Eero Simoncelli

 

Image Statistics

Lecture Slides: Image statistics I: PCA/spectral models,    Image statistics II: wavelet/joint models

demos and tutorials

 


papers

Math Tools Handouts

Estimation/Decision Theory (partial draft)
Linear Systems
Linear Algebra
Another Linear Algebra handout (by Mike Jordan)
Least Squares Estimation (Regression) and PCA

Efficient Coding: Connecting image statistics to neural function

Natural Image statistics and neural representation.
E P Simoncelli and B A Olshausen. Annual Review of Neuroscience, 24:1193-1216, May 2001. [pdf]

Natural signal statistics and sensory gain control.
O Schwartz and E P Simoncelli. Nature: Neuroscience, 4(8):819-825, August 2001. [pdf]

Natural image statistics and divisive normalization: Modeling nonlinearity and adaptation in cortical neurons.
M J Wainwright, O Schwartz, and E P Simoncelli. In Probabilistic Models of the Brain: Perception and Neural Function,
eds. R Rao, B Olshausen, and M Lewicki. MIT Press. Spring, 2002. [pdf]

Responses of neurons in primary and inferior temporal cortices to natural scenes.
R Baddeley, L F Abbott, M C Booth, F Sengpiel, T Freeman, E A Wakeman, E T Rolls. Proceedings of the Royal Society B, vol 264 pp 1775--1783, 1997. [pdf]

Emergence of simple-cell receptive field properties by learning a sparse code for natural images.
B A Olshausen and D J Field. Nature, 381:607-609, 1996. [pdf]

Possible principles underlying the transformations of sensory messages
H B Barlow. In Sensory Communications, ed. W A Rosenblith, pp 217-234, MIT Press. 1961. [pdf]

Spike-triggered analyses

Characterization of neural responses with stochastic stimuli
E P Simoncelli, J Pillow, L Paninski, and O Schwartz.
In The Cognitive Neurosciences, 3rd edition Ed: M Gazzaniga. MIT Press, November, 2004 (to appear).
[ Abstract, pdf]

Spike-triggered characterization of excitatory and suppressive stimulus dimensions in monkey V1
N C Rust, O Schwartz, J A Movshon and E P Simoncelli.
Presented at the annual meeting, Computational Neuroscience (CNS*03), Alicante Spain, 5-9 July 2003.
Published in Neurocomputing, Elsevier, 2004. [Abstract, pdf]

Maximum likelihood estimation of a stochastic integrate-and-fire neural model
J W Pillow, L Paninski, and E P Simoncelli.
Presented at Neural Information Processing Systems, December 2003 (NIPS*2003).
Published in Adv. Neural Information Processing Systems, v16, May 2004. [Abstract, pdf ]

Biases in white noise analysis due to non-Poisson spike generation
J Pillow and E P Simoncelli (2002). Presented at Computational Neuroscience Meeting*02. [pdf]

Characterizing neural gain control using spike-triggered covariance
O Schwartz, EJ Chichilnisky, and E P Simoncelli. Adv. Neural Information Processing Systems, v14, May 2002 (NIPS*2001). [pdf]

A simple white noise analysis of neuronal light responses
EJ Chichilnisky. Network, 12(2):199-213, 2001. [pdf]

Motion: Perception/Modeling

Local analysis of visual motion
E P Simoncelli. Chapter 109 in The Visual Neurosciences, eds. L M Chalupa and J S Werner, MIT Press. 2003. [pdf]

Motion illusions as optimal percepts
Y Weiss, E P Simoncelli, and E H Adelson. Nature: Neuroscience, 5(6):598-604, June 2002. [pdf]

Mechanisms of visual motion detection.
P R Schrater, D C Knill, and E P Simoncelli. Nature: Neuroscience, 3(1):64-68, January 2000. [pdf]

A model of neuronal responses in visual area MT.
E P Simoncelli and D J Heeger. Vision Research, 38(5):743-761, 1998. [pdf]

The analysis of moving visual patterns.
J A Movshon, E H Adelson, M S Gizzi, and W T Newsome. In Experimental Brain Research Supplementum II: Pattern Recognition Mechanisms, eds. C Chagas, R Gattass, and C Gross. pp 117-151. Springer-Verlag, 1986. [pdf]

Spatio-temporal energy models for the perception of motion.
E H Adelson and J R Bergen JOSA 2(2):284-299, 1985. [pdf]

 


links

Simoncelli's homepage
Additional publications...