title: Statistical test for peri-stimulus time histograms in assessing motor neuron activity.
abstract: The peri-stimulus time histogram is a valuable tool for evaluating neural connections in humans. To detect the degree to which a conditioning stimulus to a sensory nerve modulates motor neuron activity, a histogram of motor unit spike intervals after a conditioning stimulus is measured. This histogram allows the effect of the conditioning stimulus to be visualised. By comparison with a reference histogram of motor unit spike intervals after a sham stimulus, the noise caused by spontaneous firing sway can be removed. However, no valid statistical test has yet been developed to separate the physiological effect from the spontaneous sway and statistical noise. A computational method has been proposed to detect modulation caused by a conditioning stimulus. To clarify the effect of a conditioning stimulus, this new method used reference histograms to calculate a confidence interval. A simulated experiment demonstrated that about 2000 re-samplings were sufficient to estimate a confidence interval for a histogram with 1 ms bin width constructed from 300 triggers. Testing of the experimental data, measured from the tibialis anterior muscles during the elicitation of the excitatory spinal reflex, confirmed that significant peaks were produced at 30, 34, 35 and 38ms after the conditioning stimulus. These correspond appropriately to the delay of the spinal reflex.
authors.affiliation: School of Fundamental Science & Technology, Graduate School of Keio University, Japan. ushiba@bme.appi.keio.ac.jp
authors.forename: J
authors.initials: J
authors.lastname: Ushiba
authors.forename: Y
authors.initials: Y
authors.lastname: Tomita
authors.forename: Y
authors.initials: Y
authors.lastname: Masakado
authors.forename: Y
authors.initials: Y
authors.lastname: Komune
authors.forename: Y
authors.initials: Y
authors.lastname: Muraoka
mesh_terms: D004558:Electric Stimulation; D004576:Electromyography; D006801:Humans; D009046:Motor Neurons / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic