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Could a computer scientist build a brain?The problem and its constraintsStrategy 1: the identity approachStrategy 2: the guidepost approachStrategy 3: the coordinate approachThe role of noisePlasticityDiscussionNotesReferences Stan Kerstjens & Anthony M. Zador Cold Spring Harbor Laboratory Correspondence: kerstje@cshl.edu How does a brain wire itself, starting from a single cell, using only the information encoded in a genome? We pose this as an engineering problem: Write a program that a single cell executes to build itself into a brain. The program must be small enough to fit in a genome, and fast enough to finish within developmental time. A computer scientist who knows little about biology quickly realizes why the obvious strategies, which developmental biology has rejected experimentally, fail at scale: The genome is too small to store per-synapse wiring, and axons searching blindly for targets would take too long.
These same algorithmic constraints drive the design toward solutions that resemble the developmental strategies organisms actually use. That the same solution structure falls out of scaling limits as out of evolution suggests that features of neural development can be grounded in computational necessity rather than contingency alone.