Draft:Dual Mechanisms of Cognitive Control Theory

Submission declined on 11 December 2025 by Fermiboson (talk). This submission reads more like an essay than an encyclopedia article. Submissions should summarise information in secondary, reliable sources and not contain opinions or original research. Please write about the topic from a neutral point of view in an encyclopedic manner. If you would like to continue working on the submission, click on the "Edit" tab at the top of the window. If you have not resolved the issues listed above, your draft will be declined again and potentially deleted. If you need extra help, please ask us a question at the AfC Help Desk or get live help from experienced editors. Please do not remove reviewer comments or this notice until the submission is accepted. Where to get help If you need help editing or submitting your draft, please ask us a question at the AfC Help Desk or get live help from experienced editors. These venues are only for help with editing and the submission process, not to get reviews. If you need feedback on your draft, or if the review is taking a lot of time, you can try asking for help on the talk page of a relevant WikiProject. Some WikiProjects are more active than others so a speedy reply is not guaranteed. How to improve a draft Wikipedia:Contributing to Wikipedia – a basic overview on how to edit Wikipedia. Help:Wikitext – how to use the markup Help:Referencing for beginners – how to include references Wikipedia:Article development – how to develop your article Wikipedia:Writing better articles – how to improve your article Wikipedia:Verifiability – make sure your article includes reliable third-party sources You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Add tags to your draft Editor resources Easy tools: Citation bot (help) | Advanced: Fix bare URLs Declined by Fermiboson 5 days ago. Last edited by Fermiboson 5 days ago. Reviewer: Inform author. Resubmit Please note that if the issues are not fixed, the draft will be declined again.

Submission declined on 10 December 2025 by Somepinkdude (talk). Your draft shows signs of having been generated by a large language model, such as ChatGPT. Wikipedia guidelines prohibit the use of LLMs to write articles from scratch. In addition, LLM-generated articles usually have multiple quality issues, to include: Promotional tone, editorializing and other words to watch Vague, generic, and speculative statements extrapolated from similar subjects Essay-like writing Hallucinations (plausible-sounding, but false information) and non-existent references Close paraphrasing Please address these issues. The best way is usually to read reliable sources and summarize them, instead of using a large language model. See our help page on large language models. Declined by Somepinkdude 7 days ago.

• Comment: I doubt this is entirely unreviewed AI given that out of the 10 papers I read, none failed verification, and quite frankly if you were going to give us unreviewed LLM content in the form of this formatting, I doubt you would've gone to the trouble of fixing the sourcing properly. I'm on the fence on notability - clearly the subject has received significant academic interest but I'll leave this to the WP:MEDRS people to properly decide. What is definitely true, though, is that the formatting is not in an acceptable state, and there is a lot of WP:OR in the article in the form of making rather synthetic statements out of several related papers. You want to read WP:YFA for some guidance. Fermiboson (talk) 23:23, 11 December 2025 (UTC)

Introduction

The Dual Mechanisms of Cognitive Control (DMC) theory suggests that people maintain goal-directed behavior through two distinct modes; proactive and reactive forms of cognitive control. Proactive control involves keeping goal-relevant information active over time so the person is prepared to act before something happens. Proactive control helps focus attention and processing in advance of upcoming events. This mode is usually linked to sustained activity in the lateral prefrontal cortex. Reactive control is a bottom up process that is activated after a stimulus has appeared. This control is used to resolve conflicting information or correct mistakes once they are detected. Reactive control is related to activity in the anterior cingulate cortex and overlapping regions of lateral prefrontal cortex..^[1][2]. This framework was initially proposed by Todd Braver and colleagues^[2][3] and the theory describes how people adjust their thoughts and actions in response to changing demands in the environment.

Overview

According to the DMC theory, proactive control is an anticipatory form of control that allows individuals to prepare in advance. It allows individuals to prepare for changing stimuli in their environment, in order to maintain goal-directed behavior. In contrast, reactive control is a form of control that is only engaged after conflict is recognized, such as conflicting information or an error ^[2]. Together, these two forms of control help explain why executive functioning varies across people and how the prefrontal cortex works with other brain areas involved in control.

History and Theoretical Development

Foundations in top-down and bottom-up processing

The DMC theory builds on long-standing ideas about top-down and bottom-up processing to describe how cognitive control works.

• Top-down processing refers to behavior that is guided by experience, expectations, or goals. It is often slower and more deliberate than bottom-up processing.
• Bottom-up processing refers to automatic, stimulus-driven responses. It is fast and efficient, but relatively inflexible.

Both forms of processing provide a foundation for understanding how control can be used either in anticipation of events or in response to them. In general, top-down processing is typically slower than bottom-up processing.

Prefrontal cortex and control of behavior

The prefrontal cortex (PFC) plays a key role in using top-down control to adjust behavior. It is argued that this region is particularly important when habits or simple stimulus-response rules (i.e. task specific rules) are not enough, such as when rules change quickly^[4]. In these situations, PFC activation helps keep goals in mind and use them to guide behavior, even when there are strong competing impulses or distractions.

Emergence of the Dual Mechanisms Framework

Braver and colleagues ^[2][3] integrated this work into a single model of cognitive control, called the DMC framework. They proposed two may ways control operates, and these two ways are proactive and reactive control.

Later refinements of the DMC framework suggested that people can switch between these two modes of control during a task. As the demands of the task or, environment, changes, people change how much they rely and either proactive or reactive control^[2].

Experimental Paradigms and Measurement

Behavioral paradigms

Several standard laboratory tasks are used to study proactive and reactive control.

