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.


Several new postdoc positions are available: see links here and here for details.

John Cunningham was recently named a Sloan Research Fellow and a McKnight Scholar.

Mark Churchland was recently named a Klingenstein-Simons Fellow.

Several center members (Paninski, Abbott, Cunningham, and Churchland) recently received Simons Collaboration on the Global Brain 2014 research awards.

Randy Bruno, Ph.D.

Assistant Professor, Neuroscience; member, The Kavli Institute for Brain Science.

Prof. Bruno has been named as the first Grossman-Kavli faculty scholar.

Lab Website

John Cunningham, Ph.D.

Assistant Professor, Statistics.

Prof. Cunningham has joined us as the newest faculty member of the Grossman Center.

Lab Website


Mark Churchland, Ph.D.

Assistant Professor, Neuroscience; member, The Kavli Institute for Brain Science, David Mahoney Center for Brain and Behavior Research.

Lab Website

Liam Paninski, Ph.D.

Professor, Statistics and Neuroscience; member, Center for Theoretical Neuroscience; member, The Kavli Institute for Brain Science.

Lab Website

Center Postdocs

Cora Ames

Evan Archer

David Carlson

Johannes Friedrich

Logan Grosenick

Antonio Lara

Ari Pakman

Daniel Soudry

Uygar Sumbul


Lars Buesing (now at Google DeepMind)

Dean Freestone (University of Melbourne)

Josh Merel (now at Google DeepMind)

Eftychios Pnevmatikakis (now at the Simons Center for Data Analysis)

Advisory board

Larry Abbott, Ph.D.

William Bloor Professor of Neuroscience, Physiology & Cellular Biophysics, Biological Sciences; co-director, Center for Theoretical Neuroscience

Lab Website

Richard Axel, M.D.

University Professor; Investigator, Howard Hughes Medical Institute, co-director, Zuckerman Mind Brain Behavior Institute

Lab Website

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

Lab Website

Michael N. Shadlen, M.D., Ph.D.

Professor of Neuroscience; Investigator, Howard Hughes Medical Institute

Lab Website

David Madigan, Ph.D.

Professor, Department of Statistics; Executive Vice President, Arts and Sciences

Lab Website


Recent / upcoming

Yoshua Bengio
Bridging the gap between deep learning and neuroscience
Neurotheory seminar
29 Apr 2016

Shizhe Chen
Graphical modeling of time-course data
Neurostat seminar
10 May 2016

Vic Solo
U. New South Wales
System identification of point process networks
Neurostat seminar
10 May 2016

Matt Golub
Population-level changes in neural activity during learning
Neurostat seminar
17 May 2016

Neurostat group meetings

Neurotheory seminar series


Fall 2012

Spring/Summer 2013

Fall 2013

Spring 2014

Fall 2014

Spring 2015

Fall 2015

Spring 2016


Statistical Analysis of Neural Data, Liam Paninski, Fall 2015.

Gaussian Processes and Kernel Methods, John Cunningham, Fall 2015.

Theoretical Neuroscience, Larry Abbott, Stefano Fusi, Ken Miller, Spring 2014.

Computational Statistics, Liam Paninski, Spring 2014.

Selected Recent Publications

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.

Cunningham JP, Ghahramani Z (2015) Linear dimensionality reduction: survey, insights, and generalizations. Journal of Machine Learning Research.

Machado, T.A. , Pnevmatikakis, E., Paninski, L., Jessell, T.M., Miri, A. (2015). "Primacy of flexor locomotor pattern revealed by ancestral reversion of motor neuron identity" Cell.

Merel J, Pianto DM, Cunningham JP, and Paninski L (2015) Encoder-decoder optimization for brain-computer interfaces. PLOS Computational Biology.

Kao JC, Nuyujukian P, Ryu SI, Churchland MM, Cunningham JP, Shenoy KV (2015) Incorporating neural population dynamics increases brain-machine interface performance. Nature Communications.

Kaufman MT, Churchland MM, Ryu SI, and Shenoy KV (2015) Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex. eLife.

Sussillo D, Churchland MM, Kaufman MT, and Shenoy KV (2015) A neural network that finds naturalistic solutions for the production of muscle activity. Nature Neuroscience.

Soudry, D., Keshri, S., Stinson, P., Oh, M.-W., Iyengar, G. & Paninski, L. (2015). Efficient 'shotgun' inference of neural connectivity from highly sub-sampled activity data. PLoS Comp. Bio.



Columbia University

Department of Neuroscience

Department of Statistics

Center for Theoretical Neuroscience

Zuckerman Mind Brain Behavior Institute (MBBI)

Institute for Data Sciences and Engineering

The Grossman Center for the Statistics of Mind is made possible through the generosity of the Sanford J. Grossman Charitable Trust.