Learning Cognitive Flexibility: Neural Substrates of Adapting Switch-Readiness to Time-varying Demands.

An individual's readiness to switch tasks (cognitive flexibility) varies over time, in part, as the result of reinforcement learning based on the statistical structure of the world around them. Consequently, the behavioral cost associated with task-switching is smaller in contexts where switching is frequent than where it is rare, but the underlying brain mechanisms of this adaptation in cognitive flexibility are not well understood. Here, we manipulated the likelihood of switches across blocks of trials in a classic cued task-switching paradigm while participants underwent fMRI. As anticipated, behavioral switch costs decreased as the probability of switching increased, and neural switch costs were observed in lateral and medial frontoparietal cortex. To study moment-by-moment adjustments in cognitive flexibility at the neural level, we first fitted the behavioral RT data with reinforcement learning algorithms and then used the resulting trial-wise prediction error estimate as a regressor in a model-based fMRI analysis. The results revealed that lateral frontal and parietal cortex activity scaled positively with unsigned switch prediction error and that there were no brain regions encoding signed (i.e., switch- or repeat-specific) prediction error. Taken together, this study documents that adjustments in cognitive flexibility to time-varying switch demands are mediated by frontoparietal cortex tracking the likelihood of forthcoming task switches.

Resilience as the Ability to Maintain Well-Being: An Allostatic Active Inference Model.

Resilience is often characterized as the outcome of well-being maintenance despite threats to that well-being. We suggest that resilience can also be characterized as an emotional-intelligence-related ability to obtain this outcome. We formulate an allostatic active inference model that outlines the primary tools of this resilience ability as monitoring well-being, maintaining stable well-being beliefs while updating situational beliefs and flexibly prioritizing actions that are expected to lead to well-being maintenance or gathering the information needed to discern what those actions could be. This model helps to explain the role of positive emotions in resilience as well as how people high in resilience ability use regulatory flexibility in the service of maintaining well-being and provides a starting point for assessing resilience as an ability.

The location independence of learned attentional flexibility.

Individuals can adjust their shift readiness, known as attentional flexibility, according to the statistical structure of the environment. However, the extent to which these modulations in attentional flexibility are associated with a global readiness to shift attention to any location versus an anticipated shift to a single location remains unknown. Across two experiments, participants shifted attention among three rapid serial visual presentation (RSVP) streams of alphanumeric characters in response to embedded visual cues and made button presses in response to targets at the cued location. We manipulated the likelihood that participants would receive a cue that signaled a shift between two of the streams across blocks of trials. The likelihood of a cued shift of attention to the third location was held constant across all blocks. Participants demonstrated smaller target detection shift costs (Experiments 1 and 2) and shorter saccade latencies (Experiment 1) when the overall likelihood of shifting was high than when the overall shift likelihood was low. Critically, we observed evidence of both global shift readiness and location-specific shift readiness in both experiments such that participants shifted attention to the most-likely-to-be cued location the fastest, but still demonstrated a difference in the time to shift attention to the unlikely location according to the overall shift likelihood. Our findings provide evidence that moment-by-moment changes in attentional flexibility are not limited to an expectation to shift to a single location, but rather reflect, in part, a location-independent state of control.

Neural Mechanisms of Strategic Adaptation in Attentional Flexibility.

Individuals are able to adjust their readiness to shift spatial attention, referred to as "attentional flexibility," according to the changing demands of the environment, but the neural mechanisms underlying learned adjustments in flexibility are unknown. In the current study, we used fMRI to identify the brain structures responsible for learning shift likelihood. Participants were cued to covertly hold or shift attention among continuous streams of alphanumeric characters and to indicate the parity of target stimuli. Unbeknown to the participants, the stream locations were predictive of the likelihood of having to shift (or hold) attention. Participants adapted their attentional flexibility according to contextual demands, such that the RT cost associated with shifting attention was smallest when shift cues were most likely. Learning model-derived shift prediction error scaled positively with activity within dorsal and ventral frontoparietal regions, documenting that these regions track and update shift likelihood. A complementary inverted encoding model analysis revealed that the pretrial difference in attentional selection strength between to-be-attended and to-be-ignored locations did not change with increasing shift likelihood. The behavioral improvement associated with learned flexibility may primarily arise from a speeding of the shift process rather than from preparatory broadening of attentional selection.

Declarative and procedural working memory updating processes are mutually facilitative.

Executive function, or cognitive control, describes the ability to guide information processing in line with internal goals, but the nature of-and relationship between-the component processes supporting this ability remains poorly understood. Two key components of cognitive control are thought to be the regulation of the declarative contents of working memory (WM) and the selection of task sets, or procedural rules that determine how declarative items are employed. Factor-analytic studies have suggested that updating the items held in WM and updating task sets are cognitively distinct, but interrelated, core domains of executive function. However, the precise relationship between these processes remains unknown, since they have rarely been tested simultaneously in a single task. In the present study, we devised a novel method of independently manipulating declarative item-updating and procedural task-updating processes in WM. Across two experiments, we found that the updating of declarative and procedural WM representations interacted subadditively, suggesting they are not constrained by a common processing bottleneck. Moreover, in a third experiment, we found that updating two declarative items in WM simultaneously did not incur a behavioral cost in response time above and beyond the cost of one item alone. Taken together, our results provide new evidence that the updating of information in declarative and procedural WM is mutually facilitative, such that opening the gate for updating declarative content reduces the time needed to update procedural content, and vice versa.

