Integration-First Living Neural Compute Architecture (IF-LNCA): A Technical Appendix on Neural Graft Preconditioning, the Maturity–Integration Paradox, Host–Graft Co-Adaptation, and In Situ Functional Training

Integration-First Living Neural Compute Architecture (IF-LNCA) is a technical appendix to Living Neural Compute Architecture (LNCA), DOI 10.5281/zenodo.23244210. This appendix develops a more conservative implementation branch of LNCA in which ex vivo preparation is treated primarily as neural-graft preconditioning rather than complete skill pretraining. The proposed sequence is: precondition → transplant → integrate → map → train in situ → consolidate. The framework introduces the Autologous Preconditioned Neural Graft (APCG), formalizes the Maturity–Integration Paradox, distinguishes functional, interface-statistical, and plasticity/homeostatic preconditioning, and proposes quantitative measures for integration quality, host–graft alignment, in-situ learning, and preconditioning benefit. Exact retention of a complex pretrained skill across transplantation remains a stronger optional hypothesis rather than a prerequisite for the architecture.