Journal of Neurophysiology, Vol 64, Issue 5 1555-1573, Copyright © 1990 by APS

ARTICLES

Sensory input induces long-lasting changes in the output of the lobster pyloric network

S. L. Hooper, M. Moulins and L. Nonnotte
Laboratoire de Neurobiologie et Physiologie Comparees, Universite de Bordeaux I, Arcachon, France.

1. A long-lasting restructuring of the pyloric neural network of the lobster stomatogastric nervous system (STS) by a multisynaptic sensory afferent is described. This restructuring can be obtained either by mechanical stimulation of the pyloric region of the stomach or by brief high-frequency electrical stimulation of a nerve that innervates this region, the lateral posterolateral nerve (lpln). Electron microscopy shows that this nerve contains several thousand very small fibers (approximately 0.3 microns diam), the activation of some subset of which is responsible for the effects of lpln stimulation. 2. These stimulation paradigms result in both short-duration changes in pyloric activity and modulatory effects long outlasting the stimulus end. The long-lasting changes include the cessation of rhythmic ventricular dilator (VD) and lateral pyloric (LP) neuron activity, and thus result in a reduced pyloric pattern in which only the pyloric dilator (PD), inferior cardiac (IC), anterior burster (AB), and pyloric (PY) neurons are active. 3. Tonic low-frequency lpln stimulation, alternatively, results in the VD neuron rhythmically firing long spike bursts with a cycle frequency much slower than that of the pyloric network while an otherwise complete pyloric pattern continues. In this new bursting pattern the VD neuron fires exclusively with another STS neural network, the cardiac sac (CS) network, and thus functionally "switches" from the pyloric to the CS network. This switch of the VD neuron from the pyloric to the CS network also occurs when the CS network is spontaneously active. 4. Our results thus demonstrate that sensory input can provoke a long-lasting modification of the functional configuration of a rhythmic neural network. They further extend the concept of flexibility in nervous systems by showing that individual neurons can belong to more than one neural network, "switching" from one to another in response to sensory input or spontaneous central nervous activity.

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