Direct control of Fixation Duration in Scene Viewing: The Saccade-Contingent Change Paradigm

2011 ◽  
Author(s):  
Mackenzie G. Glaholt ◽  
Keith Rayner ◽  
Eyal M. Reingold
2010 ◽  
Vol 3 (3) ◽  
Author(s):  
Hsueh-Cheng Wang ◽  
Alex D. Hwang ◽  
Marc Pomplun

During text reading, the durations of eye fixations decrease with greater frequency and predictability of the currently fixated word (Rayner, 1998; 2009). However, it has not been tested whether those results also apply to scene viewing. We computed object frequency and predictability from both linguistic and visual scene analysis (LabelMe, Russell et al., 2008), and Latent Semantic Analysis (Landauer et al., 1998) was applied to estimate predictability. In a scene-viewing experiment, we found that, for small objects, linguistics-based frequency, but not scene-based frequency, had effects on first fixation duration, gaze duration, and total time. Both linguistic and scene-based predictability affected total time. Similar to reading, fixation duration decreased with higher frequency and predictability. For large objects, we found the direction of effects to be the inverse of those found in reading studies. These results suggest that the recognition of small objects in scene viewing shares some characteristics with the recognition of words in reading.


Author(s):  
R. Calen Walshe ◽  
Antje Nuthmann

AbstractResearch on eye-movement control during natural scene viewing has investigated the degree to which the duration of individual fixations can be immediately adjusted to ongoing visual-cognitive processing demands. Results from several studies using the fixation-contingent scene quality paradigm suggest that the timing of fixations adapts to stimulus changes that occur on a fixation-to-fixation basis. Analysis of fixation-duration distributions has revealed that saccade-contingent degradations and enhancements of the scene stimulus have two qualitatively distinct types of influence. The surprise effect begins early in a fixation and is tied to surprising visual events such as unexpected stimulus changes. The encoding effect is tied to difficulties in visual-cognitive processing and occurs relatively late within a fixation. Here, we formalize an existing descriptive account of these two effects (referred to as the dual-process account) by using stochastic simulations. In the computational model, surprise and encoding related influences are implemented as time-dependent changes in the rate at which saccade timing and programming are completed during critical fixations. The model was tested on data from two experiments in which the luminance of the scene image was either decreased or increased during selected critical fixations (Walshe & Nuthmann, Vision Research, 100, 38–46 2014). A counterfactual method was used to remove model components and to identify their specific influence on the fixation_duration distributions. The results suggest that the computational dual-process model provides a good account for the data from the luminance-change studies. We describe how the simulations can be generalized to explain a diverse set of experimental results.


2004 ◽  
Author(s):  
James R. Brockmole ◽  
Michael L. Mack ◽  
Monica S. Castelhano ◽  
Aude Oliva ◽  
John M. Henderson

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 72-72
Author(s):  
I T C Hooge ◽  
C J Erkelens

To investigate the interaction between saccade preparation and foveal analysis on multi-fixation search, we designed an experiment in which the result of the foveal analysis is relevant for programming the direction of the next saccade. We examined whether fixation duration is adjusted to the duration of the analysis process or not. Subjects were asked to find a circle (diameter 2.1 deg) among 35 circles (gap size 0.3 deg, diameter 2.1 deg) that were placed on an invisible hexagonal grid (35 deg × 35 deg). Eye movements of the right eye were measured. The gaps of the circles indicated the direction in which the circle could be found. Subjects were instructed to make eye movements in the direction that was indicated by the gap of the fixated circle. The proportion of eye movements made in the indicated directions ranged from 0.54 to 0.72 (0.25 is chance level). Thus direction information is indeed, but improperly, used for the programming of eye movements. Durations of fixations preceding eye movements made in non-indicated directions were smaller than durations of fixations preceding eye movements made in indicated directions. From these results we conclude that saccade preparation only uses the result of the analysis if it is available in time and that there is no direct control of fixation duration by a mechanism that monitors the analysis process.


2015 ◽  
Vol 27 (6) ◽  
pp. 1137-1145 ◽  
Author(s):  
John M. Henderson ◽  
Wonil Choi

During active scene perception, our eyes move from one location to another via saccadic eye movements, with the eyes fixating objects and scene elements for varying amounts of time. Much of the variability in fixation duration is accounted for by attentional, perceptual, and cognitive processes associated with scene analysis and comprehension. For this reason, current theories of active scene viewing attempt to account for the influence of attention and cognition on fixation duration. Yet almost nothing is known about the neurocognitive systems associated with variation in fixation duration during scene viewing. We addressed this topic using fixation-related fMRI, which involves coregistering high-resolution eye tracking and magnetic resonance scanning to conduct event-related fMRI analysis based on characteristics of eye movements. We observed that activation in visual and prefrontal executive control areas was positively correlated with fixation duration, whereas activation in ventral areas associated with scene encoding and medial superior frontal and paracentral regions associated with changing action plans was negatively correlated with fixation duration. The results suggest that fixation duration in scene viewing is controlled by cognitive processes associated with real-time scene analysis interacting with motor planning, consistent with current computational models of active vision for scene perception.


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