Topological Latent Manifold Model v6.8: Mechanistic Enrichment and Cross-Modal Fusion for Personalized Viability Forecasting in Neurodegenerative Disease

TLMM v6.8 (Topological Latent Manifold Model) extends the causal personalization and cross-cohort validation framework established in v6.6 and v6.7 by introducing mechanistic enrichment and cross-modal integration for personalized viability forecasting in neurodegenerative disease. This release presents four major methodological advances: ATN Cascade Integration embedding the Amyloid–Tau–Neurodegeneration biological ordering as differentiable soft constraints in the joint latent space. Cross-Modal Fusion Architecture integrating neuroimaging, biomarkers, genetics, and clinical assessments through modality-specific encoders with Bayesian missing-data modeling. Multi-Action Intervention Response Model (IRM) with Adaptive Viability Steering (AVS) for combination intervention optimization. Mechanistic Constraints vs. Data-Driven Forecasts, systematically evaluating biologically motivated soft constraints against unconstrained latent forecasting. Version 6.8 also introduces a new falsifiability criterion: C7: Biological Stage Consistency expanding the existing C1–C6 scientific validation framework. The repository includes: Full TLMM v6.8 paper (22 figures) Complete README Python demonstration code reproducing Figures 18–22 Synthetic illustrative examples for methodological development All numerical values, figures, and experiments are illustrative synthetic demonstrations intended solely for methodological research. They do not represent clinical performance estimates and should not be interpreted as medical advice or clinical recommendations. This version serves as the mechanistic bridge toward the planned TLMM v7.0, which aims to integrate the full Appearance–Behavior Framework (ABF) cascade into a unified probabilistic modeling framework for precision brain health research.