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Muscles express motor patterns of non-innervating neural networks by filtering broad-band input

Abstract

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.

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Figure 1: In some pyloric muscles, overall spike frequency codes steady-state average contraction amplitude.
Figure 2: A muscle innervated by PY neurons expressed a gastric mill network contraction pattern even though no gastric mill neurons innervate the muscle.
Figure 3: Although no cardiac sac neurons innervate it, the extremely slow dorsal PD muscle primarily contracted in a pattern matching the very slow cardiac sac rhythm.
Figure 4: Different muscles can respond to different frequency domains in the same neural signal.

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Acknowledgements

This work was supported by Ohio University, NSF and NIMH. We thank R.A. DiCaprio for discussion and advice and A. L. Weaver for setting up the CED to stimulator interface and writing scripts to transform CED events into waveforms used to drive the stimulator.

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Correspondence to Scott L. Hooper.

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Morris, L., Thuma, J. & Hooper, S. Muscles express motor patterns of non-innervating neural networks by filtering broad-band input. Nat Neurosci 3, 245–250 (2000). https://doi.org/10.1038/72955

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