Temperature sensitivity of the pyloric neuromuscular system and its modulation by dopamine.

We report here the effects of temperature on the p1 neuromuscular system of the stomatogastric system of the lobster (Panulirus interruptus). Muscle force generation, in response to both the spontaneously rhythmic in vitro pyloric network neural activity and direct, controlled motor nerve stimulation, dramatically decreased as temperature increased, sufficiently that stomach movements would very unlikely be maintained at warm temperatures. However, animals fed in warm tanks showed statistically identical food digestion to those in cold tanks. Applying dopamine, a circulating hormone in crustacea, increased muscle force production at all temperatures and abolished neuromuscular system temperature dependence. Modulation may thus exist not only to increase the diversity of produced behaviors, but also to maintain individual behaviors when environmental conditions (such as temperature) vary.

High-resolution computed tomography of lobster (Panulirus interruptus) stomach.

We used micro computed tomography to produce a high-resolution density image of the lobster (Panulirus interruptus) stomach and identified on this image the previously defined stomach ossicles. These data are the first coordinate-based, three-dimensional description of the stomach and are a necessary first step for developing biomechanical models of it. They are also interesting for several reasons in their own right. First, the ossicles showed large shape and density variations. These data suggest that different ossicles may serve different functions, with some acting as force-delivering levers, some as spring-like elements, and some as wall-like elements that resist internal stomach pressure or function as two-dimensional force-delivering plates. Second, large intra-ossicle density variations were present in individual ossicles, reminiscent of I-beams, oval bicycle frames, and similar mass-minimizing structural elements, suggesting that evolution has minimized ossicle mass and identifying which ossicle regions are most likely important in force delivery. Third, joints appeared to be either continuous density interconnections without distinct separations between the ossicles or 'floating' joints in which the ends of the two ossicles were separated by relatively large distances spanned by connective tissue. In these latter joints, although the distance between ossicle ends is likely maintained at a relatively constant value, a wide range of ossicle angles would thus be theoretically possible. Notably absent are close-apposition, morphologically specialized joints such as hinge or ball-and-socket joints.

Slow conductances could underlie intrinsic phase-maintaining properties of isolated lobster (Panulirus interruptus) pyloric neurons.

The rhythmic pyloric network of the lobster stomatogastric system approximately maintains phase (that is, the burst durations and durations between the bursts of its neurons change proportionally) when network cycle period is altered by current injection into the network pacemaker (Hooper, 1997a,b). When isolated from the network and driven by rhythmic hyperpolarizing current pulses, the delay to firing after each pulse of at least one network neuron type [pyloric (PY)] varies in a phase-maintaining manner when cycle period is varied (Hooper, 1998). These variations require PY neurons to have intrinsic mechanisms that respond to changes in neuron activity on time scales at least as long as 2 s. Slowly activating and deactivating conductances could provide such a mechanism. We tested this possibility by building models containing various slow conductances. This work showed that such conductances could indeed support intrinsic phase maintenance, and we show here results for one such conductance, a slow potassium conductance. These conductances supported phase maintenance because their mean activation level changed, hence altering neuron postinhibition firing delay, when the rhythmic input to the neuron changed. Switching the sign of the dependence of slow-conductance activation and deactivation on membrane potential resulted in neuron delays switching to change in an anti-phase-maintaining manner. These data suggest that slow conductances or similar slow processes such as changes in intracellular Ca(2+) concentration could underlie phase maintenance in pyloric network neurons.

Pyloric neuron morphology in the stomatogastric ganglion of the lobster, Panulirus interruptus.

