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In developing brain, axons and dendrites are capable of connecting to eachother with high precision. Recent advances in imaging have allowed for themonitoring of axonal, dendritic, and synapse dynamics in vivo. It is observedthat the majority of axonal and dendritic branches are formed 'in error', onlyto be retracted later. The functional significance of the overproduction ofbranches is not clear. In this study, we use a computational model toinvestigate the speed and efficiency of different branching strategies. We showthat branching itself allows for substantial acceleration in the identificationof appropriate targets through the use of a parallel search. We also show thatthe formation of new branches in the vicinity of existing synapses leads to theformation of target connectivity with a decreased number of erroneous branches.This finding allows us to explain the high correlation between the branchpoints and synapses observed in the Xenopus laevis retinotectal system. We alsosuggest that the most efficient branching rule is different for axons anddendrites. The optimal axonal strategy is to form new branches in the vicinityof existing synapses, whereas the optimal rule for dendrites is to form newbranches preferentially in the vicinity of synapses with correlated pre- andpostsynaptic electric activity. Thus, our studies suggest that the developingneural system employs a set of sophisticated computational strategies thatfacilitate the formation of required circuitry, so that it may proceed in thefastest and most frugal way.

Optimal axonal and dendritic branching strategies during the development of neural circuitry