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The Pupil Control System Omer Dushek and Heena Lakhani

This study explores the relationship between retinal neuron firing and iris muscles in the context of the pupil control system. Three models are presented, with a focus on exploring the effects of different parameters and the introduction of a delay. The findings have potential applications in eye disease detection.

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The Pupil Control System Omer Dushek and Heena Lakhani

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  1. The Pupil Control SystemOmer Dushek and Heena Lakhani

  2. The Eye

  3. The Retina

  4. The Iris Muscles

  5. Assumptions • The light has constant intensity and is shone constantly into the pupil • The light is shone on the edge of the pupil and the location of the light does not change • Direct relation between retinal neuron firing and iris muscles • Parameters (Rmin, Rmax, R1, R2) for models 2 and 3

  6. MODEL 1 • Equations: • Firing rate is dependent on: • pupil radius • amount of light that has contact with pupil • df/dt= a*G(r)*Intensity Change in radius of pupil • Firing rate • dr/dt= -b*f

  7. WRONG AND A DAY LOST!!! • a*G(r)*Intensity is not a rate; it is actually the number of neurons firing • Assuming instantaneous results; no delay rate -The model does not yield oscillating results; get decaying results -Delay: 200 ms • Different constants for pupil constriction and dilation

  8. Introducing A Delay – Model 2 & 3 F0 – Optimal number of neurons firing F1 – Number of neurons that will fire as a result of incident light. k – scaling parameter g(r) – Fraction of F1 actually making it through iris at radius r.

  9. Model 2 • Assume a form for g(r) • Some analysis -Analytical solution? yup -only oscillatory solutions -prediction for delay

  10. Model 3 • Assume a form for g(r) • Analysis -Analytical solution? no -Can find linear stability

  11. Conclusions • Evolutionary reason for rate of constriction/dilation of eye! • Why should damping exist? • Application: eye disease detection

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