Stroop task^[5][6] : In this task, the person is asked to name the color of the ink or font a word is printed in, while ignoring what the word itself is. For example, the word “green” might be printed in yellow ink or font, and the correct response would be “green” not “yellow”. Trials where the work and ink color match are referred to as congruent trials, and trials where they differ are referred to as incongruent trials.

Flanker task ^[7]: This task measures how well people can stay focused when there are distracting items around the thing they are supposed to respond to. For example, in modified version of the task people see a row of arrows and are required to respond to the direction of the central arrow, such as a left button press if the arrow points to the left. On congruent trials, the central arrow points in the same direction as the surrounding, or flanking, arrows. On incongruent trials, the central arrows points in the opposite direction as the surrounding arrows.

AX-Continuous Performance Task (AX-CPT)^[8]: This task is designed to distinguish proactive from reactive control by changing how often letter pairs occur. People are asked to make a certain response when the letter “X” is preceded by the letter “A” (the “AX” sequence), but not when “X” is preceded by another letter (“BX”) or when other letters appear.

Researchers look at several measures of performance in these tasks, including how quickly people respond (response time), how often they make errors, and how the pattern of one trial influences the next trial (sequence effects). These measures help indicate whether people are relying on more on proactive control or on reactive control.

Electrophysiological and neural indices

Psychophysiological measures help show when and how proactive and reactive control are engaged over time.

Proactive control

• Greater anticipation-related theta-band (3–5 Hz) power is associated with conflict expectation^[9]. Therefore, when people believe that something difficult is coming, their brain shows more of this rhythm.
• Event-related potentials (ERPs) including Cue-N1, Cue-N2, Cue-P3, and the contingent negative variation (CNV) shows how well someone prepares and keeps goals in mind^[10].

Reactive control

• Slow brain rhythms (delta–theta: 2–8 Hz) are associated with how fast a person responds and how well they correct mistakes^[9].
• Multiple indices of theta band activity, such as theta-gamma phase amplitude coupling, a cross-frequency coupling technique, becomes stronger after people make errors and is believed to show that the brain is adjusting behavior^[11][12][13].
• ERPs such as the Target-N2, Target-P3, and error-related negativity (ERN) are linked to how the brain notices and deals with conflict^[6][10].

Brain imaging studies have corroborated these findings, showing brain activity in the lateral prefrontal cortex region for proactive control and coupling between the anterior cingulate cortex and the prefrontal cortex regions for reactive control ^[8][14].

Clinical and Applied Relevance

People do not use proactive and reactive control in a fixed way. Use of these two modes varies across different groups and can also change within the same person over the course of a task.

Psychopathology

The DMC framework has been applied to several mental health and developmental conditions:

• Anxiety disorders
  • Greater reliance on reactive control, coupled with reduced proactive control, has been shown to moderate links between temperament and anxiety risk^[15]. Furthermore, people with anxiety have demonstrated increased indicators of reactive control, such as ERN, to the point that people believe it could be a biological marker of anxiety^[16]. While anxiety is associated with ERN, it is believed that the worry piece of anxiety is most related to brain responses^[17]
• Schizophrenia
  • Patients often demonstrate an intact ability to react in the moment, but impaired abilities in preparing head.^[18][19]. This highlights impaired proactive control. It is believed that decreased proactive control in individuals with schizophrenia is associated with a how they weigh rewards and is especially affected by the amount of effort that is required^[18]
• Major depressive disorder (MDD)
  • People with MDD show disruptions in proactive and reactive control during tasks that involve conflict^[20]. However, it is unclear whether these abnormalities are consistent, as the literature is mixed^[21][22]. The literature is possibly mixed because anxiety and depression symptoms are often comrobid, complicating the findings.

These findings are in line with the conflict monitoring theory of cognitive control and activity in the anterior cingulate cortex^[1], which states that when the brain detects a mistake, it sends a signal that more control is needed. Differences in clinical populations ability to regulate proactive and reactive control highlight importance of distinguishing the two forms of control.

Development and aging

It has been suggested that use of proactive and reactive control changes across the lifespan. Specifically, older adults typically rely more on proactive control but exhibit reduced ability in switching between modes^[23]. Differences in brain efficiency and working-memory ability may contribute to the age related differences, as they change across development.

Individual differences

Differences between people can influence the balance between proactive and reactive control.

• People with stronger working-memory abilities and lower impulsivity use more proactive control.^[24][10]
• Reactive control tends to dominate in individuals with lower working-memory capacity and those with greater lapses in attention.
• Research suggests that women demonstrate greater use of proactive control than males, suggesting gender differences.^[10]

Critiques and Limitations

Although the DMC theory has become an influential framework to think about cognitive control, it has also been criticized. Some researchers argue that dividing control into just two modes does not fully capture the complexity of cognitive systems^[25]. Others note that task-specific details can strongly shape how much proactive or reactive control is used, which may limit how broadly the model can be applied^[26]

To address these concerns and test the DMC framework, large-scale projects, such as the Dual Mechanisms of Cognitive Control (DMCC) Project^[14], have been developed. This project combines multiple methods, including brain imaging, behavioral measures, and individual-differences approaches, to understand how proactive and reactive control interact in guiding behavior.

Future Directions

Ongoing research is examining how factors, such as situational context, motivation, and emotional state, influence whether proactive or reactive control is more strongly engaged. Long-term and clinical studies are investigating whether training or brain-stimulation approaches can shift people toward control strategies that support better functioning in specific settings. Researchers are also studying how an individual's performance changes from trial to trial to understand how momentary fluctuations in proactive and reactive control relate to clinical diagnoses or symptom levels. Additionally, work that carefully examines how specific task features affect control modes may help synthesize findings across studies and clarify when and how each mode is most likely to be engaged.