Conformist filtering reshapes cooperation in heterogeneous populations

Understanding how cooperation emerges in structured populations remains a central problem in evolutionary dynamics. Although heterogeneous updating rules and conformist behavior have been studied in evolutionary games, their spatial placement on networks and the resulting weak-selection conditions remain less fully characterized. Here, we develop a theoretical framework that incorporates quenched behavioral heterogeneity by distinguishing between fitness-driven strategists and conformists. By mapping evolutionary dynamics onto a conformist-filtering random walk, we derive an analytical condition for cooperation and identify node-level quantities that quantify how structural positions influence evolutionary outcomes. Our analysis shows that behavioral heterogeneity can substantially reshape cooperative dynamics through a conformist-filtering mechanism. Optimal intervention strategies are intrinsically non-nested, meaning that the set of nodes selected under tight budgets may differ entirely from those chosen under larger budgets. Analytical examples further reveal a gatekeeper effect in certain network structures, where nodes bridging communities exert disproportionate influence on cooperative spreading despite modest connectivity. These findings demonstrate that cooperation in heterogeneous populations is governed jointly by network topology and behavioral diversity, providing a principled framework for optimizing collective behavior in complex networks.