scholarly journals Frontal midline theta differentiates separate cognitive control strategies while still generalizing the need for cognitive control

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jarrod Eisma ◽  
Eric Rawls ◽  
Stephanie Long ◽  
Russell Mach ◽  
Connie Lamm
Keyword(s):  
Cognitive Control ◽  
Inhibitory Control ◽  
Control Strategy ◽  
Control Strategies ◽  
Response Conflict ◽  
Proactive Control ◽  
Reactive Control ◽  
Theta Power ◽  
Prepotent Response ◽  
Frontal Midline Theta

AbstractCognitive control processes encompass many distinct components, including response inhibition (stopping a prepotent response), proactive control (using prior information to enact control), reactive control (last-minute changing of a prepotent response), and conflict monitoring (choosing between two competing responses). While frontal midline theta activity is theorized to be a general marker of the need for cognitive control, a stringent test of this hypothesis would require a quantitative, within-subject comparison of the neural activation patterns indexing many different cognitive control strategies, an experiment lacking in the current literature. We recorded EEG from 176 participants as they performed tasks that tested inhibitory control (Go/Nogo Task), proactive and reactive control (AX-Continuous Performance Task), and resolving response conflict (Global/Local Task-modified Flanker Task). As activity in the theta (4–8 Hz) frequency band is thought to be a common signature of cognitive control, we assessed frontal midline theta activation underlying each cognitive control strategy. In all strategies, we found higher frontal midline theta power for trials that required more cognitive control (target conditions) versus control conditions. Additionally, reactive control and inhibitory control had higher theta power than proactive control and response conflict, and proactive control had higher theta power than response conflict. Using decoding analyses, we were able to successfully decode control from target trials using classifiers trained exclusively on each of the other strategies, thus firmly demonstrating that theta representations of cognitive control generalize across multiple cognitive control strategies. Our results confirm that frontal midline theta-band activity is a common mechanism for initiating and executing cognitive control, but theta power also differentiates between cognitive control mechanisms. As theta activation reliably differs depending on the cognitive control strategy employed, future work will need to focus on the differential role of theta in differing cognitive control strategies.

scholarly journals Cognitive flexibility improves memory for delayed intentions

2018 ◽  
Author(s):  
Seth R. Koslov ◽  
Arjun Mukerji ◽  
Katlyn Rose Hedgpeth ◽  
Jarrod Lewis-Peacock
Keyword(s):  
Cognitive Control ◽  
Prospective Memory ◽  
Control Strategy ◽  
Control Strategies ◽  
Task Demands ◽  
Attention And Memory ◽  
Proactive Control ◽  
Reactive Control ◽  
Attentional Demands ◽  
Dynamic Task

Cognitive control involves the allocation of cognitive resources in order to successfully navigate and interact with the world. Oftentimes, control involves balancing the demands brought on by performing immediately relevant tasks and those required in order to perform future intended actions. For example, directing attention towards navigating through traffic on a highway while also needing to remember to exit the freeway at a particular street. This ability to delay execution of a goal until the appropriate time in the future is referred to as prospective memory (PM). The dual mechanisms of cognitive control (DMC) framework posits that individuals can use two different strategies to remember an intended action: a proactive control strategy involving working memory maintenance of the goal and monitoring of the environment, or a reactive control strategy relying on timely retrieval of goal information from episodic memory. Previous research on prospective memory has demonstrated that performance improves when individuals engage these control strategies in accordance with the demands of the task environment. However, it is unclear how people select a control strategy, particularly in situations with dynamic task demands. We hypothesized that if people flexibly adapt their strategy in response to changes in the environment, this should facilitate prospective memory. Across two experiments, we asked participants to identify the reappearance of a picture target (a prospective memory intention) while at the same time performing an ongoing visual search task. The attentional demands of the ongoing task were manipulated to monotonically increase or decrease on a moment to moment basis. The selection of control strategies was identified using reaction time costs and neural measures of intention maintenance. Results showed that people fluidly modified control strategies, shifting towards proactive control when the attentional demands decreased, and shifting towards reactive control when attentional demands increased. Critically, these adaptive shifts in control strategy were associated with better prospective memory performance. These results demonstrate that fine-grained control of attention and memory resources serves an adaptive role for remembering to carry out future plans.

