Conventional feedback control models
of the oculomotor system fail to account for the destabilizing effects of
neural transmission delays. To address this shortcoming, a linear quadratic
tracking algorithm used to control smoothly pursuing eye movements of various
target trajectories is presented. Based on the type of input to the system, it
is shown that stability, in the presence of large motor feedback delays, can be
maintained by modulating weighting factors intrinsic to the model.
Conditions,
such as the initial orientation of the eye relative to the location of where a
target first becomes salient and the possible oscillatory nature that the
reference trajectory may present, play important roles in determining the
optimal cost to go motor control strategy at the onset of a tracking movement.
Human perception is the process of acquiring, interpreting,
selecting and organizing sensory information to effectively interact with the
environment. It is argued that the ability to perceive and direct visual
attention to an object that warrants more detailed analysis is the most
important of the senses. The oculomotor system has evolved to serve this
purpose and, consequently, has important communicative value for studying
neuromuscular integration.
Research involving sensorimotor control seeks to answer the
fundamental question: How does our brain select inputs to produce a desired
intention and manifest it in the form of movement. The difficulty associated
with this question becomes more apparent for multi-body, multi-dimensional
systems whose equations of motion are nonlinear and coupled. Since the eye is
confined to three rotational degrees of freedom, and because the actions of its
extraocular muscles are direct, the oculomotor system provides an initial
context for gaining insight into more complex strategies of sensorimotor
control.Read More......
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