Abstract
The extent to which individual neural networks can producephase-constant motor patterns as cycle frequency is altered has notbeen studied extensively. I investigated this issue in thewell-defined, rhythmic pyloric neural network. When pyloric cyclefrequency is altered three- to fivefold, pyloric inter-neuronaldelays shift by hundreds to thousands of msec, and all pyloricpattern elements show strong phase maintenance. The experimentalparadigm used is unlikely to activate exogenous inputs to thenetwork, and these delay changes are thus likely to arise fromphase-compensatory mechanisms intrinsic to the network. Pyloricinter-neuronal delays depend on the time constants of the network‘ssynapses and of the membrane properties of its neurons. The observeddelay shifts thus suggest that, in response to changes in overallcycle frequency, these constants vary so as to maintain patternphasing.
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Hooper, S.L. Phase Maintenance in the Pyloric Pattern of the Lobster (Panulirus interruptus) Stomatogastric Ganglion. J Comput Neurosci 4, 191–205 (1997). https://doi.org/10.1023/A:1008822218061
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DOI: https://doi.org/10.1023/A:1008822218061