Abstract
Visual impairment has serious impact on our quality of life. Although stem cell-based therapies contribute to improve retinal diseases, it is essentially critical to have quantitative data of the physiological characteristics of retinal cellular functions and related neural networks for reliable treatment. In the phototransduction system of retinal photoreceptor cells, visual pigments are activated by the incident light and stimulate transducin, which in turn send electrical signals to downstream neural networks. A single visual pigment may activate hundreds of transducin, amplifying the incoming signal. Efficacy of the signal amplification system has been reported to be light intensity-dependent. Experimentally, a positive correlation between light intensity and activated transducin has been observed at a lower stimulation intensity range, whereas activated transducin starts to decrease at very high intensity light stimulation. Since none of the proposed phototransduction models were able to reproduce the complex characteristics of the signal transduction system of retinal photoreceptor cells, we propose a model that may reproduce the light intensity-dependent amplification of incoming signals in both rods and cones. The present model successfully reproduced the experimental data.