scholarly journals Changes in working memory facilitate the transition from reactive to proactive cognitive control during childhood

2019 ◽  
Author(s):  
Sonya V. Troller-Renfree ◽  
George Buzzell ◽  
Nathan A. Fox
Keyword(s):  
Working Memory ◽  
Cognitive Control ◽  
Executive Functions ◽  
Control Strategy ◽  
Neural Activity ◽  
Continuous Performance Task ◽  
Proactive Control ◽  
Reactive Control ◽  
Cross Sectional ◽  
Memory Ability

Cognitive control develops rapidly over the first decade of life, with one of the dominant changes being a transition from reliance on “as-needed” control (reactive control) to a more planful, sustained form of control (proactive control). While the emergence of proactive control is important for adaptive, mature behavior, we know little about how this transition takes place, the neural correlates of this transition, and whether development of executive functions are a precondition for developing the ability to adopt a proactive control strategy. The present study addresses these questions, focusing on the transition from reactive to proactive control in a cross-sectional sample of 79 children – forty-one 5-year-olds and thirty-eight 9-year-olds. Children completed an adapted version of the AX-Continuous Performance Task while electroencephalography was recorded and a standardized executive function battery was administered. Results revealed 5-year-olds predominantly employed reactive strategies, while 9-year-olds used proactive strategies. Critically, use of proactive control was predicted by working memory ability, above and beyond other executive functions. Moreover, when enacting proactive control, greater increases in neural activity underlying working memory updating were observed; links between working memory ability and proactive control strategy use were mediated by such neural activity. Collectively, the results provide convergent evidence that the developmental transition from reactive to proactive control is dependent on neurocognitive development of specific executive functioning skills. Developments in working memory appear to be a precondition for adopting the more mature, and adaptive, proactive control strategy.

Consequences of not planning ahead: Reduced proactive control moderates longitudinal relations between behavioral inhibition and anxiety

2019 ◽  
Author(s):  
Sonya V. Troller-Renfree ◽  
George Buzzell ◽  
Daniel Pine ◽  
Heather Henderson ◽  
Nathan A. Fox
Keyword(s):  
Cognitive Control ◽  
Control Strategy ◽  
Behavioral Inhibition ◽  
Strategy Use ◽  
Anxiety Symptoms ◽  
Continuous Performance Task ◽  
Proactive Control ◽  
Reactive Control ◽  
Increased Risk ◽  
Specific Control

Objective: Children with the temperament of Behavioral Inhibition (BI) face increased risk for developing an anxiety disorder later in life. However, not all children with BI manifest anxiety symptoms, and cognitive-control-strategy use may moderate the pathway between BI and anxiety. Individuals vary widely in the strategy used to instantiate control; the present study examined whether a more planful style of cognitive control (i.e. proactive control) or a more impulsive strategy of control (i.e. reactive control) moderates the association between early BI and later anxiety symptoms.Method: Participants were part of a longitudinal study examining the relations between BI (measured at 2-3 years) and later anxiety symptoms (measured at 13 years). Cognitive control strategy use was assessed at age 13 using the AX variant of the Continuous Performance Task (AX-CPT).Results: BI in toddlerhood significantly predicted increased use of a more reactive cognitive control style in adolescence. Additionally, cognitive control strategy moderated the relation between BI and anxious symptoms, such that reliance on a more reactive strategy predicted higher levels of anxiety for children high in BI.Conclusion: The present study is the first to identify the specific control strategy that increases risk for anxiety. Thus, is it not cognitive control per se, but the specific control strategy children adopt that may increase risk for anxiety later in life. These findings have important implications for future evidence-based interventions given that they suggest an emphasis reducing reactive cognitive control and increasing proactive cognitive control may reduce anxious cognition.

