Computational model of velocity generation from patterns of otolith activation during off-vertical axis rotation (OVAR).
Item
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Title
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Computational model of velocity generation from patterns of otolith activation during off-vertical axis rotation (OVAR).
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Identifier
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AAI9000065
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identifier
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9000065
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Creator
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Schnabolk, Charles.
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Contributor
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Adviser: Theodore Raphan
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Date
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1989
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Language
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English
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Publisher
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City University of New York.
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Subject
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Computer Science | Biology, Neuroscience
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Abstract
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Rotation about an off vertical axis (OVAR) causes continuous unidirectional horizontal nystagmus in darkness (Guedry, 1965). Evidence from a wide range of studies suggest that the otoliths are the primary effectors in generating the continuous nystagmus. The purpose of the dissertation was to develop a model which show how the continuous nystagmus during OVAR might be generated by estimating the velocity of the head from changing patterns of otolith excitation and inhibition. The model examined how noise and the distribution of the polarization vectors affect the estimation. We also examined how the model might be extended to three dimensions to gain an understanding of how position signals are processed to obtain an estimate of head velocity.;In one dimension the estimation of velocity is based on a "template matching" algorithm. It is assumed that a signal arising in each cell of the macula is delayed by a certain time (T). Thus, as the head rotates in the gravitational field a delayed pattern representing a previous position of the head is available as a "template" that can be compared to the pattern associated with the present position of the head.;The extension of the model to three dimension shows that: (1) two patterns do not contain sufficient information to uniquely specify the velocity, (2) an estimate utilizing four patterns computes an accurate estimate of head velocity based on otolith position information, (3) the estimator and velocity storage integrator form a robust compensator for head rotations in gravitational environments.
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Type
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dissertation
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Source
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PQT Legacy CUNY.xlsx
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degree
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Ph.D.
