Embodied cognition remains a contested concept in cognitive science and AI. Some researchers treat the body as a sensorimotor interface that grounds computational processes in environmental interaction, while biologically-oriented views stress the living body's homeostatic and allostatic self-regulation as foundational for both sensorimotor interaction and cognition. Adopting the latter perspective—a multi-tiered affectively embodied view—the author argues that modeling organisms as layered networks of bodily self-regulation mechanisms can advance scientific understanding of embodied cognition.
Information theory and control theory can model embodied cognition without requiring time-reversal symmetry. An iterated Morse function provides a 'higher entropy' analog that follows Onsager-like nonequilibrium thermodynamics, but because palindromes are unlikely, reciprocal relations do not hold. Group symmetry-breaking in physical phase transitions appears as groupoids linked to high-probability developmental paths. The formalism yields the Yerkes-Dodson inverted-U relation and stochastic dynamics, and suggests a canonical approach to consciousness. Context is central to real-world cognition, contrary to Western cultural emphasis on individual salience over context.