scholarly journals Slower adaptation of control strategies in individuals with high impulsive tendencies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fanny Grisetto ◽  
Yvonne N. Delevoye-Turrell ◽  
Clémence Roger
Keyword(s):  
Control Strategies ◽  
Task Demands ◽  
Proactive Control ◽  
Reactive Control ◽  
Score Distribution ◽  
Individual Level ◽  
Control Processes ◽  
Split Method ◽  
Median Split ◽  
Reactive Processes

AbstractFlexible use of reactive and proactive control according to environmental demands is the key to adaptive behavior. In this study, forty-eight adults performed ten blocks of an AX-CPT task to reveal the strength of proactive control by the calculation of the proactive behavioral index (PBI). They also filled out the UPPS questionnaire to assess their impulsiveness. The median-split method based on the global UPPS score distribution was used to categorize participants as having high (HI) or low (LI) impulsiveness traits. The analyses revealed that the PBI was negatively correlated with the UPPS scores, suggesting that the higher is the impulsiveness, the weaker the dominance of proactive control processes. We showed, at an individual level, that the PBI increased across blocks and suggested that this effect was due to a smaller decrease in reactive control processes. Notably, the PBI increase was slower in the HI group than in the LI group. Moreover, participants who did not adapt to task demands were all characterized as high impulsive. Overall, the current study demonstrates that (1) impulsiveness is associated with less dominant proactive control due to (2) slower adaptation to task demands (3) driven by a stronger reliance on reactive processes. These findings are discussed in regards to pathological populations.

scholarly journals Wearing a bike helmet leads to less cognitive control, revealed by lower frontal midline theta power and risk indifference

2019 ◽  
Vol 56 (12) ◽  
Author(s):  
Barbara Schmidt ◽  
Luisa Kessler ◽  
Clay B. Holroyd ◽  
Wolfgang H. R. Miltner
Keyword(s):  
Cognitive Control ◽  
Theta Power ◽  
Frontal Midline Theta

scholarly journals A selective role for ventromedial subthalamic nucleus in inhibitory control

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Benjamin Pasquereau ◽  
Robert S Turner
Keyword(s):  
Subthalamic Nucleus ◽  
Inhibitory Control ◽  
Impulse Control ◽  
Single Unit ◽  
Single Unit Recording ◽  
Proactive Control ◽  
Reactive Control ◽  
Unit Recording ◽  
Per Se ◽  
Action Inhibition

The subthalamic nucleus (STN) is hypothesized to play a central role in the rapid stopping of movement in reaction to a stop signal. Single-unit recording evidence for such a role is sparse, however, and it remains uncertain how that role relates to the disparate functions described for anatomic subdivisions of the STN. Here we address that gap in knowledge using non-human primates and a task that distinguishes reactive and proactive action inhibition, switching and skeletomotor functions. We found that specific subsets of STN neurons have activity consistent with causal roles in reactive action stopping or switching. Importantly, these neurons were strictly segregated to a ventromedial region of STN. Neurons in other subdivisions encoded task dimensions such as movement per se and proactive control. We propose that the involvement of STN in reactive control is restricted to its ventromedial portion, further implicating this STN subdivision in impulse control disorders.

scholarly journals Proactive Control of Emotional Distraction: An ERP Investigation

2021 ◽  
Author(s):  
◽  
Laura Kranz
Keyword(s):  
Cognitive Control ◽  
Emotional Processing ◽  
Control Mechanisms ◽  
Proactive Control ◽  
Reactive Control ◽  
Frequency Condition ◽  
Distractor Processing ◽  
Early Posterior Negativity ◽  
Distraction Task ◽  
Emotional Distraction

