Dr David Tolhurst

Computational and psychophysical investigation of human spatial and chromatic vision

The project is concerned with the ways in which the visual system encodes the spatial, temporal and chromatic information found in the natural visual environment. Our understanding of the coding properties of visual neurones is based primarily on experimental measures of their responses to simplified, “laboratory” stimuli. The project aims to discover how the response properties of visual neurones suits them to the particular tasks of encoding natural rather than “laboratory” visual stimuli. Partly, the project will entail the development of computer models of interacting visual neurones, and the models will be stimulated with photographs of natural scenes. The aim will be to determine how efficiently or faithfully the model output represents natural visual information. The computational work will be grounded in real experimental observations, and the project will include psychophysical experiments on human observers. These will measure how well human observers can extract information from natural scenes (digitised photographs) and will also attempt to determine some of the rules governing the interactions between visual neurones.

In particular, the project will measure how well people can detect small changes in the spatial structure or colour of natural scenes, and it will also examine how much subjective weight observers place on clearly-visible differences. A detailed computer model of visual processing will be developed to determine whether human perceptual performance is explicable in terms of basic neuronal behaviour. The project will entail a variety of psychophysical techniques for measuring thresholds and for evaluating subjective ratings. It will entail development of computer code (probably in Matlab) to model the known behaviour of groups of neurones in visual cortex.

Some recent papers on these themes:

WILLMORE, B. & TOLHURST, D.J. (2001). Characterising the sparseness of neural codes. Network, Computation in Neural Systems, 12, 255-270.

PÁRRAGA, C.A., TROSCIANKO, T. & TOLHURST, D.J. (2002). Spatio-chromatic properties of natural images and human vision. Current Biology, 12, 483-487.

CHIRIMUUTA, M., CLATWORTHY, P.L. & TOLHURST, D.J. (2003). Coding of the contrasts in natural images by visual cortex (V1) neurons: A Bayesian approach. Journal of the Optical Society of America A, 20, 1253-1260

CLATWORTHY, P.L., CHIRIMUUTA, M., LAURITZEN, J.S. & TOLHURST, D.J. (2003). Coding of the contrasts in natural images by populations of neurons in primary visual cortex (V1). Vision Research, 43, 1983-2001.

CAYWOOD, M.S., WILLMORE, B. and TOLHURST, D.J. (2004). Independent Components of Color Natural Scenes Resemble V1 Neurons in their Spatial and Color Tuning. Journal of Neurophysiology, 91, 2859-2873

LOVELL, P.G., TOLHURST, D.J., PÁRRAGA, C.A., BADDELEY, R., LEONARDS, U. TROSCIANKO, J. and TROSCIANKO, T. (2005). On the stability of the color-opponent signals under changes of illuminant in natural scenes. Journal of the Optical Society of America A, 22, 2060-2071.

CHIRIMUUTA, M. and TOLHURST, D.J. (2005). Does a Bayesian model of V1 contrast coding offer a neurophysiological account of human contrast discrimination? Vision Research, 45, 2943-2959.

CHIRIMUUTA, M. and TOLHURST, D.J. (2005). Accuracy of identification of grating contrast by human observers: Bayesian models of V1 contrast processing show correspondence between discrimination and identification performance. Vision Research, 45, 2960-2971.

PÁRRAGA, C.A., TROSCIANKO, T. & TOLHURST, D.J. (2005). The effects of amplitude-spectrum statistics on foveal and peripheral discrimination of changes in natural images, and a multi resolution model. Vision Research, 45, 3145-3168

TOLHURST, D.J., PÁRRAGA, C.A., LOVELL, P.G., RIPAMONTI, C. and TROSCIANKO, T. (2005). A multiresolution color model for visual difference prediction. Proceedings of the 2nd Conference of APGV. ACM International Conference Proceeding Series; 95, 135-138.

LAURITZEN, J.S. & TOLHURST, D.J. (2005). Contrast constancy in natural scenes in shadow or direct light - a proposed role for contrast-normalisation (non-specific suppression) in visual cortex.. Network, Computation in Neural Systems, in press