Pain represents a paradigmatic example of consciousness requiring rapid integration across distributed neural systems, making it an ideal model for understanding field-primary approaches to cognition and consciousness. I propose that pain perception emerges from electromagnetic field dynamics as the primary computational substrate, with neurotransmitter systems serving largely as field-controlled energy modulation networks rather than primary signaling mechanisms. This hierarchical framework positions ephaptic field effects (operating at nanosecond timescales) as the primary layer, neuromodulation and neurotransmitters (millisecond to second timescales) as energy distribution, and myelination architecture (evolutionary timescales) as the structural substrate. Building on General Resonance Theory 2.0 and resonance cascade principles, we demonstrate that pain systems maintain baseline criticality (σ = 1), with acute pain representing adaptive supercritical shifts and chronic pain reflecting maladaptive critical states. The mixed myelination of pain pathways—myelinated A-delta fibers for rapid threat detection and unmyelinated C-fibers for complex field integration—exemplifies evolution's solution to balancing speed and computational requirements. This field-primary perspective offers novel explanations for phenomena including central sensitization (as runaway resonance cascades), placebo analgesia (field-mediated expectation effects), and the efficacy of electromagnetic therapies. We present testable predictions about field propagation speeds (47-57 km/s), resonance signatures in different pain states, and optimal parameters for field-based interventions. The pain resonome framework not only advances our understanding of nociception and suffering but provides a window into the fundamental mechanisms by which electromagnetic fields give rise to conscious experience.
Tam Hunt (2025) studied this question.