Are central pattern generators understandable?

Abstract Most rhythmic behaviors are produced by a specialized ensemble of neurons found in the central nervous system. These central pattern generators (CPGs) have become a cornerstone of neuronal circuit analysis. Studying simple invertebrate nervous systems may reveal the interactions of the neurons involved in the production of rhythmic motor output. There has recently been progress in this area, but due to certain intrinsic features of CPGs it is unlikely that present techniques will ever yield a complete understanding of any but the simplest of them. The chief impediment seems to be our inability to identify and characterize the total interneuronal pool making up a CPG. In addition, our general analytic strategy relies on a descriptive, reductionist approach, with no analytical constructs beyond phenomenological modeling. Detailed descriptive data are usually not of sufficient depth for specific model testing, giving rise instead to ad hoc explanations of mechanisms which usually turn out to be incorrect. Because they make too many assumptions, modeling studies have not added much to our understanding of CPCs; this is due not so much to inadequate simulations as to the poor quality and incomplete nature of the data provided by experimentalists. A basic strategy that would provide sufficient information for neural modeling would include: (1) identifying and characterizing each element in the CPG network; (2) specifying the synaptic connectivity between the elements; and (3) analyzing nonlinear synaptic properties and interactions by means of the connectivity matrix. Limitations based on our present technical capabilities are also discussed.