<p>According to the Dual Mechanisms of Control (DMC) framework (Braver, 2012) distraction can be controlled either proactively (i.e., before the onset of a distractor) or reactively (i.e., after the onset of a distractor). Research clearly indicates that, when distractors are emotionally neutral, proactive mechanisms are more effective at controlling distraction than reactive mechanisms. However, whether proactive control mechanisms can control irrelevant emotional distractions as effectively as neutral distraction is not known. In the current thesis I examined cognitive control over emotional distraction. In Experiment 1, I tested whether proactive mechanisms can control emotional distraction as effectively as neutral distraction. Participants completed a distraction task. On each trial, they determined whether a centrally presented target letter (embedded amongst a circle of ‘o’s) was an ‘X’ or an ‘N’, while ignoring peripheral distractors (negative, neutral, or positive images). Distractors were presented on either a low proportion (25%) or a high proportion (75%) of trials, to evoke reactive and proactive cognitive control strategies, respectively. Emotional images (both positive and negative) produced more distraction than neutral images in the low distractor frequency (i.e., reactive control) condition. Critically, emotional distraction was almost abolished in the high distractor frequency condition; emotional images were only slightly more distracting than neutral images, suggesting that proactive mechanisms can control emotional distraction almost as effectively as neutral distraction. In Experiment 2, I replicated and extended Experiment 1. ERPs were recorded while participants completed the distraction task. An early index (the early posterior negativity; EPN) and a late index (the late positive potential; LPP) of emotional processing were examined to investigate the mechanisms by which proactive control minimises emotional distraction. The behavioural results of Experiment 2 replicated Experiment 1, providing further support for the hypothesis that proactive mechanisms can control emotional distractions as effectively as neutral distractions. While proactive control was found to eliminate early emotional processing of positive distractors, it paradoxically did not attenuate late emotional processing of positive distractors. On the other hand, proactive control eliminated late emotional processing of negative distractors. However, the early index of emotional processing was not a reliable index of negative distractor processing under either reactive or proactive conditions. Taken together, my findings show that proactive mechanisms can effectively control emotional distraction, but do not clearly establish the mechanisms by which this occurs.</p>

scholarly journals S140. CHARACTERISTICS OF COGNITIVE CONTROL SPECIALIZATION IN HEALTHY AND PATIENT POPULATIONS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S89-S89
Author(s):  
Anita Kwashie ◽  
Yizhou Ma ◽  
Andrew Poppe ◽  
Deanna Barch ◽  
Cameron Carter ◽  
...  
Keyword(s):  
Reaction Time ◽  
Cognitive Control ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Right Hemisphere ◽  
Group Differences ◽  
Proactive Control ◽  
Reactive Control ◽  
Goal Maintenance ◽  
Posterior Parietal

Abstract Background Cognitive control mechanisms enable an individual to regulate, coordinate, and sequence thoughts and actions to obtain desired outcomes. A theory of control specialization posits that proactive control is necessary for anticipatory planning and goal maintenance and recruits sustained lateral prefrontal activity, whereas reactive control, essential for adapting to transient changes, marshals a more extensive brain network (Braver, 2012). Increased task errors and reduced frontoparietal activity in proactive contexts is observed in severe psychopathology, including schizophrenia (Poppe et al., 2016), leading to the prediction that patients rely on reactive control more when performing such tasks. However, evidence of primate prefrontal ‘switch’ neurons, active during both proactive and reactive contexts, challenges the notion that cognitive control relies on discrete processing networks (Blackman et al., 2016). To examine this contradiction, we sought to characterize the distinctiveness between proactive and reactive control in healthy and patient populations using the Dot Pattern Expectancy Task (DPX). We also examined if a bias toward proactive or reactive control predicted behavioral metrics. Methods 44 individuals with schizophrenia (SZ) and 50 matched healthy controls (HC) completed 4 blocks of the DPX during a 3-Tesla fMRI scan (Poppe et al., 2016). Participants followed the ‘A-then-X’ rule, in which they pressed one button whenever an A cue followed an X probe, and pressed a different button for any other non-target stimulus sequence. We examined bilateral frontoparietal ROIs from the literature for evidence of cognitive control specialization as well as whole-brain analyses. Subsequent nonparametric tests and measures of neural response variation strengthened our interpretations. Participant d’-context (dependent on task accuracy) measured their tendency to engage in proactive control. Results Behavioral data revealed that HC participants showed a greater proclivity for proactive control than did their SZ counterparts. HC reaction time outpaced SZ reaction time in trials requiring successful marshalling of proactive control. Preliminary neuroimaging analyses suggest marginal between-group differences in control specialization. HC specialization appeared to be most apparent in diffuse frontal lateral regions, and bilateral posterior parietal cortex. Within the SZ group, specialization was most evident in bilateral posterior parietal cortex. Between-group control specialization differences were most apparent in right hemisphere frontal regions. Superior frontal gyrus and medial temporal lobe activity during proactive processes accounted for modest variance in d’-context. Discussion There were significant between-group differences in goal maintenance behavioral metrics such as reaction time and a tendency to engage in proactive control. Control specialization occurred more diffusely in controls compared to patient counterparts. However, activity in these regions had minimal ability to predict behavioral metrics. Overall, the relatively small size of control-specific areas compared to regions involved in dual processing offers support for the malleable nature of regions implicated in human cognitive control.

