Capturing Age-Related Alternations In The Human Smooth Pursuit Mechanism By Volterra Models

A method for quantifying the effects of aging in the human smooth pursuit system is proposed. The dynamical properties of the oculomotor system are characterized by means of a truncated Volterra model that has previously been utilized for distinguishing between patients diagnosed with Parkinson's disease and healthy controls. The orthonormal basis of Laguerre functions is employed for the parameterization of the Volterra model kernels. The Volterra-Laguerre model coefficients are estimated from gaze direction data collected by means of eye tracking from healthy adults of different age responding to specially designed visual stimuli. The experimental results suggest that aging primarily impacts the linear term of the Volterra model through gain and frequency bandwidth reduction. Parameter variability increases with age, both in the linear and quadratic term of the Volterra model. The mean values of the nonlinear term coefficients appear though to be essentially independent of age within the studied population.