Ocular torsion responses to sinusoidal electrical vestibular stimulation
- PMID: 29170018
- PMCID: PMC5786448
- DOI: 10.1016/j.jneumeth.2017.11.012
Ocular torsion responses to sinusoidal electrical vestibular stimulation
Abstract
Background: Eye movements evoked by electrical vestibular stimulation (EVS) offer potential for diagnosing vestibular dysfunction. However, ocular recording techniques are often too invasive or impractical for routine clinical use. Furthermore, the kinematic nature of the EVS signal is not fully understood in terms of movement sensations.
New method: We apply sinusoidal EVS stimuli varying from 0.05 to 20Hz, and record the eye in darkness using an infrared camera. Eye movement was measured offline using commercially available software to track iris striations. Response gain and phase were calculated separately for eye position, velocity and acceleration across all frequencies, to determine how the brain interprets the EVS signal.
Results: Ocular torsion responses were observed at the same frequency as the stimulus, for all frequencies, while lateral/vertical responses were minimal or absent. Response gain and phase resembled previously reported responses to natural rotation, but only when analysing eye velocity, not position or acceleration.
Comparison with existing method(s): Our method offers a simple, affordable, reliable and non-invasive method for tracking the ocular response to EVS. It is more convenient than scleral coil recordings, or marking the sclera to aid video tracking. It also allows us to assess the torsional VOR at frequencies not possible with natural stimuli.
Conclusions: Ocular torsion responses to EVS can be readily assessed using sinusoidal stimuli combined with an infrared camera. Gain and phase analysis suggests that the central nervous system interprets the stimulus as head roll velocity. Future work will assess the diagnostic potential for patients with vestibular disorders.
Keywords: Electrical vestibular stimulation; Ocular torsion; Vestibulo-ocular reflex.
Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
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