Micromotions of the eyes while fixating a target are called fixation eye movements. Little is known about effects of these micromotions on perception. It has been suggested that tremor and drifts, which are principal component of fixation eye movements, enhance particular spatial frequency bands of visual input (Rucci et al., 2007). Some simulations have indicated that visual information becomes clearer when microsaccades, small jumps of gazes, occur (Donner et al., 2007). Fukuoka & Kohama (2010) composed a neuron network model of the retina which takes into account the density distribution of cone cells on the basis of a mathematical model (Hennig & Worgotter, 2007). The results of their simulation analyses suggest that the modification of visual information by microsaccades appears prominently in M-type ganglion cells. Also, tremor and drifts enhance particular spatial frequency components, which is consistent with psychophysical experiments. However, their model had a rectangular shape and saturated the peak density of cone cells in the fovea because of limited computing resources. In this study, we propose a mathematical model of a retinal network considering characteristics of peripheral vision to evaluate the influence of fixation eye movements. We modified Fukuoka's model of which model-scale, shape of the retina, and photoreceptor distribution to make it more realistic. Our results show that microsaccades enhance the membrane potential of only M-type cells when visual input is composed by a low-frequency vertical sinusoidal grating. On the other hand, they do not influence the resting state of M or P-type cells when random dot patterns, which consist of particular spacial frequencies, are given. These random dot patterns were perceived as if they are fluctuating and unstable. Simulation results suggest that the visual system may not discriminate retinal slips and fluctuations of visual images because microsaccades do not activate the retinal neuron network.