My primary research focus is visual perception in everyday life. Most of what we know about visual perception is based on carefully designed experiments performed in the laboratory where conditions can be carefully controlled. While this has given us a very thorough understanding of the metrics and mechanics of vision, it tells us little about how we use vision every day.

In order to perceive the world around us, we must move our eyes almost constantly. We typically make ~2 to 4 eye movements every second; over 100,000 every day. These eye movements are necessary because of the design of the human eye. Unlike manmade image sensors such as CCDs or photographic film, the image sensor at the back of the eye (the retina) is highly anisotropic; the resolution varies by orders of magnitude across the field. High acuity is only available in a small area at the center of the retina, so the eyes are moved to 'point to' objects or regions in the scene that require high acuity. Eye movements are also made toward task-relevant targets even when high spatial resolution is not required. These eye movements, made without conscious intervention, can reveal attentional mechanisms and provide a window into cognition; they are the focus or our research.

By examining the eye movements of subjects as they perform complex tasks, we are able to take advantage of this window into cognition, helping us understand how we gather information from the environment, how we store and recover the information, and how we use that information in planning and guiding actions.

Recent work in the Visual Perception Laboratory has focused on using the RIT Wearable Eyetracker to monitor complex, real-life tasks in natural environments. Recent papers describe these experiments (follow the recent publications: link below)

The design of the human eye was necessary to meet the competing evolutionary demands for high visual acuity and a large field of view. There is simply not enough neural real estate available in the brain to support a visual system that has high resolution over the required field of view. Even if we left no room in the cortex for any other senses (not to mention housekeeping functions like breathing or keeping the heart beating), the human cortex could not support the optimal size/resolution sensor. Some animals stay within the design limits by restricting their field of view (e.g., a hawk); others give up high resolution in favor of a larger field of view (e.g., a rabbit). Rather than picking one or the other solution, humans evolved the anisotropic retina with very high spatial resolution in the center of the visual field (the fovea), surrounded by a much lower resolution region (the peripheral retina). In the human retina, the high-resolution fovea encompasses less than 0.1% of the visual field visible at any instant, and the effective resolution falls by an order of magnitude within a few degrees from the fovea. This variable-resolution retina reduces bandwidth sufficiently, but is not an acceptable solution alone. Unless the point of interest at any moment happened to fall in the exact center of the visual field, the stimulus would be relegated to the low-resolution periphery. The 'foveal compromise' was made feasible by the evolution of a complementary mechanism to move the eyes. In order to ensure useful vision, the eyes must be moved rapidly about the scene.

The first job of an eye movement system is to move the eye quickly from the current point of gaze to a new location. Vision is blurred during an eye movement, so the length of time that the eye is moving must be minimized. In order to minimize the time during which no clear image is captured on the fovea, eye movements that move the fovea from one object/point to another are very rapid. These saccadic eye movements are among the fastest movements the body can make; the eyes can rotate at over 500 deg/sec, and subjects make well over one hundred thousand of these saccades daily. These rapid eye movements are accomplished by a set of six muscles attached to the outside of each eye. They are arranged in three pairs of agonist-antagonist pairs; one pair rotates the eye horizontally (left - right), the second rotates the eye vertically (up - down), the third allows 'cyclotorsion,' or rotation about the line of sight.

The second class of eye movements maintains clear vision by stabilizing the retinal image. This stabilization assures that the image of an object or region in the center of the field-of-view is kept over the fovea. Sophisticated mechanisms exist to accomplish this goal in the face of eye, head, body, and object motion. These eye movements are often grouped into four categories:

1. The vestibular-ocular reflex (VOR) rotates the eyes to compensate for head rotation and translation. Rotational and linear acceleration are detected by the semicircular canals and otolith organs in the inner ear. The resultant signals are used to command compensating eye movements.
   
2. Optokinesis stabilizes the retinal image caused by large-field motion. Retinal slip induced by field motion is used to initiate eye movements at the appropriate rate to cancel out image motion.
   
3. Smooth-pursuit eye movements are similar to optokinesis, but allow arbitrarily sized targets to be stabilized instead of large-field motion. A moving target is required for smooth eye movements; the eyes cannot move smoothly across a stationary object.
   
4. Vergence eye movements counter-rotate the eyes to maintain the images of an object at a given depth to be maintained at corresponding locations on the two retinae.

Much of the research on eye movements to date has been focused on understanding the mechanics and dynamics of the oculomotor system. The question of how successive fixations are aligned spatially has also received much attention. Most of this research has been aimed at discovering how the visual system 'knows' where the eyes are situated for each fixation so that the individual images captured with each fixation can be correctly aligned to build the rich internal representation we experience. Evidence is emerging, however, that we may have been asking the wrong question. We are able to use regularities in the environment to maintain a stable representation without resorting to complex alignment mechanisms and large changes in the environment may go undetected. Understanding visual perception requires us to ask a similar, but orthogonal question about the temporal stitching of successive views. This issue has not arisen with experimental tasks in the past because task complexity was purposely restricted.

We are studying eye movements in complex tasks and natural environments so that we can better understand the process, rather than the mechanics, of visual perception