Self-Aware Networks: A Falsifiable Theory-and-Methods Framework for Phase-Gradient Routing and Recurrent Oscillatory Reconstruction

This corrected preprint presents its research question, method, bounded result, and principal limitations in a standardized reader-facing format. Version 2.2 presents Self-Aware Networks as a lossless, operational theory-and-methods framework for receiver-relative timing, recurrent reconstruction, and embodied perception-action loops. It defines the Phase Wave Differential as a receiver-relative change that can affect routing or action; NAPOT as a joined receive-transform-project-reconstruct proposal; and Neural Rendering as recurrent updating of a distributed body and world model. The paper separates established mechanisms from SAN-specific synthesis, formalizes matched comparators and falsification conditions, and restores the full Oscillatory Computational Agency genealogy without deleting corrected historical claims. It reports no new human or animal experiment and no empirical confirmation. 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.