Operation of eye-movement control mechanisms during the perception of naturalistic scenes.
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Date
28/06/2016Author
Walshe, Ross Calen
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Abstract
Understanding of visual scenes takes place within very brief episodes
known as fixations. To explore the extent of the scene, the eye shifts
between fixation locations at intervals of roughly 300 ms. Currently,
it is a matter of open inquiry as to what factors influence the timing
of these movements. This thesis focuses on understanding the
mechanisms that govern the rapid adjustment of fixation and saccade
timings when novel stimulus information is encountered during a fixation.
In part I, I use an experimental technique known as the fixation-contingent
scene quality paradigm to control the quality of incoming
visual scene information. This approach is used to assess how fixation
timing adapts to moment-by-moment changes in the quality level of
the stimulus. I find that quality changes tend to result in an increase
in fixation durations and this occurs whether the quality is increased
or decreased. Using distributional analytic techniques, I argue that
these results reflect the combined influence of a rapid surprise related
process and a slower acting encoding related influence. In part II, I
study how fixation durations are influenced by the underlying saccade
programming mechanisms. An important assumption within
the eye-movement control literature is that there exists a threshold
called the point-of-no-return. Once this point has been reached, a
saccade may no longer be modified or cancelled. I adapt a classic psychophysical
technique known as the double-step procedure to study
the point-of-no-return within scene viewing tasks. I also provide a
measurement of the saccadic dead time, the last point in time that
a saccade may be modified. In Part III, a formal model of fixation
durations in high-level tasks is presented. I build on recent modelling
work and develop a formal account for the early-surprise late-encoding
modulation account of fixation durations in scene viewing
tasks. The model is tested against data observed in Part I of the thesis.
I demonstrate that the model does a very good job of predicting these
distributions with relatively few assumptions. In summary, I use experimental
techniques in combination with computational modelling
to reveal how a composite of low-level (saccade programming) and
high-level (information processing) considerations can, and must, be
taken into consideration when understanding eye-movement control
behaviour in scene viewing tasks.
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