The pyloric network of decapod crustaceans has been intensively studied electrophysiologically in the infraorders Astacidea, Brachyura, and Palinura. The morphology of some or all pyloric neurons has been well described in Astacidea and Brachyura, but less so in Palinura. Given the large evolutionary distance between these three groups, and the large amount of electrophysiology that has been performed in palinuroid species, it is important to fill this gap. We describe here the gross morphology of all six pyloric neuron types in a palinuroid, P. interruptus. All pyloric neurons had complicated, extended dendritic trees that filled the majority of the neuropil, with most small diameter processes present in a shell near the surface of the ganglion. Certain neuron types showed modest preferences for somata location in the ganglion, but these differences were too weak to use as identifying characteristics. Quantitative measurements of secondary branch number, maximum branch order, total process length, and neuron somata diameter were also, in general, insufficient to distinguish among the neurons, although AB and LP neuron somata diameters differed from those of the other types. One neuron type (VD) had a distinctive neurite branching pattern consisting of a small initial branch followed shortly by a bifurcation of the main neurite. The processes arising from these two branches occupied largely non-overlapping neuropil. Electrophysiological recordings showed that each major branch had its own spike initiation zone and that, although the zones fired correlated spikes, they generated spikes independently. VD neurons in the other infraorders have similar morphologies, suggesting that having two arbors is important for the function of this neuron. These data are similar to those previously obtained in Brachyura and Astacidea. It thus appears that, despite their long evolutionary separation, neuron morphology in these three infraorders has not greatly diverged.

Invertebrate muscles: thin and thick filament structure; molecular basis of contraction and its regulation, catch and asynchronous muscle.

This is the second in a series of canonical reviews on invertebrate muscle. We cover here thin and thick filament structure, the molecular basis of force generation and its regulation, and two special properties of some invertebrate muscle, catch and asynchronous muscle. Invertebrate thin filaments resemble vertebrate thin filaments, although helix structure and tropomyosin arrangement show small differences. Invertebrate thick filaments, alternatively, are very different from vertebrate striated thick filaments and show great variation within invertebrates. Part of this diversity stems from variation in paramyosin content, which is greatly increased in very large diameter invertebrate thick filaments. Other of it arises from relatively small changes in filament backbone structure, which results in filaments with grossly similar myosin head placements (rotating crowns of heads every 14.5 nm) but large changes in detail (distances between heads in azimuthal registration varying from three to thousands of crowns). The lever arm basis of force generation is common to both vertebrates and invertebrates, and in some invertebrates this process is understood on the near atomic level. Invertebrate actomyosin is both thin (tropomyosin:troponin) and thick (primarily via direct Ca(++) binding to myosin) filament regulated, and most invertebrate muscles are dually regulated. These mechanisms are well understood on the molecular level, but the behavioral utility of dual regulation is less so. The phosphorylation state of the thick filament associated giant protein, twitchin, has been recently shown to be the molecular basis of catch. The molecular basis of the stretch activation underlying asynchronous muscle activity, however, remains unresolved.

Using complicated, wide dynamic range driving to develop models of single neurons in single recording sessions.

Neuron models are typically built by measuring individually, for each membrane conductance, its parameters (e.g., half-maximal voltages) and maximal conductance value (g(max)). However, neurons have extended morphologies with nonuniform conductance distributions, whereas models generally contain at most a few compartments. Both the original conductance measurements and the models therefore unavoidably contain error due to the electrical filtering of neurons and the differential placement of conductances on them. Model parameters (typically g(max) values) are therefore generally altered by hand or brute force to match model and neuron activity. We propose an alternative method in which complicated, rapidly changing driving input is used to optimize model parameters. This method also ensures that neuron and model dynamics match across a wide dynamic range, a test not performed in most modeling. We tested this concept using leech heartbeat and generic tonically firing models and lobster stomatogastric and generic bursting models as targets and g(max) values as optimized parameters. In all four cases optimization solutions excellently matched target activity. Complicated, wide dynamic range driving thus appears to be an excellent method to characterize neuron properties in detail and to build highly accurate models. In these completely defined targets, the method found each target's 8-13 g(max) values with high accuracy, and may therefore also provide an alternative, functionally based method of defining neuron g(max) values. The method uses only standard experimental and computational techniques, could be easily extended to optimize conductance parameters other than g(max), and should be readily applicable to real neurons.

A computational role for slow conductances: single-neuron models that measure duration.

Humans effortlessly interpret speech and music, whose patterns can contain sound durations up to thousands of milliseconds. How nervous systems measure such long durations is unclear. We show here that model neurons containing physiological slow conductances are 'naturally' sensitive to duration, replicate known duration-sensitive neurons and can be 'tuned' to respond to a wide range of specific durations. In addition, these models reproduce several other properties of duration-sensitive neurons not selected for in model construction. These data, and the widespread presence of slow conductances in nervous systems, suggest that slow conductances might play a major role in duration measurement.