Proactive and reactive cognitive control and dorsolateral prefrontal cortex dysfunction in first episode schizophrenia.

Cognitive control deficits have been consistently documented in patients with schizophrenia. Recent work in cognitive neuroscience has hypothesized a distinction between two theoretically separable modes of cognitive control-reactive and proactive. However, it remains unclear the extent to which these processes are uniquely associated with dysfunctional neural recruitment in individuals with schizophrenia. This functional magnetic resonance imaging (fMRI) study utilized the color word Stroop task and AX Continuous Performance Task (AX-CPT) to tap reactive and proactive control processes, respectively, in a sample of 54 healthy controls and 43 patients with first episode schizophrenia. Healthy controls demonstrated robust dorsolateral prefrontal, anterior cingulate, and parietal cortex activity on both tasks. In contrast, patients with schizophrenia did not show any significant activation during proactive control, while showing activation similar to control subjects during reactive control. Critically, an interaction analysis showed that the degree to which prefrontal activity was reduced in patients versus controls depended on the type of control process engaged. Controls showed increased dorsolateral prefrontal cortex (DLPFC) and parietal activity in the proactive compared to the reactive control task, whereas patients with schizophrenia did not demonstrate this increase. Additionally, patients' DLPFC activity and performance during proactive control was associated with disorganization symptoms, while no reactive control measures showed this association. Proactive control processes and concomitant dysfunctional recruitment of DLPFC represent robust features of schizophrenia that are also directly associated with symptoms of disorganization

Consistent use of proactive control and relation with academic achievement in childhood

As children become older, they better maintain task-relevant information in preparation of upcoming cognitive demands. This is referred to as proactive control, which is a key component of cognitive control development. However, it is still uncertain whether children engage in proactive control consistently across different contexts and how proactive control relates to academic abilities. This study used two common tasks—the AX Continuous Performance Task (AX-CPT) and the Cued Task-Switching Paradigm (CTS)—to examine whether proactive control engagement in 102 children (age range: 6.91–10.91 years) converges between the two tasks and predicts academic abilities. Proactive control indices modestly correlated between tasks in higher but not lower working-memory children, suggesting that consistency in proactive control engagement across contexts is relatively low during childhood but increases with working memory capacity. Further, working memory (but not verbal speed) predicted proactive control engagement in both tasks. While proactive control as measured by each task predicted math and reading performance, only proactive control measured by CTS additionally predicted reasoning, suggesting that proactive control can be used as a proxy for academic achievements

ELECTROPHYSIOLOGICAL MECHANISMS FOR PREPARING CONTROL IN TIME

Cognitive control is critical in guiding goal-directed behavior, preparing neural resources and adapting processing to promote optimal action in a given environment. According to the Dual Mechanisms of Control theory (Braver, 2012), control can be dichotomized into proactive and reactive modes of control, utilized reciprocally in ahead-of-time preparation versus last-minute, stimulus-evoked reaction. Although a substantial body of work has tested differences between proactive control and reactive control, the underlying assumption of proactive control as a unitary process has not been systematically investigated. Very little is known as to how or when proactive control is initiated, sustained, or implemented. As time is an integral building block of perception, cognition, and action (Buhusi & Meck, 2005), one should expect temporal information to be integrated into proactive control. Cognitive control is costly (Shenhav, Botvinick, & Cohen, 2013), and a temporally-guided modulation of control may offer substantial cost savings. By measuring proactive control on a sub-second time-scale, we can begin to gauge whether dissociable sub-types of proactive control are utilized demanding on temporal demands. Moreover, by comparing proactive control processes across different temporal demands, we can parse out when different aspects of control are computed and implemented. Through a meta-analytic review and three empirical experiments, this dissertation provides insight into how timing dynamics may influence the computation, maintenance, and instantiation of proactive cognitive control. First, a meta-analysis on the cued control literature reveals that seemingly trivial experimental parameters shape the use of proactive versus reactive control. Two EEG studies then demonstrate how modulating timing dynamics influences prefrontal mechanisms for preparatory cognitive control. In a final EEG study, we compare the mechanisms utilized to retain control goals versus visuo-spatial working memory items. Overall, this dissertation elucidates several novel electrophysiological mechanisms by which timing information is implemented in the computation and retention of cognitive control rules. Further, we provide evidence that individual differences in impulsivity and working memory shape distinct aspects of preparation. The findings reported here make clear that timing information is critical in guiding proactive control processes, and support a fundamental reconsideration of proactive control based on temporal dynamics

Control of Spin Dynamics of Excitons in Nanodots for Quantum Operations

This work presents a step furthering a new perspective of proactive control of the spin-exciton dynamics in the quantum limit. Laser manipulation of spin-polarized optical excitations in a semiconductor nanodot is used to control the spin dynamics of two interacting excitons. Shaping of femtosecond laser pulses keeps the quantum operation within the decoherence time. Computation of the fidelity of the operations and application to the complete solution of a basic quantum computing algorithm demonstrate in theory the feasibility of quantum control.Comment: 5 pages, 4 figure

Abnormal proactive and reactive cognitive control during conflict processing in major depression

