title: The proportion of common synaptic input to motor neurons increases with an increase in net excitatory input.
abstract: α-Motor neurons receive synaptic inputs from spinal and supraspinal centers that comprise components either common to the motor neuron pool or independent. The input shared by motor neurons--common input--determines force control. The aim of the study was to investigate the changes in the strength of common synaptic input delivered to motor neurons with changes in force and with fatigue, two conditions that underlie an increase in the net excitatory drive to the motor neurons. High-density surface electromyogram (EMG) signals were recorded from the tibialis anterior muscle during contractions at 20, 50, and 75% of the maximal voluntary contraction force (in 3 sessions separated by at least 2 days), all sustained until task failure. EMG signal decomposition identified the activity of a total of 1,245 motor units. The coherence values between cumulative motor unit spike trains increased with increasing force, especially for low frequencies. This increase in coherence was not observed when comparing two subsets of motor units having different recruitment thresholds, but detected at the same force level. Moreover, the coherence values for frequencies <5 Hz increased at task failure with respect to the beginning of the contractions for all force levels. In conclusion, the results indicated that the relative strength of common synaptic input to motor neurons increases with respect to independent input when the net excitatory drive to motor neurons increases as a consequence of a change in force and fatigue.
authors.affiliation: Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany; and BioLab, Biomedical Engineering Laboratory, Department of Engineering, University Roma TRE, Rome, Italy.
authors.forename: Anna Margherita
authors.initials: AM
authors.lastname: Castronovo
authors.affiliation: Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany; and.
authors.forename: Francesco
authors.initials: F
authors.lastname: Negro
authors.affiliation: BioLab, Biomedical Engineering Laboratory, Department of Engineering, University Roma TRE, Rome, Italy.
authors.forename: Silvia
authors.initials: S
authors.lastname: Conforto
authors.affiliation: Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology, Bernstein Center for Computational Neuroscience, University Medical Center Göttingen, Georg-August University, Göttingen, Germany; and dario.farina@bccn.uni-goettingen.de.
authors.forename: Dario
authors.initials: D
authors.lastname: Farina
mesh_terms: D000328:Adult; D000465:Algorithms; D004576:Electromyography; D006801:Humans; D008297:Male; D009046:Motor Neurons / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology; D018763:Muscle Fatigue / Q000502:physiology; D018485:Muscle Fibers, Skeletal / Q000502:physiology; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology; D011999:Recruitment, Neurophysiological / Q000502:physiology; D013569:Synapses / Q000502:physiology*
keywords: coherence; common synaptic input; motor neuron; motor neuron spike trains; net excitation; task failure