Neural Processing of Gravitoinertial Cues in Humans. III. Modeling Tilt and Translation Responses

Author:

Merfeld D. M.1,Zupan L. H.1

Affiliation:

1. Jenks Vestibular Physiology Laboratory, Massachusetts Eye and Ear Infirmary, Department of Otology and Laryngology, Harvard Medical School, Boston, Massachusetts 02114

Abstract

All linear accelerometers measure gravitoinertial force, which is the sum of gravitational force (tilt) and inertial force due to linear acceleration (translation). Neural strategies must exist to elicit tilt and translation responses from this ambiguous cue. To investigate these neural processes, we developed a model of human responses and simulated a number of motion paradigms used to investigate this tilt/translation ambiguity. In this model, the separation of GIF into neural estimates of gravity and linear acceleration is accomplished via an internal model made up of three principal components: 1) the influence of rotational cues (e.g., semicircular canals) on the neural representation of gravity, 2) the resolution of gravitoinertial force into neural representations of gravity and linear acceleration, and 3) the neural representation of the dynamics of the semicircular canals. By combining these simple hypotheses within the internal model framework, the model mimics human responses to a number of different paradigms, ranging from simple paradigms, like roll tilt, to complex paradigms, like postrotational tilt and centrifugation. It is important to note that the exact same mechanisms can explain responses induced by simple movements as well as by more complex paradigms; no additional elements or hypotheses are needed to match the data obtained during more complex paradigms. Therefore these modeled response characteristics are consistent with available data and with the hypothesis that the nervous system uses internal models to estimate tilt and translation in the presence of ambiguous sensory cues.

Publisher

American Physiological Society

Subject

Physiology,General Neuroscience

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