Selected Publications

The following publications are a representative sample of recent work central to the Grossman Center mission. For full publication lists, see the pages of individual Center members.

Gao Y, Archer E, Paninski L, Cunningham JP (2016) Linear dynamical neural population models through nonlinear embeddings. NIPS.
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Elsayed GF, Lara AH, Churchland MM, Cunningham JP (2016). Complete reorganization of population response across linked computations in motor cortex. Nature Communications.
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Merel J, Carlson D, Paninski L, Cunningham JP (2016) Neuroprosthetic decoder training as imitation learning. PLOS Computational Biology.
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Friedrich, J. et al (2016). Multi-scale approaches for high-speed imaging and analysis of large neural populations. bioRxiv.
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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.
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Pnevmatikakis, E. et al (2016). Simultaneous denoising, deconvolution, and demixing of calcium imaging data. Neuron.
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Seely JS, Kaufman MT, Ryu SI, Shenoy KV, Cunningham JP, Churchland MM (2016). Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1. PLoS Comput. Bio.
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Cunningham, J.P. and Ghahramani, Z. (2015). Linear dimensionality reduction: survey, insights, and generalizations. Journal of Machine Learning Research.
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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.
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Merel J, Pianto DM, Cunningham JP, and Paninski L (2015) Encoder-decoder optimization for brain-computer interfaces. PLOS Computational Biology.
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Kao JC, Nuyujukian P, Ryu SI, Churchland MM, Cunningham JP, Shenoy KV (2015) Incorporating neural population dynamics increases brain-machine interface performance. Nature Communications.
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Kaufman MT, Churchland MM, Ryu SI, and Shenoy KV (2015) Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex. eLife.
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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.
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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.
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L. Buesing, T. Machado, J.P. Cunningham, and L. Paninski. (2014) Clustered factor analysis of multineuronal spike data. NIPS 27.
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Kaufman MT, Churchland MM, Ryu SI, Shenoy KV (2014). Cortical activity in the null space: permitting preparation without movement. Nature Neuroscience.
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J.P. Cunningham and B.M. Yu. (2014) Dimensionality reduction for large-scale neural recordings. Nature Neuroscience.
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Gilboa E, Saatci Y, Cunningham JP (2014) Scaling multidimensional inference for structured Gaussian Processes, IEEE Transactions on Pattern Analysis and Machine Intelligence, In Press.
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Shenoy KV, Sahani M, Churchland MM (2013) Cortical control of arm movements: a dynamical systems perspective. Annual Review of Neuroscience 36:337-359.
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Caron, S.J.C, Ruta, V., Abbott, L.F. and Axel, R. (2013) Random Convergence of Afferent Olfactory Inputs in the Drosophila Mushroom Body. Nature 497:113-117.
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Shababo, B., Paige, B., Pakman, A. & Paninski, L. (2013). Bayesian inference and online experimental design for mapping neural microcircuits. NIPS.
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Pnevmatikakis, E. and Paninski, L. (2013). Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions. NIPS.
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Ramirez, A. & Paninski, L. (2013). Fast generalized linear model estimation via expected log-likelihoods. J. Comput. Neurosci.
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Churchland MM*, Cunningham JP* (contributing equally), Kaufman MT, Nuyujukian P, Foster JD, Ryu SI, and Shenoy KV (2012) Structure of neural population dynamics during reaching. Nature 487: 51-56.
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Pillow, J., Ahmadian, Y. & Paninski, L. (2011). Model-based decoding, information estimation, and change-point detection in multi-neuron spike trains. Neural Computation 23: 1-45.
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Field, G., Gauthier, J., Sher, A. et al. (2010). Functional connectivity in the retina at the resolution of photoreceptors. Nature 467, 673-677.
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