The ARCH model: a neuroevolutionary framework for behavioral execution

Area of Science:

• Computational neuroscience
• Behavioral science
• Psychology

Background:

• Behavior is understood as arising from complex, interacting factors.
• Existing models often simplify the multifaceted nature of behavioral drivers.
• A need exists for a unified framework integrating biological, affective, and cultural influences.

Purpose of the Study:

• To introduce the ARCH × Φ model, a computational grammar for behavior.
• To formalize the multiplicative interaction of Archetype (A), Drive (D), and Culture (C) modulated by a context-sensitive threshold (Φ).
• To propose a taxonomy of ten archetypal systems (Systema Behavorum) as inputs to the model.

Main Methods:

• Development of the ARCH × Φ computational grammar.
• Integration of ethology, affective neuroscience, psychiatry, and cultural psychology.
• Definition of a provisional taxonomy of ten archetypal systems.

Main Results:

• The ARCH × Φ model specifies behavior as a probabilistic, testable outcome of convergent constraints.
• Archetypes are reframed as conserved neural scripts modulated by scalar amplification and symbolic expression.
• The framework supports falsifiable predictions and operational definitions.

Conclusions:

• Behavior is an emergent property of convergent constraints across biological, affective, cultural, and contextual domains.
• The ARCH × Φ model offers a unified approach to understanding motivation, threshold regulation, and symbolic processing.
• This framework has potential clinical applications in decoding and treating behavioral dysregulations.