Vision, Ocular Clinical Trial
Official title:
Visual Attention and Eye Movements
The purpose of this study is to provide information about how the brain processes sensory inputs using visual stimuli throughout various psychophysical experiments.
This laboratory studies visual perception with a focus on the interaction between eye movements and attention. It is well established that attending to a stimulus can profoundly alter perception. For example, attending to a speaker at a crowded party can almost completely filter background both in terms of auditory noise and visual distractions. Although laboratory studies have traditionally investigated the effects of attentional changes in the absence of eye movements, under natural conditions, visual attention is often accompanied by orienting movements to direct our head and eyes towards the relevant objects of interest. Recent work has suggested that these orienting movements affect perception in a manner similar to covert attention. The proposed studies will investigate how eye movements contribute to perception and attention. The research covered by this protocol combines traditional "button-press" psychophysics with non-invasive eye-tracking to investigate the interaction between eye movements and perception. Subjects will perform simple perceptual tasks, such as judging the orientation or direction of a visual stimulus, while their eye position is monitored with a video eye-tracker. This approach (combining psychophysics and eye-tracking) is flexible, low risk, and fast when compared with neurophysiological studies. However, by focusing on low-level perceptual tasks, the results will be interpretable in the context of larger studies of neurophysiological responses in the visual system. The investigators hope that this basic research will ultimately have both applied and clinical significance. For example, understanding how perception is influenced by attention and eye-movements in neurotypical populations may provide non-invasive and naturalistic ways to identify and diagnose psychiatric disorders. Additionally, understanding how eye-movements interact with sensory encoding has the potential to improve machine learning algorithms for vision and navigation (These are not a part of the current study, but a potential future impact). ;
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