title: 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.
authors.affiliation: Department of Physiology and Biophysics, Mt. Sinai Medical School, Box 1218, 1 Gustave L. Levy Place, New York, New York 10029, USA.
authors.forename: L G
authors.initials: LG
authors.lastname: Morris
authors.forename: J B
authors.initials: JB
authors.lastname: Thuma
authors.forename: S L
authors.initials: SL
authors.lastname: Hooper
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D004558:Electric Stimulation; D006321:Heart / Q000294:innervation / Q000502:physiology; D009046:Motor Neurons / Q000166:cytology / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology*; D009132:Muscles / Q000294:innervation* / Q000502:physiology*; D008121:Nephropidae / Q000166:cytology / Q000502:physiology*; D009415:Nerve Net / Q000166:cytology / Q000502:physiology*; D009469:Neuromuscular Junction / Q000166:cytology / Q000502:physiology; D013270:Stomach / Q000294:innervation / Q000502:physiology; D016474:Weight-Bearing