Psychology Department -> People -> Faculty Directory ->
Jonathan Pillow, Ph.D.
Assistant Professor of Psychology
VITA
Email: pillow@mail.utexas.edu
Office Phone: 512-232-1923 Lab: 512-232-5010
Office: SEA 4.104.
Neural Coding and Computation Lab
See also Institute for Neuroscience
Perceptual Systems, Center for Perceptual Systems
Jonathan Pillow received a Ph.D. in Neural Science from New York University, and was a postdoctoral fellow at the Gatsby Computational Neuroscience Unit, UCL, before coming to the University of Texas. Jonathan's research interests lie at the intersection of computational neuroscience, machine learning, and human visual perception. His lab employs a variety of theoretical tools, in conjunction with psychophysical experiments, to study how neural populations represent and process information. He collaborates closely with labs devoted to neurophysiology and fMRI, applying Bayesian statistical methods to model the responses of neural populations in the visual pathway.
Current research topics include: neural decoding methods, population coding, human motion perception, theoretical models of adaptation, natural scene statistics, and unsupervised learning with spike trains.
Selected Publications:
(See Dr. Pillows's Lab page for full list of publications which can be downloaded as PDF files)
Pillow, JW, Shlens, J, Paninski, L, Sher, A, Litke, AM, Chichilnisky, EJ, Simoncelli, EP. (2008) Spatio-temporal correlations and visual signaling in a complete neuronal population. Nature 454: 995-999.
Pillow JW and Simoncelli EP. (2006). Dimensionality reduction in neural models: an information-theoretic generalization of spike-triggered average and covariance analysis. Journal of Vision, 6(4):414-428.
Pillow JW, Paninski L, Uzzell VJ, Simoncelli EP, Chichilnisky EJ. (2005). Prediction and Decoding of Retinal Ganglion Cell Responses with a Probabilistic Spiking Model. Journal of Neuroscience 25:11003-11013.
Pillow JW & Rubin N. (2002). Perceptual Completion across the Vertical Meridian and the Role of Early Visual Cortex. Neuron 33(5):805-13.
