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 model-based neural networks in 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
computer clusters containing hundreds of processors that I help to acquire, set up and maintain.
My neurotree
node.
Selected work:
Neuroimaging Analysis Methods
3D funcnorm demo [13MB]
- Sabuncu MR, Singer BD, Conroy BR, Ramadge PJ, Haxby JV. (2009). Function-based inter-subject alignment of cortical anatomy. Cerebral Cortex Advance Access published May 6, 2009, doi:10.1093/cercor/bhp085. pubmed.
- Arcaro MJ, McMains SA, Singer BD, Kastner S. (2009). Retinotopic organization of human ventral visual cortex. Journal of Neuroscience, 29, 10638-10652; doi:10.1523/JNEUROSCI.2807-09.2009. jneurosci.org. PubMed ID (not yet online): 19710316.
- Conroy BR, Singer BD, Ramadge PJ, Haxby JV. (2008). Inter-subject functional connectivity alignment. Annual Meeting of the Organization of Human Brain Mapping, Melbourne, Australia. poster pdf.
- Sabuncu MR, Singer BD, Bryan RE, Ramadge PJ, Haxby JV. (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 SM, Moore CD, Natu VS, Singer BD, Cohen JD, Haxby JV, Norman KA. (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 came to the CSBMB from the Center for Visual Science at the University of Rochester where I did psychophysics, electrophysiology, and real-time retinal imaging software as a research associate, following doctoral work in color vision psychophysics at UCI Cognitive Science and undergraduate work in philosophy of mind 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. google books.
- Chen L, Kruger P, Hofer H, Singer B, Williams DR. (2006). Accommodation with higher-order monochromatic aberrations corrected with adaptive optics. Journal of the Optical Society of America A, 23, 1-8. pdf.
- Chen L, Singer B, Guirao A, Porter J, Williams DR. (2005). Image metrics for predicting subjective image quality. Optometry and Vision Science, 82, 358-369. pdf.
- Hofer H, Singer B, Williams DR. (2005). Different sensations from cones with the same photopigment. Journal of Vision, 444-454. pdf
- Artal P, Chen L, Fernandez EJ, Singer B, Manzanera S, Williams DR. (2004). Neural compensation for the eye's optical aberrations. Journal of Vision, 281-287. pdf.
- Doble, N, Yoon GY, Chen L, Bierden P, Singer B, Olivier S, Williams DR. (2002). Use of a microelectromechanical mirror for adaptive optics in the human eye. Optics Letters, 27, 1537-1539. pdf.
- Hofer H, Chen L, Yoon GY, Singer B, Yamauchi Y, Williams DR. (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 JL, Williams DR. (2001). Dynamics of the eye's wave aberration, Journal of the Optical Society of America A, 18, 497-506. pdf
Human color vision:
- D'Zmura M, Singer B. (1999). Contrast gain control. In Sharpe LT, Gegenfurtner KR. (Eds.) Color Vision: From Genes to Perception. Cambridge: Cambridge University Press, 369-385. google books.
- 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 RD, D'Zmura M, Hoffman DD, Iverson G, Romney K. (Eds.), Geometric Representations of Perceptual Phenomena. Mahwah, NJ: Lawrence Erlbaum Associates, 187-202. google books.
- 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!
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.