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C.M. Schor, S.R. Bharadwaj, C.D. Burns; Dynamic Performance of Accommodating–Intraocular Lenses: A Simulation–Based Study . Invest. Ophthalmol. Vis. Sci. 2006;47(13):5843.
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© ARVO (1962-2015); The Authors (2016-present)
A dynamic model of accommodation was developed using Matlab & Simulink that simulates stability & dynamic performance of accommodating intraocular lenses (A–IOL’s) when they are controlled under negative feedback of the accommodation system. The model simulates first– & second–order dynamics of accommodation that result from interactions between the accommodative neural controller of an older eye & the A–IOL material with biomechanical properties of a younger eye. An interactive web model of A–IOL is available at http://schorlab.berkeley.edu/.
The model predicts static & dynamic properties of the accommodative step response based on age–dependent biomechanics of accommodative plant & neural control signals. The model independently controls the dynamic & static characteristics of the response with phasic–velocity & tonic–position signals respectively. Three A–IOL simulations were performed. In simulation I, the visco–elasticity of a 45–yr old matrix was replaced with that of a 25–yr old matrix. In simulation II, only elasticity of a 45–yr old matrix was replaced with that of a 25–yr old matrix while the matrix viscosity was retained. In simulation III, the visco–elasticity of a 45–yr old matrix was replaced with that of a polymer that was used previously as an A–IOL material (Koopmans et al., 2003; 2004). The 45–yr old lens capsule elasticity was retained in all simulations. The simulations illustrate the influence of decreased visco–elasticity of the A–IOL on dynamic accommodation & how adaptation of phasic & tonic signals can restore normal response dynamics.
Reducing the visco–elasticity of A–IOL to equal a younger lens increased the static amplitude of accommodation but with marked overshoots & oscillations in all simulations. However, the dynamic response could be stabilized by decreasing the amplitudes of phasic & tonic neural control signals.
The model is a tool to simulate static & dynamic properties of A–IOL materials with visco–elastic properties of a young lens & how adjustments of neural control properties of the older eye can restore stable dynamics. Simulations indicate that neural control must be recalibrated to avoid unstable dynamic accommodation with the A–IOL.
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