Characteristics of fixational eye movements in people with macular disease

Abstract

Purpose: Fixation stability is known to be poor for people with macular disease and has been suggested as a contributing factor for the poor visual performance of these individuals. In this study, we examined the characteristics of the different components of fixational eye movements and determined the component that plays a major role in limiting fixation stability in people with macular disease.

Methods: Sixteen observers with macular disease and 14 older adults with normal vision (control observers) monocularly fixated a small cross presented using a Rodenstock scanning laser ophthalmoscope, for trials of 30 seconds. The retinal image and the position of the cross on the retina were recorded digitally. Eye movements were extracted from the recorded videos at a sampling rate of 540 Hz using a cross-correlation technique. A velocity criterion of 8°/s was used to differentiate between slow drifts and microsaccades.

Results: Observers with macular disease demonstrated higher fixation instability, larger amplitudes of slow drifts and microsaccades, and lower drift velocities, when compared with older adults with normal vision. The velocity and the rate of microsaccades were comparable between the two groups of observers. Multiple linear regression analysis showed that the amplitude of microsaccades, and to a smaller extent, the amplitude of slow drifts, play a major role in limiting fixation stability.

Conclusions: Fixation stability in people with macular disease is primarily limited by the amplitude of microsaccades, implying that rehabilitative strategies targeted at reducing the amplitude of microsaccades should improve fixation stability, and may lead to improved visual functions.

Keywords: fixation stability; fixational eye movements; low vision; macular disease.

Figure 1

Eye position traces of two observers, whose fixation stability (according to BCEA) was the median of their respective groups, are shown here. For clarity, the horizontal (red) and vertical (blue) eye position traces are offset vertically in each panel.

Figure 2

Box-and-whisker plots comparing fixation stability, quantified as BCEA (left) or the area enclosed by the isoline corresponding to 68% of the probability density function of the eye position distribution (right), for the two groups of observers. The upper and lower bound of each box represent the 75th and 25th percentiles of the distribution, and the median is represented by the thick line inside the box. The top and bottom ends of the whisker represent the 95th and 5th percentiles of the distribution, respectively. The diamond symbol represents the mean value.

Figure 3

Left: Fixation stability quantified by the area enclosed by the isoline is plotted as a function of BCEA. The data show a very high correlation and the slope of the line (on log–log axes) is 0.99. However, there is a constant offset from the 1:1 line (gray dashed line). Right: The isoline and BCEA values are compared in a Bland-Altman plot. The mean difference (using log values) between the two methods is statistically different from 0 (represented by the middle black dashed line), consistent with the left panel that the isoline values are smaller than the BCEA values. All except one data point falls within the ±95% limits of agreement (gray dashed lines).

Figure 4

Box-and-whisker plots comparing the number of microsaccades per second between the two groups of observers. Details of the box and whiskers are as in Figure 2.

Figure 5

Box-and-whisker plots comparing the vector velocities of slow drifts (left) and microsaccades (right) between the two groups of observers. Details of the box and whiskers are as in Figure 2.

Figure 6

Box-and-whisker plots comparing the amplitudes of slow drifts (left) and microsaccades (right) between the two groups of observers. Details of the box and whiskers are as in Figure 2.

Figure 7

Fixation stability quantified as BCEA (deg²) is plotted as a function of the amplitude of microsaccade (top), amplitude of slow drifts (middle), and velocity of slow drifts (bottom). The straight line in each panel is the best-fit regression line to the data (log–log axes), with the correlation coefficient given in the upper left corner in each panel.