According to the Dual Mechanisms of Control framework, cognitive control consists of two complementary components: proactive control refers to anticipatory maintenance of goal-relevant information, whereas reactive control acts as a correction mechanism that is activated when a conflict occurs. Possibly, the well-known diminished inhibitory control in response to negative stimuli in Major Depressive Disorder (MDD) patients stems from a breakdown in proactive control, and/or anomalies in reactive cognitive control. In our study, MDD patients specifically showed increased response latencies when actively inhibiting a dominant response to a sad compared with a happy face. This condition was associated with a longer duration of a dominant ERP topography (800-900 ms poststimulus onset) and a stronger activity in the bilateral dorsal anterior cingulate cortex, reflecting abnormal reactive control when inhibiting attention to a negative stimulus. Moreover, MDD patients showed abnormalities in proactive cognitive control when preparing for the upcoming imperative stimulus (abnormal modulation of the contingent negative variation component), accompanied by more activity in brain regions belonging to the default mode network. All together, deficits to inhibit attention to negative information in MDD might originate from an abnormal use of both proactive resources and reactive control processes. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly

Adaptiveness in proactive control engagement in children and adults

Age-related progress in cognitive control reflects more frequent engagement of proactive control during childhood. As proactive preparation for an upcoming task is adaptive only when the task can be reliably predicted, progress in proactive control engagement may rely on more efficient use of contextual cue reliability. Developmental progress may also reflect increasing efficiency in how proactive control is engaged, making this control mode more advantageous with age. To address these possibilities, 6-year-olds, 9-year-olds, and adults completed three versions of a cued task-switching paradigm in which contextual cue reliability was manipulated. When contextual cues were reliable (but not unreliable or uninformative), all age groups showed greater pupil dilation and a more pronounced (pre)cue-locked posterior positivity associated with faster response times, suggesting adaptive engagement of proactive task selection. However, adults additionally showed a larger contingent negative variation (CNV) predicting a further reduction in response times with reliable cues, suggesting motor preparation in adults but not children. Thus, early developing use of contextual cue reliability promotes adaptiveness in proactive control engagement from early childhood; yet, less efficient motor preparation in children makes this control mode overall less advantageous in childhood than adulthood

Temporal dynamics of motivation-cognitive control interactions revealed by high-resolution pupillometry

Motivational manipulations, such as the presence of performance-contingent reward incentives, can have substantial influences on cognitive control. Previous evidence suggests that reward incentives may enhance cognitive performance specifically through increased preparatory, or proactive, control processes. The present study examined reward influences on cognitive control dynamics in the AX-Continuous Performance Task (AX-CPT), using high-resolution pupillometry. In the AX-CPT, contextual cues must be actively maintained over a delay in order to appropriately respond to ambiguous target probes. A key feature of the task is that it permits dissociable characterization of preparatory, proactive control processes (i.e., utilization of context) and reactive control processes (i.e., target-evoked interference resolution). Task performance profiles suggested that reward incentives enhanced proactive control (context utilization). Critically, pupil dilation was also increased on reward incentive trials during context maintenance periods, suggesting trial-specific shifts in proactive control, particularly when context cues indicated the need to overcome the dominant target response bias. Reward incentives had both transient (i.e., trial-by-trial) and sustained (i.e., block-based) effects on pupil dilation, which may reflect distinct underlying processes. The transient pupillary effects were present even when comparing against trials matched in task performance, suggesting a unique motivational influence of reward incentives. These results suggest that pupillometry may be a useful technique for investigating reward motivational signals and their dynamic influence on cognitive control

How Does Anxiety Affect Cognitive Control? Proactive and Reactive Control Under State Anxiety

Cognitive control is a construct that prioritizes how we process stimuli and information and execute behaviors to flexibly and efficiently adapt to internal goals and external environmental changes. A recent theory, the Dual Mechanism of Control (DMC), distinguishes this phenomenon by two distinct cognitive control operations: proactive control and reactive control (Braver, 2012). Anxiety increases the allocation of attentional and working memory resources to threat-related stimuli, which impairs cognitive performance (Sarason, 1988), but additional work is needed to assess how anxiety impacts these two distinct forms of cognitive control. In this study, I examined how state anxiety affected proactive control, using the AX-continuous performance task (AX-CPT), and reactive control, using the classic Stroop task. The results showed that state anxiety inhibited proactive control in AX-CPT test, but increased reactive control in the Stroop task. Ultimately, by completing this study, we will better understand how anxiety impacts the proactive and reactive control

Smart Optimization of Proactive Control of Petroleum Reservoir

Artificial Intelligence plays an increasingly important role in many industrial applications as it has great potential for solving complex engineering problems. One of such applications is the optimization of petroleum reservoirs production. It is crucial to produce hydrocarbons efficiently as their geological resources are limited. From an economic point of view, optimization of hydrocarbon well control is an important factor as it affects the whole market. The solution proposed in this paper is based on state-of-the-art artificial intelligence methods, optimal control, and decision tree theory. The proposed idea is to apply a novel temporal clustering algorithm utilizing an autoencoder for temporal dimensionality reduction and a temporal clustering layer for cluster assignment, to cluster wells into groups depending on the production situation that occurs in the vicinity of the well, which allows reacting proactively. Then the optimal control of wells belonging to specific groups is determined using an auto-adaptive decision tree whose parameters are optimized using a novel sequential model-based algorithm configuration method. Optimization of petroleum reservoirs production translates directly into several economic benefits: reduction in operation costs, increase in the production effectiveness and increase in overall income without any extra expenditure as only control is changed