Information processing biases in the brain: Implications for decision-making and self-governance.

To make behavioral choices that are in line with our goals and our moral beliefs, we need to gather and consider information about our current situation. Most information present in our environment is not relevant to the choices we need or would want to make and thus could interfere with our ability to behave in ways that reflect our underlying values. Certain sources of information could even lead us to make choices we later regret, and thus it would be beneficial to be able to ignore that information. Our ability to exert successful self-governance depends on our ability to attend to sources of information that we deem important to our decision-making processes. We generally assume that, at any moment, we have the ability to choose what we pay attention to. However, recent research indicates that what we pay attention to is influenced by our prior experiences, including reward history and past successes and failures, even when we are not aware of this history. Even momentary distractions can cause us to miss or discount information that should have a greater influence on our decisions given our values. Such biases in attention thus raise questions about the degree to which the choices that we make may be poorly informed and not truly reflect our ability to otherwise exert self-governance.

Correction to: Reduced Value-Driven Attentional Capture among Children with ADHD Compared to Typically Developing Controls.

The authors would like to correct a few minor errors in our article, none of which change the conclusions or interpretations presented.

Reduced Value-Driven Attentional Capture Among Children with ADHD Compared to Typically Developing Controls.

The current study examined whether children with ADHD were more distracted by a stimulus previously associated with reward, but currently goal-irrelevant, than their typically-developing peers. In addition, we also probed the associated cognitive and motivational mechanisms by examining correlations with other behavioral tasks. Participants included 8-12 year-old children with ADHD (n = 30) and typically developing controls (n = 26). Children were instructed to visually search for color-defined targets and received monetary rewards for accurate responses. In a subsequent search task in which color was explicitly irrelevant, we manipulated whether a distractor item appeared in a previously reward-associated color. We examined whether children responded more slowly on trials with the previously-rewarded distractor present compared to trials without this distractor, a phenomenon referred to as value-driven attentional capture (VDAC), and whether children with and without ADHD differed in the extent to which they displayed VDAC. Correlations among working memory performance, immediate reward preference (delay discounting) and attentional capture were also examined. Children with ADHD were significantly less affected by the presence of the previously rewarded distractor than were control participants. Within the ADHD group, greater value-driven attentional capture was associated with poorer working memory. Although both ADHD and control participants were initially distracted by previously reward-associated stimuli, the magnitude of distraction was larger and persisted longer among control participants.

Neural Basis of Cognitive Control over Movement Inhibition: Human fMRI and Primate Electrophysiology Evidence.

Executive control involves the ability to flexibly inhibit or change an action when it is contextually inappropriate. Using the complimentary techniques of human fMRI and monkey electrophysiology in a context-dependent stop signal task, we found a functional double dissociation between the right ventrolateral prefrontal cortex (rVLPFC) and the bi-lateral frontal eye field (FEF). Different regions of rVLPFC were associated with context-based signal meaning versus intention to inhibit a response, while FEF activity corresponded to success or failure of the response inhibition regardless of the stimulus response mapping or the context. These results were validated by electrophysiological recordings in rVLPFC and FEF from one monkey. Inhibition of a planned behavior is therefore likely not governed by a single brain system as had been previously proposed, but instead depends on two distinct neural processes involving different sub-regions of the rVLPFC and their interactions with other motor-related brain regions.

Spontaneous Fluctuations in the Flexible Control of Covert Attention.

Spontaneous fluctuations in cognitive flexibility are characterized by moment-to-moment changes in the efficacy of control over attentional shifts. We used fMRI to investigate the neural correlates in humans of spontaneous fluctuations in readiness to covertly shift attention between two peripheral rapid serial visual presentation streams. Target detection response time (RT) after a shift or hold of covert spatial attention served as a behavioral index of fluctuations in attentional flexibility. In particular, the cost associated with shifting attention compared with holding attention varied as a function of pretrial brain activity in key regions of the default mode network (DMN), but not the dorsal attention network. High pretrial activity within the DMN was associated with a greater increase in shift trial RT relative to hold trial RT, revealing that these areas are associated with a state of attentional stability. Conversely, high pretrial activity within bilateral anterior insula and the presupplementary motor area/supplementary motor area was associated with a greater decrease in shift trial RT relative to hold trial RT, reflecting increased flexibility. Our results importantly clarify the roles of the precuneus, medial prefrontal cortex, and lateral parietal cortex, indicating that reduced activity may not simply indicate greater task engagement, but also, specifically, a readiness to update the focus of attention. Investigation of the neural correlates of spontaneous changes in attentional flexibility may contribute to our understanding of disorders of cognitive control as well as healthy variability in the control of spatial attention. SIGNIFICANCE STATEMENT: Individuals regularly experience fluctuations in preparatory cognitive control that affect performance in everyday life. For example, individuals are able to more quickly initiate a spatial shift of attention at some moments than at others. The current study revealed that pretrial brain activity in specific cortical regions predicted trial-by-trial changes in participants' abilities to flexibly shift the focus of attention. Intrinsically generated fluctuations in brain activity within several key default mode network regions, as well as within the anterior insula and presupplementary/supplementary motor areas, carried behavioral consequences for preparatory attentional control beyond lapses of attentional engagement. Our results are the first to link intrinsic variation in pretrial brain activity to moment-by-moment changes in preparatory attentional control over spatial selection.

