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Updated: Apr 15, 2026
Stochastic Noise Application for the Assessment of Medial Vestibular Nucleus Neuron Sensitivity In Vitro
Published on: August 28, 2019
Evaluating Inhibition of Motoneuron Firing From Electromyogram Data to Assess Vestibular Output Using Vestibular
S R Prakash1, Barbara S Herrmann, Rupprecht Milojcic
11Harvard-MIT Division of Health Science and Technology, Speech and Hearing Bioscience and Technology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; 2Department of Otology and Laryngology, Harvard Medical School, Boston, Massachusetts, USA; 3Department of Otolaryngology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, USA; 4Department of Audiology, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, USA; and 5Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston, Massachusetts, USA.
Objectives:
Vestibular evoked myogenic potentials (VEMPs) are due to vestibular responses producing brief inhibitions of muscle contractions that are detectable in electromyographic (EMG) responses. VEMP amplitudes are traditionally measured by the peak to peak amplitude of the averaged EMG response (VEMPpp) or by a normalized VEMPpp (nVEMPpp). However, a brief EMG inhibition does not satisfy the statistical assumptions for the average to be the optimal processing strategy. Here, it is postulated that the inhibition depth of motoneuron firing is the desired metric for showing the influence of the vestibular system on the muscle system. The authors present a metric called "VEMPid" that estimates this inhibition depth from the EMG data obtained in a usual VEMP data acquisition. The goal of this article was to compare how well VEMPid, VEMPpp, and nVEMPpp track inhibition depth.
Design:
To find a robust method to compare VEMPid, VEMPpp, and nVEMPpp, realistic physiological models for the inhibition of VEMP EMG signals were made using VEMP data from four measurement sessions on each of the five normal subjects. Each of the resulting 20 EMG-production models was adjusted to match the EMG autocorrelation of an individual subject and session. Simulated VEMP traces produced by these models were used to compare how well VEMPid, VEMPpp, and nVEMPpp tracked model inhibition depth.
Results:
Applied to simulated and real VEMP data, VEMPid showed good test-retest consistency and greater sensitivity at low stimulus levels than VEMPpp or nVEMPpp. For large-amplitude responses, nVEMPpp and VEMPid were equivalent in their consistency across subjects and sessions, but for low-amplitude responses, VEMPid was superior. Unnormalized VEMPpp was always worse than nVEMPpp or VEMPid.
Conclusions:
VEMPid provides a more reliable measurement of vestibular function at low sound levels than the traditional nVEMPpp, without requiring a change in how VEMP tests are performed. The calculation method for VEMPid should be applicable whenever an ongoing muscle contraction is briefly inhibited by an external stimulus.
