The Brainard Lab studies human vision, both experimentally and through computational modeling of visual processing. Our primary concern is with how the visual system estimates object properties from the information available in the light signal incident at the eye. To study this general problem, we conduct psychophysical experiments to investigate questions such as how object color appearance is related to object surface properties under a wide range of illumination conditions and how color is used to identify objects, and formulate computational models of the results. In addition, we are interested in developing machine visual systems that can mimic human performance and in understanding the neural mechanisms of vision.
Representative Recent Publications
(See Publications for more, or download Brainard's CV in PDF Format. Or visit Brainard's Google Scholar Page).
Ruff, D. Brainard, D. H., Cohen, M. R. (2018). Neuronal population mechanisms of lightness perception. In press, Journal of Neurophysiology. (Preprint available at https://doi.org/10.1101/294280.)
Tuten, W. S., Cooper, R. F., Tiruveedhula, P., Dubra, A., Roorda, A., Cottaris, N. P., Brainard, D. H., Morgan, J. I. W. (2018). Spatial summation in the human fovea: the effect of optical aberrations and fixational eye movements. Journal of Vision, 18(8):6, doi: 10.1167/18.8.6, https://jov.arvojournals.org/article.aspx?articleid=2697364.
Spitschan, M., Bock, A. S., Ryan, J., Frazzetta, G., Brainard, D. H., Aguirre, G. K. (2017). The human visual cortex response to melanopsin-directed stimulation is accompanied by a distinct perceptual experience. PNAS, 114(46), 12291–12296, doi: 10.1073/pnas.1711522114. Download PDF. Press release. [There is a link in the paper to a repository with the raw data. That link turns out to have a finite lifetime. The permalink to the data respository is: https://doi.org/10.6084/m9.figshare.4906727.v12.]
Cooper, R. F., Tuten, W. S., Dubra, A., Brainard, D. H., Morgan, J. I. W. (2017). Non-invasive assessment of human cone photoreceptor function. Biomedical Optics Express, 8(11), 5098-5112, doi: 10.1364/BOE.8.005098. https://www.osapublishing.org/boe/abstract.cfm?uri=boe-8-11-5098. Erratum: Biomed. Opt. Express, 2018, 9, 1842, https://doi.org/10.1364/BOE.9.001842.
Lindsey, D. T., Brown, A. M., Brainard D. H. & Apicella, C. A. (2015). Hunter-gatherer color naming provides new insight into the evolution of color terms. Current Biology, 25, 2441-2446, doi: 10.1016/j.cub.2015.08.006. Download PDF. Press coverage: Science World Report, Medical Daily, Phys.org.
Preprints (listed until work is published)
5. Cottaris, N. P., Jiang, H., Ding, X., Wandell, B. A., Brainard, D. H. (2018). A computational observer model of spatial contrast sensitivity: Effects of wavefront-based optics, cone mosaic structure, and inference engine. bioRxiv 378323, https://doi.org/10.1101/378323.
4. McAdams, H., Igdalova, A., Spitschan, M., Brainard, D. H., Aguirre, G. K. (2018). Pulses of melanopsin-directed contrast produce highly reliable pupil responses that are insensitive to a change in background radiance. bioRxiv 365718, https://doi.org/10.1101/365718.
3. Singh, V., Cottaris, N. P., Heasly, B. S., Brainard, D. H. Burge, J. (2018). Computational luminance constancy from naturalistic images. bioRxiv 358671, https://doi.org/10.1101/358671.
2. Ding, X., Radonjić, A., Cottaris, N. P., Jiang, H., Wandell, B. A., Brainard D. H. (2018). Computational-observer analysis of illumination discrimination. bioRxiv 302315, https://doi.org/10.1101/302315.
1. Golden, J. R., Erickson-Davis, C., Parthasarathy, N., Rieke, F., Brainard, D. H., Wandell, B. A., Chichilnisky, E. J. (2018). Simulation of visual perception and learning with a retinal prosthesis. bioRxiv 206409, https://doi.org/10.1101/206409.
Here is a link to our list of preregistered experiments.