Self-Deception as a Ze-Pattern

This paper presents a formal theory of self-deception, reconceptualizing it not as a failure of rationality but as an emergent property of predictive information processing within the Ze-theoretic framework. We posit that the cognitive system functions as a Ze-pattern—a structured information stream—that generates a predicted Ze-stream (Ze_predict). Perception is modeled as a process of matching this prediction against observed sensory Ze-stream (Ze_real). We formalize the probability of conscious perception of an event as: P(perceive)=1exp(−|Ze_predict−Ze_real|). Large mismatches are classified as T-events (incorrect predictions) and are cognitively suppressed. The model is derived from the axioms of Ze-theory (Variant 1: Predictive Inference), specifically from the fundamental stopping axiom: Retrograde Encoding (R) requires complete cessation of Forward Reading (F). The perception kernel follows from assuming a stochastic threshold θ with an exponential distribution, justified by the maximum entropy principle (Jaynes, 1957). Self-deception is formalized as pathological threshold tuning: def<opt, where the degree of self-deception is D=(opt−def)/opt. We derive three empirically testable predictions: (1) a discontinuous jump in reaction time at ΔF ≈ θ, (2) absence of post-error correction in self-deception, and (3) a transient vulnerability window (100–500 ms) following Retrograde Encoding. A complete experimental protocol with power analysis (N = 30 per group, Cohen’s d = 0.8, α = 0.05, power = 0.8) and Bonferroni correction for multiple comparisons is provided. All key parameters (Ze_predict, Ze_real, α, θ, λ) are operationally defined, with a specified number of trials (500 per participant: 10 ΔF levels × 50 repetitions).