Eye movements: The past 25 years

Visual search, a vital task for humans and animals, has also become a common and important tool for studying many topics central to active vision and cognition ranging from spatial vision, attention, and oculomotor control to memory, decision making, and rewards. While visual search often seems effortless to humans, trying to recreate human visual search abilities in machines has represented an incredible challenge for computer scientists and engineers. What are the brain computations that ensure successful search? This review article draws on efforts from various subfields and discusses the mechanisms and strategies the brain uses to optimize visual search: the psychophysical evidence, their neural correlates, and if unknown, possible loci of the neural computations. Mechanisms and strategies include use of knowledge about the target, distractor, background statistical properties, location probabilities, contextual cues, scene context, rewards, target prevalence, and also the role of saliency, center-surround organization of search templates, and eye movement plans. I provide overviews of classic and contemporary theories of covert attention and eye movements during search explaining their differences and similarities. To allow the reader to anchor some of the laboratory findings to real-world tasks, the article includes interviews with three expert searchers: a radiologist, a fisherman, and a satellite image analyst.

Visual search: a retrospective.

Eye movements are an integral and essential part of our human foveated vision system. Here, we review recent work on voluntary eye movements, with an emphasis on the last decade. More selectively, we address two of the most important questions about saccadic and smooth pursuit eye movements in natural vision. First, why do we saccade to where we do? We argue that, like for many other aspects of vision, several different circuits related to salience, object recognition, actions, and value ultimately interact to determine gaze behavior. Second, how are pursuit eye movements and perceptual experience of visual motion related? We show that motion perception and pursuit have a lot in common, but they also have separate noise sources that can lead to dissociations between them. We emphasize the point that pursuit actively modulates visual perception and that it can provide valuable information for motion perception.

Eye movements and perception: a selective review.

A growing number of studies in vision research employ analyses of how perturbations in visual stimuli influence behavior on single trials. Recently, we have developed a method along such lines to assess the time course over which object velocity information is extracted on a trial-by-trial basis in order to produce an accurate intercepting saccade to a moving target. Here, we present a simplified version of this methodology, and use it to investigate how changes in stimulus contrast affect the temporal velocity integration window used when generating saccades to moving targets. Observers generated saccades to one of two moving targets which were presented at high (80%) or low (7.5%) contrast. In 50% of trials, target velocity stepped up or down after a variable interval after the saccadic go signal. The extent to which the saccade endpoint can be accounted for as a weighted combination of the pre- or post-step velocities allows for identification of the temporal velocity integration window. Our results show that the temporal integration window takes longer to peak in the low when compared to high contrast condition. By enabling the assessment of how information such as changes in velocity can be used in the programming of a saccadic eye movement on single trials, this study describes and tests a novel methodology with which to look at the internal processing mechanisms that transform sensory visual inputs into oculomotor outputs.

/pdf/testing-a-simplified-method-for-measuring-velocity-2w8cxpaep5.pdf

Testing a simplified method for measuring velocity integration in saccades using a manipulation of target contrast

The human visual system is foveated, that is, outside the central visual ﬁeld resolution and acuity drop rapidly.Nonetheless much of a visual scene is perceived after only a few saccadic eye movements, suggesting an effectivestrategy for selecting saccade targets. It has been known for some time that local image structure at saccade targetsinﬂuences the selection process. However, the question of what the most relevant visual features are is still under debate.Here we show that center-surround patterns emerge as the optimal solution for predicting saccade targets from their localimage structure. The resulting model, a one-layer feed-forward network, is surprisingly simple compared to previouslysuggested models which assume much more complex computations such as multi-scale processing and multiple featurechannels. Nevertheless, our model is equally predictive. Furthermore, our ﬁndings are consistent with neurophysiologicalhardware in the superior colliculus. Bottom-up visual saliency may thus not be computed cortically as has been thoughtpreviously.Keywords: visual saliency, eye movements, receptive ﬁeld analysis, classiﬁcation images, kernel methods,support vector machines, natural scenesCitation: Kienzle, W., Franz, M. O., Scholkopf, B., & Wichmann, F. A. (2009). Center-surround patterns emerge as optimalpredictors for human saccade targets. Journal of Vision, 9(5):7, 1–15, http://journalofvision.org/9/5/7/, doi:10.1167/9.5.7.

Center-surround patterns emerge as optimal predictors for human saccade targets.

When your eyes see more than you do

Coding of Information in the Phase of Local Field Potentials within Human Medial Temporal Lobe

http://live.ece.utexas.edu/publications/2009/at_visres_jan09.pdf

Eye movements selective for spatial frequency and orientation during active visual search.

Smooth pursuit eye movements allow the approximate stabilization of a moving visual target on the retina. To study the dynamics of smooth pursuit, we measured eye velocity during the visual tracking of a Gabor target moving at a constant velocity plus a noisy perturbation term. The optimal linear filter linking fluctuations in target velocity to evoked fluctuations in eye velocity was computed. These filters predicted eye velocity to novel stimuli in the 0- to 15-Hz band with good accuracy, showing that pursuit maintenance is approximately linear under these conditions. The shape of the filters were indicative of fast dynamics, with pure delays of merely ∼67 ms, times-to-peak of ∼115 ms, and effective integration times of ∼45 ms. The gain of the system, reflected in the amplitude of the filters, was inversely proportional to the size of the velocity fluctuations and independent of the target mean speed. A modest slow-down of the dynamics was observed as the contrast of the target decreased. Finally, the temporal filters recovered during fixation and pursuit were similar in shape, supporting the notion that they might share a common underlying circuitry. These findings show that the visual tracking of moving objects by the human eye includes a reflexive-like pathway with high contrast sensitivity and fast dynamics.

Dynamics of smooth pursuit maintenance.

We propose a novel variant of the classification image paradigm that allows us to rapidly reveal strategies used by observers in visual search tasks. We make use of eye tracking, 1/f noise, and a grid-like stimulus ensemble and also introduce a new classification taxonomy that distinguishes between foveal and peripheral processes. We tested our method for 3 human observers and two simple shapes used as search targets. The classification images obtained show the efficacy of the proposed method by revealing the features used by the observers in as few as 200 trials. Using two control experiments, we evaluated the use of naturalistic 1/f noise with classification images, in comparison with the more commonly used white noise, and compared the performance of our technique with that of an earlier approach without a stimulus grid.

/pdf/an-efficient-technique-for-revealing-visual-search-258pxou16l.pdf

Abtine Tavassoli

Papers

When your eyes see more than you do

Coding of Information in the Phase of Local Field Potentials within Human Medial Temporal Lobe

Eye movements selective for spatial frequency and orientation during active visual search.

Dynamics of smooth pursuit maintenance.

An efficient technique for revealing visual search strategies with classification images.