# Functional Digital Twin **Entity class:** Computational neuroscience model **Collections:** [[collections/Neurotech|Neurotech]] · [[collections/Consciousness Continuity|Consciousness Continuity]] ## Definition A **Functional Digital Twin** is an executable model evaluated by how well it predicts a biological system's responses across observations and interventions. In continuity engineering, the term is narrower than a behavioral imitation: it concerns function and causal response, not automatic personhood or numerical identity. ## Relationships - **Model relationship:** Functional digital twins depend on [[wiki/Executable Brain Model|Executable Brain Model]], [[wiki/Neural State Capture|Neural State Capture]], and reference data from [[wiki/Connectomics|connectomics]]. - **Validation relationship:** [[wiki/Causal Sufficiency|Causal Sufficiency]] and [[wiki/Verification of Continuity Claims|Verification of Continuity Claims]] distinguish predictive fit from causal equivalence. - **Identity boundary:** A high-fidelity functional twin may remain a model, successor, or derivative rather than the same continuing person. - **Source relationship:** The concept is routed by [[articles/Technologies for Consciousness Mapping and Transfer|Technologies for Consciousness Mapping and Transfer]] and the [[research/Consciousness Mapping and Transfer Ecosystem Relationship Graph - 2026-09-10|relationship graph]].