Neural and perceptual mechanisms of spatial stability across eye movements
- Institution
- OHIO STATE UNIVERSITY, OH
- Principal investigator
- Julie D Golomb
- Funding
- $402K
- Duration
- 2015–2026
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Abstract
Project Summary The overarching goal of this research is to better understand the human visual system, and how objects and their locations are perceived and represented in the brain. The proposal investigates a fundamental challenge for our visual systems: Visual information is coded relative to the eyes, but the eyes are constantly moving. How, then, do we achieve spatial stability? The world does not appear to “jump” with each eye movement, but this seamless percept belies a complicated computational process. Moreover, spatial localization is not an isolated process; it interacts with attention, object recognition, depth perception, memory, cognitive control, and more. In order to understand visual stability, we need to account for both how spatial information is represented (or “remapped”) across eye movements, and how spatial information is integrated with these other processes. Research under the prior award made strong strides in two key directions along these lines: understanding how 2D spatial information is integrated with depth information to consider spatial stability in 3D, and revealing how spatial remapping impacts feature/object perception. In the next stage of this research program, we build on this momentum to investigate spatial and object stability across eye movements – and their integration more broadly – with a special focus on the roles of dynamic context and top-down attentional control. In Aim 1 we employ an fMRI-EEG fusion approach to investigate 3D stability and object integration in visual cortex and the hippocampus, hypothesizing that dynamic, active saccade context may promote enhanced visual integration and stability. Next, we further develop the PI’s Dual-Spotlight Theory of remapping (Golomb, 2019) and explore the role of top-down attentional control in remapping and perceptual stability (Aim 2). Finally, we develop a new model-based neuroimaging analysis technique to enable future progress on persistently less tractable aspects of this question (Aim 3). The proposed experiments strive to continue to transform our understanding of visual stability, particularly how it interfaces with other perceptual and cognitive processes that are central to our understanding of human perception and brain function. The research proposed here will have an immediate impact on our understanding of typical visual functioning in healthy human populations. These advances could also have a longer-term impact on a variety of clinical applications, informing our knowledge and assessment of visual disorders resulting from eye disease, injury, brain damage, and development/aging.
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