Peripheral Facial Features Guiding Eye Movements and Reducing Fixational Variability

Face processing is a fast and efficient process due to its evolutionary and social importance. A majority of people direct their first eye movement to a featureless point just below the eyes that maximizes accuracy in recognizing a person's identity and gender. Yet, the exact properties or features of the face that guide the first eye movements and reduce fixational variability are unknown. Here, we manipulated the presence of the facial features and the spatial configuration of features to investigate their effect on the location and variability of first and second fixations to peripherally presented faces. Results showed that observers can utilize the face outline, individual facial features, and feature spatial configuration to guide the first eye movements to their preferred point of fixation. The eyes have a preferential role in guiding the first eye movements and reducing fixation variability. Eliminating the eyes or altering their position had the greatest influence on the location and variability of fixations and resulted in the largest detriment to face identification performance. The other internal features (nose and mouth) also contribute to reducing fixation variability. A subsequent experiment measuring detection of single features showed that the eyes have the highest detectability (relative to other features) in the visual periphery providing a strong sensory signal to guide the oculomotor system. Together, the results suggest a flexible multiple-cue approach that might be a robust solution to cope with how the varying eccentricities in the real world influence the ability to resolve individual feature properties and the preferential role of the eyes.

Quantifying Eye Stability During a Fixation Task: A Review of Definitions and Methods

Several definitions, measurements, and implicit meanings of ‘fixation stability’ have been used in clinical vision research, leading to some confusion. One definition concerns eye movements observed within fixations (i.e., within periods separated by saccades) when observing a point target: drift, microsaccades and physiological tremor all lead to some degree of within-fixation instability. A second definition relates to eye position during multiple fixations (and saccades) when patients fixate a point target. Increased between-fixation variability, combined with within-fixation instability, is known to be associated with poorer visual function in people with retinal disease such as age-related macular degeneration. In this review article, methods of eye stability measurement and quantification are summarised. Two common measures are described in detail: the bivariate contour ellipse area (BCEA) and the within-isolines area. The first measure assumes normality of the underlying positions distribution whereas the second does not. Each of these measures can be applied to two fundamentally different kinds of eye position data collected during a period of target observation. In the first case, mean positions of eye fixations are used to obtain an estimate of between-fixation variability. In the second case, often used in clinical vision research, eye position samples recorded by the eyetracker are used to obtain an estimate that confounds within- and between-fixation variability.We show that these two methods can produce significantly different values of eye stability, especially when reported as BCEA values. Statistical techniques for describing eye stability when the distribution of eye positions is multimodal and not normally distributed are also reviewed.