scholarly journals Metacognitive Processes in Executive Control Development: The Case of Reactive and Proactive Control

2015 ◽  
Vol 27 (6) ◽  
pp. 1125-1136 ◽  
Author(s):  
Nicolas Chevalier ◽  
Shaina Bailey Martis ◽  
Tim Curran ◽  
Yuko Munakata
Keyword(s):  
Young Children ◽  
Cognitive Control ◽  
Task Switching ◽  
Executive Control ◽  
Target Onset ◽  
Proactive Control ◽  
Older Children ◽  
Reactive Control ◽  
Critical Aspect ◽  
Metacognitive Processes

Young children engage cognitive control reactively in response to events, rather than proactively preparing for events. Such limitations in executive control have been explained in terms of fundamental constraints on children's cognitive capacities. Alternatively, young children might be capable of proactive control but differ from older children in their metacognitive decisions regarding when to engage proactive control. We examined these possibilities in three conditions of a task-switching paradigm, varying in whether task cues were available before or after target onset. RTs, ERPs, and pupil dilation showed that 5-year-olds did engage in advance preparation, a critical aspect of proactive control, but only when reactive control was made more difficult, whereas 10-year-olds engaged in proactive control whenever possible. These findings highlight metacognitive processes in children's cognitive control, an understudied aspect of executive control development.

scholarly journals Cognitive Control in Young and Older Adults: Does Mood Matter?

2021 ◽  
Vol 12 (1) ◽  
pp. 50
Author(s):  
Linda Truong ◽  
Kesaan Kandasamy ◽  
Lixia Yang
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Control ◽  
Mood Induction ◽  
Control Mode ◽  
Proactive Control ◽  
Reactive Control ◽  
Age Related ◽  
Control Framework ◽  
Neutral Mood

The dual mechanisms of control framework (DMC) proposes two modes of cognitive control: proactive and reactive control. In anticipation of an interference event, young adults primarily use a more proactive control mode, whereas older adults tend to use a more reactive one during the event, due to age-related deficits in working memory. The current study aimed to examine the effects of mood induction on cognitive control mode in older (ages 65+) compared to young adults (ages 18–30) with a standard letter-cue (Experiment 1) and a modified face-cue AX-CPT (Experiment 2). Mood induction into negative and/or positive mood versus neutral mood was conducted prior to the cognitive control task. Experiment 1 replicated the typical pattern of proactive control use in young adults and reactive control use in older adults. In Experiment 2, older adults showed comparable proactive control to young adults in their response time (RT). Mood induction showed little effect on cognitive control across the two experiments. These results did not reveal consistent effects of mood (negative or positive) on cognitive control mode in young and older adults, but discovered (or demonstrated) that older adults can engage proactive control when dichotomous face cues (female or male) are used in AX-CPT.

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