-trial fashion.
Humans can fluently switch between different tasks, reflecting an ability to dynamically configure "task sets," rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior.
Attention, the prioritization of goal-relevant stimuli, and expectation, the modulation of stimulus processing by probabilistic context, represent the two main endogenous determinants of visual ...cognition. Neural selectivity in visual cortex is enhanced for both attended and expected stimuli, but the functional relationship between these mechanisms is poorly understood. Here, we adjudicated between two current hypotheses of how attention relates to predictive processing, namely, that attention either enhances or filters out perceptual prediction errors (PEs), the PE-promotion model versus the PE-suppression model. We acquired fMRI data from category-selective visual regions while human subjects viewed expected and unexpected stimuli that were either attended or unattended. Then, we trained multivariate neural pattern classifiers to discriminate expected from unexpected stimuli, depending on whether these stimuli had been attended or unattended. If attention promotes PEs, then this should increase the disparity of neural patterns associated with expected and unexpected stimuli, thus enhancing the classifier's ability to distinguish between the two. In contrast, if attention suppresses PEs, then this should reduce the disparity between neural signals for expected and unexpected percepts, thus impairing classifier performance. We demonstrate that attention greatly enhances a neural pattern classifier's ability to discriminate between expected and unexpected stimuli in a region- and stimulus category-specific fashion. These findings are incompatible with the PE-suppression model, but they strongly support the PE-promotion model, whereby attention increases the precision of prediction errors. Our results clarify the relationship between attention and expectation, casting attention as a mechanism for accelerating online error correction in predicting task-relevant visual inputs.
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