December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Modelling the neural control of ocular accommodation
Author Affiliations & Notes
  • Jenny Read
    Newcastle University
  • Christos Kaspiris-Rousellis
    Newcastle University
  • Toby Wood
    Newcastle University
  • Bing Wu
    Magic Leap Inc
  • Björn Vlaskamp
    Magic Leap Inc
  • Clifton Schor
    University of California at Berkeley
  • Footnotes
    Acknowledgements  Magic Leap Inc
Journal of Vision December 2022, Vol.22, 3272. doi:https://doi.org/10.1167/jov.22.14.3272
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      Jenny Read, Christos Kaspiris-Rousellis, Toby Wood, Bing Wu, Björn Vlaskamp, Clifton Schor; Modelling the neural control of ocular accommodation. Journal of Vision 2022;22(14):3272. https://doi.org/10.1167/jov.22.14.3272.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Ocular accommodation is the process of adjusting the eye’s crystalline lens so as to bring the retinal image into sharp focus. The major stimulus to accommodation is therefore retinal defocus, and in essence, the job of accommodative control is to send a signal to the ciliary muscle which will minimise the magnitude of defocus. This is complicated by the sensorimotor latencies within the system, which delay both information about defocus and the accommodation changes made in response, and by the sluggish response of the motor plant. Both of these can lead to instability during steady fixation, phase delays during tracking of moving objects, and overshoots and oscillations in the response to a step change in distance, and/or excessively large oscillations in response to changing distance. A common technique to reduce these problems in motor control is the use of a “forward model” or Smith predictor, whereby the control system uses an internal model to predict the future effect of its planned actions, allowing for sensorimotor delays. Following previous work, we conclude that most aspects of accommodation are well explained by dual integral control, with a “fast” or “phasic” integrator enabling response to rapid changes in demand, but which hands over control to a “slow” or “tonic” integrator which maintains the response to steady demand. For the first time, we combine dual integral control with a Smith predictor. In addition, we propose a novel proportional-control signal, not available to the Smith predictor, to account for the power spectrum of accommodative microfluctuations during steady fixation, which may be important in hunting for optimal focus, and for the nonlinear resonance observed for low-amplitude, high-frequency input.

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