Nicholas V. Swindale

Associations
Graduate Program in Neuroscience, Mathematical Biology Program, Institute of Applied Mathematics

Research Description

I am interested in vision, and the development and organization of the primary visual cortex. This includes studying how the genes and environment interact in early post-natal development, how cellular mechanisms contribute to perceptual processing, and how disorders such as amblyopia and glaucoma may affect visual function. I use computer models to simulate developmental mechanisms, cats as experimental models for visual processing, and humans as subjects for psychophysical research. Present and past research projects include the following:

• Application of neural net models to the formation of computational maps of ocular dominance and orientation columns in the visual cortex
• Analysis of columnar organization in the cat visual cortex using optical recording of stimulus evoked neural activity
• Multi-electrode recording methods for the comparison of receptive field properties in simultaneously recorded clusters of neurons
• Quantitative analysis and modeling of spatial summation in simple and complex cell receptive fields in cat visual cortex
• Physiological and psychophysical studies of the mechanisms of vernier hyperacuity
• The development of clinically diagnostic psychophysical tests of visual function in glaucoma
• Early detection of glaucoma using mathematical modelling of optic nerve head shape and neural network methods for classifying images as normal or glaucomatous.