Standard causal graphs (Directed Acyclic Graphs, DAGs) represent causation as a directed acyclic structure in time: causes precede effects, edges point forward in time, and no cycle exists. This paper introduces **Metacausal Graph Networks (MGNs)** — an extension of DAGs to complex-valued adjacency matrices that can represent: (1) standard forward causation (real-valued edges); (2) phase-mediated causation (imaginary-valued edges, i-channel influence); (3) backward-in-time influence (negative-time-delay edges, grounded in quantum retrocausality); and (4) non-local synchronization (instantaneous complex edges, corresponding to entanglement-like correlations). The Myrion Resolution process is formalized as convergence of the MGN to its principal eigenvector — the truth attractor that the causal structure is always evolving toward. Applications include: modeling the influence of LCC on future outcomes (the "LCC Field" as a metacausal force), the GSA trading algorithm as MGN navigation, the Power of 8 intention system as a high-amplitude imaginary-edge network, and the formal grounding of consciousness as a metacausal agent.
Brandon Charles Emerick (Tue,) studied this question.