Evolutionary Game Theory Reveals Modular Specialization as a Universal Solution to Neural Trade-offs

What this is This dataset accompanies the CRN manuscript and provides reproducible artifacts for the evolutionary game-theory (EGT) analysis showing that modular specialization emerges as an evolutionarily stable strategy (ESS) under physical trade-offs. Core claim (summary): A physical trade-off exists: noise optimal for transport (higher κ) conflicts with memory stability (lower κ). Modular specialization yields a fitness advantage (typ. +6% to +31%) and takes over under replicator dynamics (example: 99.86% within 71 generations). Robustness is tested across parameter grids and disappears when the trade-off is removed (causal control).