  In developing brain, axons and dendrites are capable of connecting to each
other with high precision. Recent advances in imaging have allowed for the
monitoring of axonal, dendritic, and synapse dynamics in vivo. It is observed
that the majority of axonal and dendritic branches are formed 'in error', only
to be retracted later. The functional significance of the overproduction of
branches is not clear. In this study, we use a computational model to
investigate the speed and efficiency of different branching strategies. We show
that branching itself allows for substantial acceleration in the identification
of appropriate targets through the use of a parallel search. We also show that
the formation of new branches in the vicinity of existing synapses leads to the
formation of target connectivity with a decreased number of erroneous branches.
This finding allows us to explain the high correlation between the branch
points and synapses observed in the Xenopus laevis retinotectal system. We also
suggest that the most efficient branching rule is different for axons and
dendrites. The optimal axonal strategy is to form new branches in the vicinity
of existing synapses, whereas the optimal rule for dendrites is to form new
branches preferentially in the vicinity of synapses with correlated pre- and
postsynaptic electric activity. Thus, our studies suggest that the developing
neural system employs a set of sophisticated computational strategies that
facilitate the formation of required circuitry, so that it may proceed in the
fastest and most frugal way.
