These papers do not directly validate QWR or Resonant Intelligence. They provide established or active research contexts relevant to synchronization, relational representation, predictive processing, oscillatory communication, and dynamical computation.
Arenas, Díaz-Guilera, Kurths, Moreno & Zhou, Physics Reports 469 (2008). A broad review of how interacting oscillatory elements synchronize under complex network topology.
DOI / publisher →Rao & Ballard, Nature Neuroscience 2 (1999). Models hierarchical feedback as prediction and feedforward activity as residual prediction error.
DOI / Nature →Battaglia et al. (2018). Argues for structured relational representations and graph-network computation as a route toward stronger generalization.
arXiv →Tanaka et al., Neural Networks (2019). Reviews reservoir computing and the use of physical dynamical substrates for temporal and sequential computation.
arXiv →Fries, Neuron 88 (2015). Reviews a framework in which synchronization and coherence influence selective communication among neuronal groups.
DOI / PubMed →Friston et al. (2022). Presents a formal account linking random dynamical systems, conditional independence, Bayesian inference, and self-organization.
arXiv →We cite adjacent work to identify mechanisms worth testing—not to imply that a neuroscience or complex-systems paper proves a ResBased architecture. Our own claims require our own benchmarks, ablations, and reproducible evidence.