The overall mission of the Grossman Center for the Statistics of Mind is to better understand the brain by applying quantitative methods to uncover deep and meaningful structure in large neural datasets.
We just moved into a beautiful new space.
John Cunningham was recently named a Sloan Research Fellow and a McKnight Scholar.
Mark Churchland was recently named a Klingenstein-Simons Fellow.
Randy Bruno, Ph.D.
Associate Professor, Neuroscience; member, The Kavli Institute for Brain Science.
Prof. Bruno has been named as the first Grossman-Kavli faculty scholar.
John Cunningham, Ph.D.
Assistant Professor, Statistics.
Prof. Cunningham has joined us as the newest faculty member of the Grossman Center.
Mark Churchland, Ph.D.
Assistant Professor, Neuroscience; member, The Kavli Institute for Brain Science, David Mahoney Center for Brain and Behavior Research.
Liam Paninski, Ph.D.
Professor, Statistics and Neuroscience; member, Center for Theoretical Neuroscience; member, The Kavli Institute for Brain Science.
Evan Archer (Cognescent)
Lars Buesing (Google DeepMind)
David Carlson (Duke)
Dean Freestone (University of Melbourne)
Josh Merel (Google DeepMind)
Eftychios Pnevmatikakis (Simons Center for Data Analysis)
Larry Abbott, Ph.D.
William Bloor Professor of Neuroscience, Physiology & Cellular Biophysics, Biological Sciences; co-director, Center for Theoretical Neuroscience
Richard Axel, M.D.
University Professor; Investigator, Howard Hughes Medical Institute, co-director, Zuckerman Mind Brain Behavior Institute
Thomas Jessell, Ph.D.
Claire Tow Professor, Neuroscience and Biochemistry & Molecular Biophysics; co-director, Zuckerman Mind Brain Behavior Institute, co-director, Kavli Institute for Brain Science; Investigator, Howard Hughes Medical Institute
Michael N. Shadlen, M.D., Ph.D.
Professor of Neuroscience; Investigator, Howard Hughes Medical Institute
David Madigan, Ph.D.
Professor, Department of Statistics; Executive Vice President, Arts and Sciences
Recent / upcoming
Computational Statistics, Liam Paninski, Spring
Statistical Analysis of Neural Data, Liam
Paninski, Fall 2015.
Gaussian Processes and Kernel Methods, John Cunningham, Fall 2015.
Advanced Topics in Theoretical Neuroscience, Larry Abbott, Stefano Fusi, Ken Miller, Spring 2014.
Selected Recent Publications
Gao Y, Archer E, Paninski L, Cunningham JP (2016) Linear dynamical neural population models through nonlinear embeddings. NIPS.
Elsayed GF, Lara AH, Churchland MM, Cunningham JP (2016). Complete reorganization of population response across linked computations in motor cortex. Nature Communications.
Gabitto M., Pakman A., Bikoff J., Abbott L., Jessell T. & Paninski, L. (2016). Bayesian sparse regression analysis reveals the extent of spinal V1 interneuron diversity. Cell.
Pnevmatikakis, E. et al (2016). Simultaneous denoising, deconvolution, and demixing of
calcium imaging data. Neuron.
Merel J, Carlson D, Paninski L, Cunningham JP (2016) Neuroprosthetic decoder training as imitation learning. PLOS Computational Biology.
The Grossman Center for the Statistics of Mind is made possible through the generosity of the Sanford J. Grossman Charitable Trust.