Neurons, networks, and motor behavior.

The field of motor pattern generation and motor control has progressed markedly in the last decade. There has been a revolutionary shift in thinking from hard-wired circuits to multifunctional networks. Yet, it is clear that we still have a long way to go before we understand how very large ensembles of neurons produce behaviors. The systems where we have made the most headway are those that have an orderly topography, such as the superior colliculus (Sparks) or motor cortex (Georgopoulos). However, even in these systems, although we understand how to interpret the combined activity of the neuronal population, it is not clear how this population activity is translated into a motor command. Similarly, the directional behavior produced in cockroach (Ritzmann) and fish escape (Eaton) systems can be predicted based on the activity of neurons, but the cellular mechanisms producing the turning responses in cockroaches and teleost fish are not completely understood. Undoubtedly, computational approaches, including new mathematical formalisms and computer simulations, will play a role in elucidating how very large ensembles of neurons produce their coordinated output. For now, the systems where motor pattern generation is best understood at the cellular level are those with small numbers of neurons (such as invertebrate circuits) or small numbers of cell types, such as lamprey and tadpole spinal circuits. These systems are thus valuable for pointing to potential mechanisms used in larger systems. (Note that I avoid using the term "simple" systems to describe invertebrates because it is quite clear that these systems are anything but simple.) However, "interphyletic awareness," as it was referred to at this conference, is not important just for what it can tell us about how mammals work. It is also important to learn of alternative ways in which organisms solve similar problems. This may prove to be particularly important for the future of robotics. Already, robots have been designed based on insights gained from studying insect visual (Strausfeld) and motor (Ritzmann) systems. Robotics engineers have also independently converged on some of the same mechanisms used by biological systems (MacPherson). There is clearly a need for better understanding of higher control of pattern-generating circuits. This is not limited to how motor patterns are initiated, but also includes how they are altered on a moment to moment basis to suit the needs of the animal. The next revolution in the field is likely to come from a paradigm shift regarding such control of motor circuits, similar to the shift that has already occurred in our understanding of the pattern-generating circuits themselves. Such flexibility of control is the basis for decision making in the nervous system and the very essence of what animals must do throughout their daily lives. I look forward to the next conference in 2005 to see how far we've progressed in these pursuits.