Professor, Ophthalmology and Visual Sciences
Biography

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

Research

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.
Upper row: pseudocolor images of optic nerve head topography obtained with the Heidelberg Retina Tomograph; lower row: mathematical models of the same images, from which a Glaucoma Probability Score (GPS) can be calculated. See Swindale et al. (2000) IOVS, 1,1730.

Upper row: pseudocolor images of optic nerve head topography obtained with the Heidelberg Retina Tomograph; lower row: mathematical models of the same images, from which a Glaucoma Probability Score (GPS) can be calculated. See Swindale et al. (2000) IOVS, 1,1730.

Recent Publications

Spacek, M, Blanche, T, Swindale N (2009) Python for large-scale electrophysiology. Frontiers in Neuroinformatics , 2 (9), 1 – 10.

Godfrey, KB, Eglen SJ and Swindale, NV (2009) A multi-component model of the developing retinocollicular pathway incorporating axonal and synaptic growth.” PLoS Comput Biol. Dec ;5 (12):e1000600, 1 – 22.

Swindale, N.V. (2008) Feedback Decoding of Spatially Structured Population Activity in Cortical Maps. Neural Computation , 20 , 176-204

Godfrey, KB and Swindale, NV (2007) Retinal wave behaviour through activity dependent refractory periods. PLoS Computational Biology , 3 (11), 1 – 13.

Swindale, NV (2007) A model for the thick, thin and pale stripe organization of primate V2. Network: Computation in Neural Systems , 18 , 327-342.

Blanche, TJ, Spacek MA, Hetke JF, Swindale NV (2005) Polytrodes: High Density Silicon Electrode Arrays for Large Scale Multiunit Recording. J. Neurophysiol., 93, 2987-3000.

Swindale, N.V. (2004) How Different Feature Spaces may be Represented in Cortical Maps. Network, 15, 217-242.

Swindale, N.V., Grinvald A. and Shmuel A. (2003) The Spatial Pattern of Response Magnitude and Selectivity for Orientation and Direction in Cat Visual Cortex. Cerebral Cortex 13, 225-238.

Swindale, N.V., Stjepanovic, G., Chin A. & Mikelberg F.S. (2000) Automated analysis of normal and glaucomatous optic nerve head topography images. Investigative Ophthalmology and Visual Science, 41, 1730-1742.