Jonathan W. Pillow, Ph.D.

2009-2014 Psychology University of Texas at Austin, Austin, Texas, U.S.A. 
 2014- Princeton Neuroscience Institute Princeton University, Princeton, NJ 
Computational Neuroscience, Machine Learning
"Jonathan Pillow"
Mean distance: 13.82 (cluster 17)


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Rich S. Zemel research assistant University of Arizona
Eero P. Simoncelli grad student 2001-2005 Princeton
 (Neural coding and the statistical modeling of neuronal responses.)
Peter Latham post-doc 2005-2008 Gatsby Computational Neuroscience Unit


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Lea Duncker research assistant 2015-2016 Princeton
Yoel Sanchez Araujo grad student Princeton
Mike Morais grad student 2016- Princeton
David Zoltowski grad student 2017- Princeton
Zoe Ashwood grad student 2018- Princeton
Kevin S. Chen grad student 2018- Princeton
Iris Stone grad student 2018- Princeton
Mijung Park grad student 2009-2013 UT Austin
Kenneth W. Latimer grad student 2011-2015 UT Austin
Jacob Yates grad student 2011-2016 UT Austin
Ji Hyun Bak grad student 2015-2016 Princeton
Anqi Wu grad student 2014-2019 Princeton
Nick A Roy grad student 2015-2020 Princeton
Mikio Aoi post-doc Princeton
Adam Charles post-doc 2015- Princeton
Brian D. DePasquale post-doc 2016- Princeton
Ben Cowley post-doc 2018- Princeton
Abigail A Russo post-doc 2019- Princeton
Il Memming Park post-doc 2010-2014 UT Austin
Stephen Keeley post-doc 2018-2020 Princeton
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Keeley SL, Zoltowski DM, Aoi MC, et al. (2020) Modeling statistical dependencies in multi-region spike train data. Current Opinion in Neurobiology
Aoi MC, Mante V, Pillow JW. (2020) Prefrontal cortex exhibits multidimensional dynamic encoding during decision-making. Nature Neuroscience
Yates JL, Katz LN, Levi AJ, et al. (2019) A simple linear readout of MT supports motion direction-discrimination performance. Journal of Neurophysiology
Latimer KW, Rieke F, Pillow JW. (2019) Inferring synaptic inputs from spikes with a conductance-based neural encoding model. Elife. 8
Williamson RS, Sahani M, Pillow JW. (2019) Correction: The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction (Plos Comput Biol, (2015), 11, 4, 10.1371/journal.pcbi.1004141) Plos Computational Biology. 15
Jonathan Pillow, Sahani M. (2019) Editorial overview: Machine learning, big data, and neuroscience. Current Opinion in Neurobiology. 55: iii-iv
Zoltowski DM, Latimer KW, Yates JL, et al. (2019) Discrete Stepping and Nonlinear Ramping Dynamics Underlie Spiking Responses of LIP Neurons during Decision-Making. Neuron
Latimer KW, Rieke F, Pillow JW. (2019) Author response: Inferring synaptic inputs from spikes with a conductance-based neural encoding model Elife
Aoi MC, Pillow JW. (2018) Model-based targeted dimensionality reduction for neuronal population data. Advances in Neural Information Processing Systems. 31: 6690-6699
Zoltowski DM, Pillow JW. (2018) Scaling the Poisson GLM to massive neural datasets through polynomial approximations. Advances in Neural Information Processing Systems. 31: 3517-3527
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