This project focuses on coordination of eye and hand movements in carrying out simple tasks. Using gaze-contingent displays, we simulate the kinds of retinal damage that are associated with glaucoma, retinitis pigmentosa and age-related macular degeneration, evaluate how damage affects eye-hand coordination and measure how quickly subjects learn to compensate. In three series of experiments, we track eye movements and hand movements and their interaction. Bayesian decision theory provides a very natural way to model and better understand how humans plan movements. The first goal of this research is to extend existing Bayesian decision-theoretic models of movement planning to include eye and hand movements and their interactions. The result will be a predictive model of human planning of movement. A second goal is to better understand how the visuo-motor system learns to compensate for damage due to retinal disease or injury and how to speed such compensation.

Public Health Relevance

We are studying how humans plan movement in realistic tasks that require coordination of hand and eye. Exploring the limits of movement planning in normal, healthy humans gives us insight into how well or poorly they will cope with disease, aging or injury.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY019889-03
Application #
8423378
Study Section
Cognition and Perception Study Section (CP)
Program Officer
Steinmetz, Michael A
Project Start
2011-02-01
Project End
2014-01-31
Budget Start
2013-02-01
Budget End
2014-01-31
Support Year
3
Fiscal Year
2013
Total Cost
$286,993
Indirect Cost
$96,993
Name
New York University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
041968306
City
New York
State
NY
Country
United States
Zip Code
10012
Zhang, Hang; Daw, Nathaniel D; Maloney, Laurence T (2013) Testing whether humans have an accurate model of their own motor uncertainty in a speeded reaching task. PLoS Comput Biol 9:e1003080
Morvan, Camille; Maloney, Laurence T (2012) Human visual search does not maximize the post-saccadic probability of identifying targets. PLoS Comput Biol 8:e1002342
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