The Silhouette Fallacy: why copying neuron geometry isn't inheriting its computation
neurovium · x · 2026-10-05
The author coins the "Silhouette Fallacy" in NeuroAI: resemblance is not inheritance — copying a neuron's branched geometry doesn't reproduce its computation.
Key points:
- Dendrite-inspired architectures and branched neuromorphic devices can be useful, and networks borrowing a neuron's visual language can do interesting things;
- But if all you copied is the tree, you've only copied the first row of the computational hierarchy;
- Going beyond requires internal dynamical states in the branches;
- To recover field-closed organization, those states must write into a shared physical variable that acts back on computation — not necessarily extracellular electric fields; optical, mechanical, chemical, acoustic, or electromagnetic media could work.
This explains the author's caution about biomimetic geometry in NeuroAI.
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