. A central pattern generator producing alternative outputs: temporal pattern of premotor activity.

We aimed to determine the neuronal parameters controlling the contraction of slowly contracting, non-twitch ("tonic") muscles driven by rhythmic neuronal activity. These muscles are almost completely absent in mammals but are common in lower vertebrates and invertebrates. Slow muscles are often believed to function primarily in tonic motor patterns. However, previous research and data presented here indicate that slow muscles are also driven by rhythmic neuronal inputs.In rapidly contracting "twitch" muscles, motor unit force is believed to be primarily determined by motor neuron spike frequency. What determines slow muscle output is less well understood. We present a simple model that suggests that when motor neuron burst duration is brief compared with muscle summation time, spike number, not spike frequency, determines slow muscle contraction amplitude.We present analyses that distinguish between spike number and spike frequency dependence in two slow muscles in the lobster stomatogastric system. Our analysis shows that, functionally, one muscle is spike number dependent, whereas the other is primarily spike frequency dependent. Thus, both of these parameters can determine slow muscle output. To predict the movements elicited by neuronal activity in preparations in which slow muscles are common, it may be necessary to determine spike number versus spike frequency dependence for each muscle.Spike number dependence couples motor neuron burst duration and spike frequency in that changing either parameter alone alters spike number (and hence muscle contraction amplitude). Neural networks innervating spike number-dependent muscles may therefore have specific properties to compensate for the complexity intrinsic to spike number coding.

Slow, non-twitch muscles are widespread in lower vertebrates and invertebrates and are often assumed to be primarily involved in posture or slow motor patterns. However, in several preparations, including some well known invertebrate "model" preparations, slow muscles are driven by rapid, rhythmic inputs. The response of slow muscles to such inputs is little understood. We are investigating this issue with a slow stomatogastric muscle (cpv1b) driven by a relatively rapid, rhythmic neural pattern. A simple model suggests that as cycle period decreases, slow muscle contractions show increasing intercontraction temporal summation and at steady state consist of phasic contractions overlying a tonic contracture. We identify five components of these contractions: total, average, tonic, and phasic amplitudes, and percent phasic (phasic amplitude divided by total amplitude). cpv1b muscle contractions induced by spontaneous rhythmic neural input in vitro consist of phasic and tonic components. Nerve stimulation at varying cycle periods and constant duty cycle shows that a tonic component is always present, and at short periods the muscle transforms rhythmic input into almost completely tonic output. Varying spike frequency, spike number, and cycle period show that frequency codes total, average, and tonic amplitudes, number codes phasic amplitude, and period codes percent phasic. These data suggest that tonic contraction may be a property of slow muscles driven by rapid, rhythmic input, and in these cases it is necessary to identify the various contraction components and their neural coding. Furthermore, the parameters that code these components are interdependent, and control of slow muscle contraction is thus likely complex.

We describe three slow muscles that responded to low-frequency modulation of a high-frequency neuronal input and, consequently, could express the motor patterns of neural networks whose neurons did not directly innervate the muscles. Two of these muscles responded to different frequency components present in the same input, and as a result each muscle expressed the motor pattern of a different, non-innervating, neural network. In an analogous manner, the distinct dynamics of the multiple intracellular processes that most cells possess may allow each process to respond to, and hence differentiate among, specific frequency ranges present in broad-band input.

In several systems, including some well studied invertebrate "model" preparations, rapid, rhythmic inputs drive slow muscles. In this situation muscle contractions can summate temporally between motor neuron bursts, tonically contract, and low-pass filter broad-band input. We have investigated how the muscles innervated by each motor neuron type of the rapid, rhythmic (cycle period, approximately 1 sec) lobster pyloric network respond when driven by previously recorded in vitro pyloric network activity from intact stomatogastric nervous systems. Under these conditions the much slower gastric mill and cardiac sac networks of the stomatogastric nervous system are also active and modify pyloric activity. All of the muscles show pyloric timed phasic contractions that ride on a sustained tonic contraction; muscle activity can range from being almost completely phasic to almost completely tonic. The modifications of pyloric neuron activity induced by gastric mill (cycle period, approximately 10 sec) activity result in some pyloric muscles showing prominent, gastric mill-timed, changes in either phasic or tonic contraction amplitude. The strong modification of pyloric neuron activity induced by cardiac sac (cycle period, approximately 60 sec) activity alters the contractions of all pyloric muscles. These changes are sufficient that for some muscles, in some preparations, the primary muscle output is cardiac sac-timed. This is the first work to examine the motor responses of all pyloric muscle classes to spontaneous stomatogastric activity and shows that the pyloric motor pattern is a complex combination of the activities of three neural networks, although only one (the pyloric) innervates the muscles.