The Role of Neuromodulators in Setting Cellular and Network Properties for Operation

Neuromodulators act on motor circuits by affecting the properties of the underlying neural networks and their individual neuronal elements. Alterations occur either in the excitability of neurons or the properties of their synaptic connectivity. This has been demonstrated for all consecutive layers of neuronal processing, from the level of the sensory neurons to the level of the muscle fibers generating force, thereby closing the loop for the organism-environment interaction.

The motor systems of invertebrates, ranging from mollusks to annelids and arthropods, control behaviors such as walking, flying, swimming, crawling, feeding, not to mention more complex behaviors such as prey capture or courtship. Knowledge about the underlying network and cellular mechanisms of neuromodulation is not only incomplete, but highly "patchy." This is in contrast to the potential of some of these systems, in which a large body of in-depth knowledge on the motor behaviors, the contributing component neurons, and the generation of various motor outputs has been accumulated. Component neurons of motor networks have been shown to exhibit intrinsic bursting properties upon elevated levels of neuromodulators, for example, in the presence of octopamine in the locust flight system (Ramirez and Pearson 1991a, b). The same is true for motor neurons in insect walking systems. These motor neurons can exhibit increased excitability in response to neuromodulators, like 5-HT (e.g., Parker 1995), or plateauing in the presence of elevated levels of octopa-mine (Ramirez and Pearson 1991a). The underlying ionic and subcellular mechanisms have not been established, but spike broadening and spike afterhyper-polarization appear to contribute to alterations in spike frequency adaptation.

One of the principle invertebrate motor circuits in which neuromodulatory action has been studied in great detail is the crustacean STG, which consists of approximately 30 neurons, primarily motor neurons of muscles moving the different parts of the stomach (Selverston et al. 1976). Several discrete rhythms generated by this network, or by subsets of its elements, have been described. Two largely distinct motor networks generate the slow rhythm of the gastric mill

(0.05-0.2 Hz) and the faster pyloric rhythm (about 1 Hz). Within the STG, most of the chemical and electrical synaptic connections as well as the electrical properties of individual neurons are well known. Different rhythms are induced because of the action of neuromodulatory neurons situated in more rostral ganglia (e.g., the commissural and the esophageal ganglia). In fact, the neuronal network within the stomatogastric network requires neuromodulatory input, as suppression of this input by blocking transmission in the afferent stomatogastric nerve blocks reversibly the gastric and pyloric rhythmic activity (Robertson and Moulins 1981).

In the pyloric network, small modifications in specific voltage-gated ionic currents of particular component neurons are important for shaping the rhythm (Harris-Warrick 2002). Neuromodulators, such as biogenic amines and neuropeptides, target these ionic currents to change the firing patterns of the network (Peck et al. 2001). Knowledge of the cellular mechanisms of peptidergic modulation is increasingly available. For example, three proctolin-containing neurons affect the pyloric rhythm differently, perhaps reflecting different co-transmitters that these neurons possess (Nusbaum et al. 2001). Thus, in the STG one has good knowledge on how particular neuromodulators or co-transmitters affect the cellular and molecular machinery of particular neurons (Harris-Warrick 2000; Nusbaum et al. 2001; Nusbaum 2002). Similarly, information on the contribution of particular ionic currents and how they are targeted by neuromodu-lators is presently available for some vertebrate motor systems, for example, the central pattern generators (CPGs) in the mouse spinal cord, which also has the advantage of being amenable to use the tools of genetics (Kiehn and Butt 2003).

The lack of detailed knowledge on the cellular and network mechanisms of neuromodulation in many more complex invertebrate motor circuits is in con-trastto the current knowledge on specific peripheral effects of neuromodulators, for example, on the muscular system of insects and mollusks, where cellular mechanisms have been identified (see below).

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