A Differential Neural Scene Codec: Formal Conditions and Exploratory Limits of Scene-Conditioned Residual Neural Control

A Differential Neural Scene Codec develops a testable framework for a bidirectional perceptual interface. It asks how a system could estimate a person's current measurable neural state, construct a scene-conditioned target, isolate the part of their difference that is both observable and reachable, and apply a bounded update. The paper traces this operation to Micah Blumberg's 2017 Neural Lace Podcast and its 2022 Self Aware Networks extension. It preserves negative results from 3,000 exploratory and 2,520 frozen adversarial simulations. Predictive residual control was not uniformly superior and sometimes failed sharply. Its conclusions are limited to the assumptions, evidence, and testing conditions stated in the manuscript. It belongs to the Self-Aware Networks neuroscience and consciousness research program. This is a corrected preprint edition released under the Creative Commons Attribution 4.0 license.