Hence, computation is cheap but communication is expensive. Thus, a vanishingly small fraction of the connection space is explored by tweaking existing synapses. Sprouting new connections and pruning old ones, over time, greatly enlarges the search space. Growth is indispensable in the developmental phase, and probably supports learning in the mature structure as well. In addition to using wires efficiently, growing connections implement weight normalization, competitive learning, and programmable delays efficiently.
Normalization occurs by limiting the number of connections an afferent makes.
Competition occurs by forcing it to choose one of several nearby targets. And delays are adjusted by migrating down the dendritic tree. Implementing these desirable learning mechanisms with analog weights has proved exceedingly difficult no existing learning chip boast all three. And, spiking neurons transmit information robustly and process it efficiently by exploiting coincidence, latency, and hot spots. Correlation is measured by detecting coincidence, or synchrony, instead of performing multiplications.