Abstract
We have developed a dynamic model of accommodation that combines independent phasic-velocity and tonic-position neural signals to control position, velocity and acceleration properties of accommodative step responses. Phasic and tonic signals were produced by neural integration of a fixed-height acceleration-pulse and variable-height velocity-step respectively to control independent acceleration and velocity properties of the step response. Duration and amplitude of the acceleration-pulse are increased with age to compensate for age-related increases of visco-elastic properties of the lens to maintain youthful velocity. The model illustrates a neural control strategy that is similar to the classical neural control model of step changes by the saccadic and vergence systems. This model could be used to estimate the stability and dynamic performance of prosthetic devices, such as accommodating intraocular lens implants.