Meta-control: From psychology to computational neuroscience

Area of Science:

• Cognitive psychology
• Cognitive neuroscience
• Artificial intelligence

Background:

• Cognitive control mechanisms are well-researched.
• Meta-control processes, which regulate cognitive control, are poorly understood.
• Meta-control involves monitoring processing and regulating control parameters for task goals.

Purpose of the Study:

• To integrate research on meta-control from psychological, computational, and neuroscience perspectives.
• To functionally specify meta-control processes and operationalize them experimentally.
• To formalize meta-control problems computationally and identify neural correlates.

Main Methods:

• Psychological perspective: Functional specification and experimental operationalization.
• Computational perspective: Formalization using artificial intelligence principles.
• Cognitive neuroscience perspective: Identifying neural correlates and mechanisms.

Main Results:

• The study aims to bridge segregated research strands on meta-control.
• It seeks to provide a unified understanding of how cognitive control is regulated.
• It highlights the importance of meta-control for behavioral strategy selection.

Conclusions:

• Meta-control is key to understanding executive functions and behavioral regulation.
• Integrating multiple perspectives offers a comprehensive view of meta-control.
• Further research is needed to fully elucidate the neural basis and computational principles of meta-control.