Motor behaviour results from information processing across multiple neural networks acting at all levels from initial selection of the behaviour to its final generation. Understanding how motor behaviour is produced requires identifying the constituent neurons of these networks, their cellular properties, and their pattern of synaptic connectivity. Neural networks have been traditionally studied with neurophysiological and neuroanatomical approaches. These approaches have been highly successful in particularly suitable 'model' preparations, typically ones in which the numbers of neurons in the networks were relatively small, neural network composition was unvarying across individual animals, and the preparations continued to produce fictive motor patterns in vitro. However, analysing networks without these characteristics, and analysing the complete ensemble of networks that cooperatively generate behaviours, is difficult with these approaches. Recently developed molecular and neurogenetic tools provide additional avenues for analysing motor networks by allowing individual or groups of neurons within networks to be manipulated in novel ways and allowing experiments to be performed not only in vitro but also in vivo. We review here some of the new insights into motor network function that these advances have provided and indicate how these advances might bridge gaps in our understanding of motor control. To these ends, we first review motor neural network organisation highlighting cross-phylum principles. We then use prominent examples from the field to show how neurogenetic approaches can complement classical physiological studies, and identify additional areas where these approaches could be advantageously applied.
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