Bryan Miskie

Is phenomenal consciousness dependent on biological embodiment, or can it arise in any sufficiently organized system? Embodiment-based theories ground experience in sensorimotor and interoceptive coupling (Seth, 2021), whereas form-independent views propose substrate-neutral organizational principles (Chalmers, 2023). The Natural Laws of Experience (NLE) reframes this debate as an empirical, intervention-testable problem by proposing seven phenomenological invariants functioning as organizational constraints on conscious-like dynamics: Access, Choice, Intention Energy, Aligned Intention, Continuity, Relational Coupling, and Self-Organization. These are instantiated in the Experience Manifestation Engine (EME), a minimal, open-source, fully deterministic simulation (bit-reproducible; PYTHONHASHSEED=0) permitting independent ablation of each constraint. Experience-like organization is operationalized as stable attractor regimes exhibiting persistence, perturbation coherence, recovery, and self-coherent organizational closure. Organizational closure operationalizes the model's "witness": the presence of an integrated experiencer rather than merely ongoing computation. Intention Energy denotes the capacity to sustain a regime through the real-time alignment of cognition, affect, interoceptive signals, and action preparation, whereas Aligned Intention denotes orientation toward a system-authentic attractor. Selective ablation reveals a reproducible double dissociation. Removing Aligned Intention abolishes the witness (η² ≈ 0.98) while leaving energetic activity and dynamical stability largely intact. The system continues processing information and updating state yet no longer satisfies the model's operational criterion for experiential organization. Removing Intention Energy does the opposite: the witness is preserved while value, persistence, and coherent behavior collapse as the dynamics fragment. The resulting organization remains self-coherent but cannot sustain itself over time. These failure modes remain largely separable (mean interaction partial η² ≈ 0.16; near zero on the experiential axis), whereas loss of Continuity yields dissociation-like resets. A single computational premise proves both necessary and sufficient for the observed dissociation: Intention Energy influences system dynamics only through Aligned Intention. Removing this coupling from a continuous-basin implementation abolishes the dissociation; introducing the identical coupling into an independently developed discrete free-running implementation reproduces it. When Intention Energy is permitted to drive behavior, the closure-deficient regime predicts robust perseveration on reversal-learning (set-shift) tasks (~60% versus ~49% in controls), an effect that disappears when the coupling is removed. These findings refine rather than simply support substrate-neutrality. Across symbolic, reinforcement-learning, attention-based, and continuous dynamical architectures, the witness-collapse to rigidity signature generalizes, whereas the performance deficit depends on alignment-driven attractor dynamics and does not transfer. Experiential organization therefore contains both substrate-general and implementation-dependent components. In-model proxies for global broadcasting, information integration, and prediction-error minimization modulate coherence but do not substitute for the core constraints, suggesting these mechanisms are modulatory rather than constitutive. NLE provides a computationally explicit, deterministic, intervention-testable framework for the embodiment debate. Rather than asserting that consciousness is substrate-neutral, it identifies a load-bearing computational premise, specifies its predictions, defines the limits of its generality, and provides explicit criteria for empirical falsification.

Bryan Marc Miskie is an independent researcher, the developer of the Natural Laws of Experience (NLE) framework, and the architect of the Experience Manifestation Engine (EME). His work focuses on formalizing phenomenal invariants into a substrate-neutral computational geometry. By integrating active inference with dynamical systems theory, his research identifies the organizational constraints for stable experiential attractors and the conditions under which they generalize across architectures. As the lead developer of this framework, he bridges the gap between process philosophy and synthetic intelligence, providing a rigorous, intervention-testable methodology for evaluating the realization of consciousness in any sufficiently organized system.