ABSTRACT
It was recently established that the axial power, the refractive power required by the eye for a sharp retinal image in an eye of a certain axial length, and the total refractive power of the eye may both be described by a bi-exponential function as a function of age (Rozema, 2023). Inspired by this result, this work explores whether these bi-exponential functions are able to simulate the various known courses of refractive development described in the literature, such as instant emmetropization, persistent hypermetropia, developing hypermetropia, myopia, instant homeostasis, modulated development, or emmetropizing hypermetropes. Moreover, the equations can be adjusted to match the refractive development of school-age myopia and pseudophakia up to the age of 20 years. All of these courses closely resemble those reported in the previous literature while simultaneously providing estimates for the underlying changes in axial and whole eye power.
Subject(s)
Emmetropia , Hyperopia , Myopia , Refraction, Ocular , Humans , Refraction, Ocular/physiology , Myopia/physiopathology , Child , Adolescent , Hyperopia/physiopathology , Young Adult , Emmetropia/physiology , Child, Preschool , Axial Length, Eye , Pseudophakia/physiopathology , Adult , Eye/growth & development , Aging/physiology , Refractive Errors/physiopathologyABSTRACT
PURPOSE: To present a paraxial method to estimate the influence of variations in ocular biometry on changes in refractive error (S) at a population level and apply this method to literature data. METHODS: Error propagation was applied to two methods of eye modelling, referred to as the simple method and the matrix method. The simple method defines S as the difference between the axial power and the whole-eye power, while the matrix method uses more accurate ray transfer matrices. These methods were applied to literature data, containing the mean ocular biometry data from the SyntEyes model, as well as populations of premature infants with or without retinopathy, full-term infants, school children and healthy and diabetic adults. RESULTS: Applying these equations to 1000 SyntEyes showed that changes in axial length provided the most important contribution to the variations in refractive error (57%-64%), followed by lens power/gradient index power (16%-31%) and the anterior corneal radius of curvature (10%-13%). All other components of the eye contributed <4%. For young children, the largest contributions were made by variations in axial length, lens and corneal power for the simple method (67%, 23% and 8%, respectively) and by variations in axial length, gradient lens power and anterior corneal curvature for the matrix method (55%, 21% and 14%, respectively). During myopisation, the influence of variations in axial length increased from 54.5% to 73.4%, while changes in corneal power decreased from 9.82% to 6.32%. Similarly, for the other data sets, the largest contribution was related to axial length. CONCLUSIONS: This analysis confirms that the changes in ocular refraction were mostly associated with variations in axial length, lens and corneal power. The relative contributions of the latter two varied, depending on the particular population.
Subject(s)
Axial Length, Eye , Biometry , Refraction, Ocular , Refractive Errors , Humans , Refractive Errors/physiopathology , Refractive Errors/diagnosis , Biometry/methods , Refraction, Ocular/physiology , Child , Axial Length, Eye/diagnostic imaging , Cornea/diagnostic imaging , Adult , Infant , Child, Preschool , Infant, Newborn , Male , Female , AdolescentABSTRACT
Nowadays, numerous studies have investigated the modeling of efficient neural encoding processes in the retina of the eye to encode the sensory data. Retina, as the innermost coat of the eye, is the first and the most important area of the visual neural system of mammalians, which is responsible for neural processes. Retina encodes the information of light intensity into a sequence of spikes, and sends them to retinal ganglion cells (RGCs) for further processing. An appropriate retinal encoding model should be adapted to the real retina as much as possible by considering the physiological constraints of the visual pathway to transfer most of the information of the input signal to the brain without too much redundancy of the channel. In this paper, inspired from the existing linear models of retinal encoding process, which have employed input noise and the spatial locality of the RGCs receptive fields (RFs) in the calculation of the encoding matrix, two extra physiological constraints, adapted from the real retina are taken into account so as to achieve a more realistic model for themammalian retina. These new constraints that are the correlation between RGCs and the spatial locality of the photoreceptors' projective fields (PFs), are modeled in a mathematical form and analyzed in detail. To quantify fidelity of the proposed encoding matrix and prove its superiority over existing models, various parameters of the models are calculated and presented in this paper: mean square error between the original and reconstructed image (MSE), the redundancy of the channel, the amount of information transferred through the channel, and the amount of wasted capacity for carrying input noise, to name a few. The results of these calculations show that the proposed model transfers input information with less redundancy of the channel. In other words, it reduces a portion of channel capacity which is wasted for carrying the input noise in comparison to the existing models. Also, due to considering extra physiological constraints in the proposed model, it is acceptable to have a slightly higher amount of MSE value in order to become similar to the real retina.