Benjamin D. Singer, PhD
Director of Scientific Computing
Princeton Neuroscience Institute (see CSBMB, Neuroscience)
Green Hall
Princeton University
(609)258-8632
I work on neuroimaging analysis methods such as function-based
inter-subject alignment of cortical anatomy, surface-based analysis and
visualization, and multiple voxel pattern analysis. In addition to
implementing novel methods, I work to speed up and streamline
neuroimaging analysis algorithms via low-level optimizations and
parallelization. The latter is achieved with the help of a 64-node
computer cluster I helped acquire, set up and maintain.
My neurotree
node.
Selected work:
Neuroimaging
3D funcnorm demo [13MB]
- Conroy, B.R., Singer, B.D., Ramadge, P.J. & Haxby, J.V. (2008).
Inter-subject functional connectivity alignment. Annual Meeting of
the Organization of Human Brain Mapping, Melbourne,
Australia. poster pdf
- Sabuncu, M.R., Singer, B.D., Conroy, B.R., Ramadge, P.J. & Haxby, J.V. (2008, in preparation). Function-based inter-subject alignment of cortical anatomy
- Sabuncu, M.R., Singer, B.D., Bryan, R.E., Ramadge, P.J. & Haxby, J.V. (2006). Function-based inter-subject alignment of cortical anatomy. Annual Meeting of the Organization of Human Brain Mapping, Florence, Italy. poster pdf
- Detre, G., Polyn, S.M., Moore, C.D., Natu, V.S., Singer, B.D., Cohen, J.D., Haxby, J.V. & Norman, K.A. (2006). The Multi-Voxel Pattern Analysis (MVPA) toolbox. Annual Meeting of the Organization of Human Brain Mapping, Florence, Italy. poster pdf
- Polyn, S., Detre, G., Takerkart, S., Natu, V., Benharrosh, M., Singer, B., Cohen, J., Haxby, J. & Norman, K., (2005). A Matlab-based toolbox to facilitate multi-voxel pattern classification of fMRI data. Annual Meeting of the Organization of Human Brain Mapping, Toronto, Canada. poster pdf
Vision Science
I also do work in vision science, now mostly as a consultant. I came to the CSBMB from the Center for Visual Science at the University of Rochester where I did work in electrophysiology and retinal imaging as a postdoc turned staff member, following graduate work in color vision at UCI Cognitive Science and undergraduate work at Cornell Psychology.
Adaptive optics for retinal imaging and supernormal vision:
- Singer, B. (2006). Adaptive optics software for vision research. In Porter, J., Awwal, A., Lin, J., Queener, H. & Thorn, K. (Eds). Adaptive Optics for Vision Science: Principles, Practices, Design, and Applications. John Wiley & Sons, Inc., 139-153. amazon
- Chen, L., Kruger, P., Hofer, H., Singer, B. & Williams, D.R. (2006). Accommodation with higher-order monochromatic aberrations corrected with adaptive optics. J. Opt. Soc. Am. A, 23, 1-8. pdf
- Chen, L., Singer, B., Guirao, A., Porter, J. & Williams, D.R. (2005). Image metrics for predicting subjective image quality. Optometry and Vision Science, 82, 358-369. pdf
- Hofer, H., Singer, B. & Williams, D.R. (2005). Different sensations from cones with the same photopigment. Journal of Vision, 444-454. pdf
- Artal, P., Chen, L., Fernandez, E.J., Singer, B., Manzanera, S. & Williams, D.R. (2004). Neural compensation for the eye's optical aberrations. Journal of Vision, 281-287. pdf
- Doble, N., Yoon, G.Y., Chen, L., Bierden, P., Singer, B., Olivier, S., & Williams, D.R. (2002). Use of a microelectromechanical mirror for adaptive optics in the human eye. Optics Letters, 27, 1537-1539. pdf
- Hofer, H., Chen, L., Yoon, G.Y.,Singer, B., Yamauchi, Y. & Williams, D.R. (2001). Improvement in retinal image quality with dynamic correction of the eye's aberrations. Optics Express, 8, 631-643. pdf
- Hofer, H., Artal, P., Singer, B., Aragon, J.L. & Williams, D.R. (2001). Dynamics of the eye's wave aberration, J. Opt. Soc. Am. A. 18, 497-506. pdf
Human color vision:
- D'Zmura, M. & Singer, B. (1999). Contrast gain control. In Sharpe, L.T. & Gegenfurtner, K.R. (Eds.) Color Vision: From Genes to Perception. Cambridge: Cambridge University Press, 369-385. amazon
- D'Zmura, M. & Singer, B. (1996). The spatial pooling of contrast in contrast gain control. Journal of the Optical Society of America A, 13, 2135-2140. pdf
- D'Zmura, M., Iverson, G. & Singer, B. (1995). Probabilistic color constancy. In Luce, R.D., D'Zmura, M., Hoffman, D.D., Iverson, G. and Romney, K. (Eds.), Geometric Representations of Perceptual Phenomena. Mahwah, NJ: Lawrence Erlbaum Associates, 187-202. amazon
- Singer, B. & D'Zmura, M. (1995). Contrast gain control. A bilinear model for chromatic selectivity. Journal of the Optical Society of America A, 12, 667-685. pdf
- Singer, B. & D'Zmura, M. (1994). Color contrast induction. Vision Research, 34, 3111-3126. pdf
Scientific Computing
A theme throughout my life has been fooling with computers and programming. My main contribution to the above
work was (and still is) implementing the algorithms underlying research questions in software
(algorithm development, stimulus presentation, device control/communication, and data analysis) running on the Macintosh operating
system whenever possible. It's fun!
Software:
- An archive of old (mostly pre-Mac OS X) Mac software I made is here and I plan to make some current software available soon.