Imaginación Consciente con Neurofeedback (IC-NF): Modelo generativo-disolutivo, neuroautonómico y falsable para la investigación contemplativa

This preprint presents Conscious Imagination with Neurofeedback (IC-NF) as a falsifiable theoretical-methodological framework and a reproducible research program for investigating psychological transformation through a closed-loop interaction between conscious mental simulation, contemplative training, autonomic regulation, and neurophysiological feedback. IC-NF integrates attentional stabilization (Shamatha/Shiné), metacognitive monitoring (Vipashyana/Lhaktong), controlled generative imagery (Kyerim/bskyed rim), explicit representational dissolution (Dzogrim/rdzogs rim), non-referential awareness (Mahamudra), multimodal neurofeedback, and heart rate variability biofeedback (HRVB) into a single operational architecture designed for empirical testing, methodological transparency, and computational reproducibility. The present work does not report original human experimental data and does not claim established clinical efficacy of the complete IC-NF protocol. Instead, it rigorously distinguishes between (i) externally validated evidence for individual components, (ii) the author's auditable documentary evidence (Study 0B), and (iii) the future experimental validation pathway required to evaluate the integrated protocol. The preprint includes a reproducible Monte Carlo power simulation, an auditable documentary corpus, methodological specifications, explicit falsification criteria, supplementary material, computational resources, and reproducibility files intended to facilitate independent verification and future replication studies. Within the author's research program, IMAG (Conscious Imagination and Mental Simulation) constitutes the overarching theoretical architecture, whereas IC-NF represents a functionally differentiated contemplative-neurophysiological specialization. The conceptual overlap between both models is explicit and intentional; however, IC-NF introduces a distinct closed-loop architecture based on generative-dissolutive mental simulation, physiological calibration, and neurofeedback-guided learning. Previous Zenodo publications authored by Florencio Serrano Prior are cited exclusively as programmatic continuity and conceptual traceability. They are not presented as independent external evidence supporting the IC-NF model. This version is intended as the stable, citable reference implementation of IC-NF and as the scientific foundation for subsequent empirical studies and multiple peer-reviewed Q1 journal articles.