Spatial compression: Dissociable effects at the time of saccades and blinks

Abstract

Various studies have identified systematic errors, such as spatial compression, when observers report the locations of objects displayed around the time of saccades. Localization errors also occur when holding spatial representations in visual working memory. Such errors, however, have not been examined in the context of eye blinks. In this study, we examined the effects of blinks and saccades when observers reproduced the locations of a set of briefly presented, randomly placed discs. Performance was compared with a fixation-only condition in which observers simply held these representations in working memory for the same duration; this allowed us to elucidate the relationship between the perceptual phenomena related to blinks, saccades, and visual working memory. Our results indicate that the same amount of spatial compression is experienced prior to a blink as is experienced in the control fixation-only condition, suggesting that blinks do not increase compression above that occurring from holding a spatial representation in visual memory. Saccades, however, tend to increase these compression effects and produce translational shifts both toward and away from saccade targets (depending on the time of the saccade onset in relation to the stimulus offset). A higher numerosity recall capacity was also observed when stimuli were presented prior to a blink in comparison with the other conditions. These findings reflect key differences underlying blinks and saccades in terms of spatial compression and translational shifts. Such results suggest that separate mechanisms maintain perceptual stability across these visual events.

Fixation related shifts of perceptual localization counter to saccade direction

“…The mislocalization toward the saccade target location at saccade onset is consistent with the typical pattern of perisaccadic compression Ross et al, 1997;Lappe et al, 2000;Kaiser & Lappe, 2002;Ostendorf et al, 2007). The preceding mislocalization toward the fixation location is consis- tent with localization errors toward the initial fixation point described by Haladjian et al (2015) for double overlap saccades. Since this mislocalization occurred for single overlap saccades, it is not reliant on the presence of a return saccade.…”

“…This mislocalization begins about 150 ms before the saccade and peaks between 100 and 50 ms before saccade onset. Haladjian et al (2015) first reported evidence for compression toward fixation in a study involving a sequence of first outward and then return saccades. In that study, the fixation marker was also the target of the return saccade so that the compression might have been driven by the preplanning of the return saccade.…”

“…While saccadic and masking-induced mislocalization has generally been investigated using a motor end plan or attentional capture target that is away from the current fixation point, Haladjian, Wufong, and Watson (2015) found that when participants are asked to make two saccades, the second of which returns to the original fixation location, localization errors are toward the initial fixation point when the target stimulus is presented 50 ms ahead of the first saccade and then turn toward the end point of the first saccade when the stimulus is presented within 20 ms before the onset of or during the first eye movement. The early mislocalization in the direction of the current fixation location/ final saccade target for stimuli presented ahead of the onset of the first saccade presents an opportunity to investigate whether this mislocalization is due to allocation of attention to the final landing location of the two-saccade sequence or might rather be due to a fixation maintenance-related modulation of attention at the fovea in the context of an impending eye movement.…”

Simulation of visual acuity by personalizable neuro-physiological model of the human eye

“…This takes us to the last step of image processing: the calculation of a noisy image, that is to be analyzed by the cortical recognition process. As with all biological organs, the visual system also has some temporal uncertainty 16,17 , which is usually modeled at one instant as additive noise:…”

“…The “optically filtered” retinal image can be reconstructed from the monochromatic aberrations of the human eye 11–14 , which is measurable using Shack-Hartmann wavefront sensors 15 . As a next step, neural transfer simulates the post-retinal neural image, with additional neural noise being taken into account to determine the noisy image which is finally recognized by the visual cortex 16,17 . The recognition process is usually represented as a template-matching algorithm, which is known to be one of the simplest and oldest models of pattern vision 18–20 .…”