Learned states of preparatory attentional control.

Individuals regularly experience fluctuations in the ability to perform cognitive operations. Although previous research has focused on predicting cognitive flexibility from persistent individual traits, as well as from spontaneous fluctuations in neural activity, the role of learning in shaping preparatory attentional control remains poorly understood. Across 3 experiments, we manipulated the statistical regularities of an attentional orienting paradigm to examine whether individuals modulated attentional flexibility, the readiness to perform a spatial shift of attention, across learned contexts. We found evidence of learning-based modulations in preparatory attentional control settings when the probability of shifting the focus of attention differed based on temporally or color-defined contexts. Furthermore, in the case of color-defined contexts, these modulations in preparatory control persisted even after a change in the underlying statistical properties. Our results indicate that dynamic adjustments in preparatory attentional control are sensitive to the underlying statistical regularities of an environment. This finding has implications for understanding disordered patterns of attentional control and how these patterns might be modified with training.

The role of reward prediction in the control of attention.

Previously rewarded stimuli involuntarily capture attention. The learning mechanisms underlying this value-driven attentional capture remain less understood. We tested whether theories of prediction-based associative reward learning explain the conditions under which reward feedback leads to value-based modulations of attentional priority. Across 4 experiments, we manipulated whether stimulus features served as unique predictors of reward outcomes. Participants received monetary rewards for correctly identifying a color-defined target in an initial search task (training phase) and then immediately completed a second, unrewarded visual search task in which color was irrelevant (test phase). In Experiments 1-3, monetary reward followed correct target selection during training, but critically, no target-defining features carried uniquely predictive information about reward outcomes. Under these conditions, we found no evidence of attentional capture by the previous target colors in the subsequent test phase. Conversely, when target colors in the training phase of Experiment 4 carried uniquely predictive information about reward magnitude, we observed significant attentional capture by the previously rewarded color. Our findings show that value-based attentional priority only develops for stimulus features that carry uniquely predictive information about reward, ruling out a purely motivational account and suggesting that mechanisms of reward prediction play an important role in shaping attentional priorities.

Reinforcement learning modulates the stability of cognitive control settings for object selection.

Cognitive flexibility reflects both a trait that reliably differs between individuals and a state that can fluctuate moment-to-moment. Whether individuals can undergo persistent changes in cognitive flexibility as a result of reward learning is less understood. Here, we investigated whether reinforcing a periodic shift in an object selection strategy can make an individual more prone to switch strategies in a subsequent unrelated task. Participants completed two different choice tasks in which they selected one of four objects in an attempt to obtain a hidden reward on each trial. During a training phase, objects were defined by color. Participants received either consistent reward contingencies in which one color was more often rewarded, or contingencies in which the color that was more often rewarded changed periodically and without warning. Following the training phase, all participants completed a test phase in which reward contingencies were defined by spatial location and the location that was more often rewarded remained constant across the entire task. Those participants who received inconsistent contingencies during training continued to make more variable selections during the test phase in comparison to those who received the consistent training. Furthermore, a difference in the likelihood to switch selections on a trial-by-trial basis emerged between training groups: participants who received consistent contingencies during training were less likely to switch object selections following an unrewarded trial and more likely to repeat a selection following reward. Our findings provide evidence that the extent to which priority shifting is reinforced modulates the stability of cognitive control settings in a persistent manner, such that individuals become generally more or less prone to shifting priorities in the future.

Extending Fitts' Law to three-dimensional obstacle-avoidance movements: support for the posture-based motion planning model.

According to Fitts' Law, the time (MT) to move to a target is a linear function of the logarithm of the ratio between the target's distance and width. Although Fitts' Law accurately predicts MTs for direct movements, it does not accurately predict MTs for indirect movements, as when an obstacle intrudes on the direct movement path. To address this limitation, Jax et al. (2007) added an obstacle-intrusion term to Fitts' Law. They accurately predicted MTs around obstacles in two-dimensional (2-D) workspaces, but their model had one more parameter than Fitts' Law did and was merely descriptive. In this study, we addressed these concerns by turning to the mechanistic, posture-based (PB) movement planning model. The PB-based model accounted for almost as much MT variance in a 3-D movement task as the model of Jax et al., with only two parameters, the same number of parameters as in Fitts' Law.