Norma Graham, PhD
Research Interest
Mathematical Models of Visual Perception
Our research attempts to uncover and describe the hidden stages of visual processing, the many stages now known to intervene between the light entering the eye and the human's conscious perception. The neural substrate of these stages is known to be in the back part of the brain, but little is known about how they work. In our work we derive predictions from theories (embodied in mathematical models) about how these hidden stages might work. We compare these predictions to data from behavioral studies (some done by us) and neurophysiological studies (usually done by others) of visual perception. Lately we have been particularly interested in the results of adaptation to visual contrast. We discovered a previously-unknown form of contrast adaptation - a rectifying, shifting contrast comparison level. We have begun studying its properties and its interaction with an older-known process, a contrast-gain control that produces Weber-law-like behavior.
Ratliff, F., Knight, B. W. and Graham, N. (1969) On tuning and amplification by lateral inhibition. Proceedings of National Academy of Sciences, 62, 733-740.
Graham, N. and Nachmias, J. (1971) Detection of grating patterns containing two spatial frequencies: A test of single-channel and multiple-channels models. Vision Research, 11, 251-259.
Graham, N. (1979) Does the brain perform a Fourier analysis of the visual scene? Trends in Neurosciences, August, 1979, pp 207-208.
Davis, E T., Kramer, P., and Graham, N. (1983) Uncertainty about spatial frequency, spatial position, or contrast of visual patterns. Perception and Psychophysics, 33, 20-28.
Graham, N., Kramer, P. and Yager, D. (1987) Signal-detection models for multidimensional stimuli: Probability distributions and combination rules. J. Mathematical Psychology, 31, 366-409.
Graham, N. (1989) Visual Pattern Analyzers. New York: Oxford University Press. 646 pages. Paperback edition (2001).
Graham, N. (1992) Breaking the visual stimulus into parts. Current Directions in Psychological Science, 1, 55-61.
Hood, D.C. and Graham, N.G. (1998) Threshold fluctuations on temporally modulated backgrounds: A possible physiological explanation based upon a recent computational model. Visual Neuroscience, 15, 957-967.
Graham, N. and Sutter, A. (2000) Normalization: Contrast-gain control in simple (Fourier) and complex (non-Fourier) pathways of pattern vision. Vision Research, 40, 2737-2761.
Graham, N. and Wolfson, S. (2001) A note about preferred orientations at the first and second stages of complex (second-order) texture channels. Journal of the Optical Society of America A, 18, 2273-2281.
Graham, N. and Wolfson, S. (2007). Exploring contrast-controlled adaptation processes in human vision (with help from Buffy the Vampire Slayer). In Computational Vision in Neural and Machine System, eds Michael Jenkins & Laurence Harris, Cambridge University Press. pp. 9-47.
Wolfson, S and Graham, N (2009) Two contrast adaptation processes: contrast normalization and shifting, rectifying, contrast comparison. Journal of Vision. 9(4): 30, 1-23.
Graham, N. (2011). Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): Useful additions of the last 25 years. Vision Research. doi:10.1016/j.visres.2011.02.007
Graham,N. and Wolfson, S (2018). Is the straddle effect in contrast perception limited to 2nd-order spatial vision? Journal of Vision.18(5):15, 1-43, https://doi.org/10.1167/18.5.15
Wolfson, S. and Graham, N. (2019). Spatial characteristics of a contrast-comparison process. In Pioneer Visual Neuroscience: A Festschrift for Naomi Weisstein. Ed. James Brown. Routledge/Taylor&Francis, London and New York, pp 104-117.