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.
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.
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.
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)
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
Bridging the gap between deep learning and neuroscience
29 Apr 2016
Graphical modeling of time-course data
10 May 2016
U. New South Wales
System identification of point process networks
10 May 2016
Population-level changes in neural activity during learning
17 May 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
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.
The Grossman Center for the Statistics of Mind is made possible through the generosity of the Sanford J. Grossman Charitable Trust.