A linear homeomorphic eye movement model that produces 3D saccadic eye movements consistent with anatomical and physiological evidence is introduced in this second part of a two-paper sequence. Central to the model is the implementation of a time-optimal neural control strategy involving six linear muscle models that faithfully represent the dynamic characteristics of 3D saccades. The muscle is modeled as a parallel combination of viscosity [Formula: see text] and series elasticity [Formula: see text], connected to the parallel combination of active-state tension generator [Formula: see text], viscosity element [Formula: see text], and length tension elastic element [Formula: see text]. The neural input for each muscle is separately maintained while the effective pulling direction is modulated by its respective pulley. The results demonstrate that a time-optimal, 2D commutative neural controller, together with the pulley system, actively functions to implement Listing's law during both static and dynamic simulations and provide an excellent match with the experimental data. The parameters and neural input to the muscles are estimated using a time domain system identification technique from saccade data, with an excellent match between the model estimates and the data. A total of 20 horizontal, 5 vertical and 62 oblique saccades are analyzed.
Keywords: 3D rotational dynamics; Listing’s law; Saccades; main sequence diagrams; oculomotor plant; system identification technique; time-optical control.