Functional Disassembly by Sequential Feature Removal: A Methodology for Generating Parallel Evolutionary Analogues, with Application to Neural Architecture

This note proposes a methodology called Functional Disassembly by Sequential Feature Removal (FDSFR): taking any complex system in its current form, identifying its most recently added functional feature, removing it, observing what the system becomes, and repeating until the simplest functional ancestor is reached. At each removal step, the methodology asks what alternative versions of the removed feature existed or could have existed — generating a branching tree of parallel possible systems, not a single ancestral sequence. Applied to engineered systems (tyres, jet engines, smartphones), this process is intuitive and produces well-defined branch trees. Applied to biological neural architecture, the same process generates a tree of parallel possible brains — alternative cognitive architectures that could have emerged from the same evolutionary substrate under different selection pressures. These parallel analogues are not recoverable from comparative neuroscience across existing species; they must be generated computationally from first principles of feature-removal logic. The resulting tree constitutes a prediction space for non-Earth neural architectures and a methodology for understanding which human cognitive properties are substrate-universal versus which are contingent on specific historical branch-point outcomes.