Suggested further readings

Further reading on linear dynamical systems models in neuroscience:

Costa, A. C., Ahamed, T., and Stephens, G. J. (2019). Adaptive, locally linear models of complex dynamics. Proceedings of the National Academy of Sciences 116(5): 1501-1510. doi: 10.1073/pnas.1813476116 Open Access publication.

Billeh, Y. N., Cai, B., Gratiy, S. L., Dai, K., Iyer, R., Gouwens, N. W., … and Arkhipov, A. (2020). Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex. Neuron 106(3): 388-403. doi: 10.1016/j.neuron.2020.01.040 Open Access publication.

Brunton, B. W., Botvinick, M. M., and Brody, C. D. (2013). Rats and humans can optimally accumulate evidence for decision-making. Science 340(6128): 95-98. doi: 10.1126/science.1233912 Closed Access publication.

Brunton, B. W., Johnson, L. A., Ojemann, J. G., and Kutz, J. N. (2016). Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition. Journal of neuroscience methods 258: 1-15. doi: 10.1016/j.jneumeth.2015.10.010 Open Access publication.

Gilson, M., Burkitt, A. N., Grayden, D. B., Thomas, D. A., and van Hemmen, J. L. (2009). Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity–strengthening correlated input pathways. Biological cybernetics 101(2): 81-102. doi: 10.1007/s00422-009-0319-4 Closed Access publication.

Harris, K. D., Aravkin, A., Rao, R., and Brunton, B. W. (2021). Time-Varying Autoregression with Low-Rank Tensors. SIAM Journal on Applied Dynamical Systems 20(4): 2335-2358. doi: 10.1137/20M1338058 Closed Access publication (preprint: Open Access publication).

Hodgkin, A. L., and Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of physiology 117(4): 500–544. doi: 10.1113/jphysiol.1952.sp004764 Open Access publication.

Hu, Y., Brunton, S. L., Cain, N., Mihalas, S., Kutz, J. N., and Shea-Brown, E. (2018). Feedback through graph motifs relates structure and function in complex networks. Physical Review E 98(6): 062312. doi: 10.1103/physreve.98.062312 Open Access publication.

Izhikevich, E.M. (2007). Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting. MIT Press.

Linderman, S. W., Miller, A. C., Adams, R. P., Blei, D. M., Paninski, L., and Johnson, M. J. (2016). Recurrent switching linear dynamical systems. arXiv preprint. arXiv:1610.08466.

Mante, V., Sussillo, D., Shenoy, K. V., and Newsome, W. T. (2013). Context-dependent computation by recurrent dynamics in prefrontal cortex. Nature 503(7474): 78-84. doi: 10.1038/nature12742 Closed Access publication (postprint: Open Access publication)

Morrison, K., and Curto, C. (2019). Predicting neural network dynamics via graphical analysis. In: Algebraic and Combinatorial Computational Biology (pp. 241-277). Academic Press. doi: 10.1016/B978-0-12-814066-6.00008-8 Closed Access publication (preprint: Open Access publication) or arxiv:1804.01487.

Ocker, G. K., Litwin-Kumar, A., and Doiron, B. (2015). Self-organization of microcircuits in networks of spiking neurons with plastic synapses. PLoS computational biology 11(8): e1004458. doi: 10.1371/journal.pcbi.1004458 Open Access publication.

Ocker, G. K., Josić, K., Shea-Brown, E., and Buice, M. A. (2017). Linking structure and activity in nonlinear spiking networks. PLoS computational biology 13(6): e1005583. doi: 10.1371/journal.pcbi.1005583 Open Access publication.

Pillow, J. W., Shlens, J., Paninski, L., Sher, A., Litke, A. M., Chichilnisky, E. J., and Simoncelli, E. P. (2008). Spatio-temporal correlations and visual signalling in a complete neuronal population. Nature 454(7207): 995-999. doi: 10.1038/nature07140 Closed Access publication (postprint: Open Access publication).

Seung, H. S. (1996). How the brain keeps the eyes still. Proceedings of the National Academy of Sciences 93(23): 13339-13344. doi: 10.1073/pnas.93.23.13339 Open Access publication.

Usher, M., and McClelland, J. L. (2001). The time course of perceptual choice: the leaky, competing accumulator model. Psychological review 108(3): 550. doi: 10.1037/0033-295X.108.3.550 Closed Access publication.

Further reading from Outro lecture:

Ames, K. C., Ryu, S. I., and Shenoy, K. V. (2019). Simultaneous motor preparation and execution in a last-moment reach correction task. Nature communications 10(1): 1-13. doi: 10.1038/s41467-019-10772-2 Open Access publication.

Churchland, M. M., Cunningham, J. P., Kaufman, M. T., Foster, J. D., Nuyujukian, P., Ryu, S. I., and Shenoy, K. V. (2012). Neural population dynamics during reaching. Nature 487(7405): 51-56. doi: 10.1038/nature11129 Closed Access publication (postprint: Open Access publication).

Gilja, V., Pandarinath, C., Blabe, C. H., Nuyujukian, P., Simeral, J. D., Sarma, A. A., … and Henderson, J. M. (2015). Clinical translation of a high-performance neural prosthesis. Nature medicine 21(10): 1142-1145. doi: 10.1038/nm.3953 Closed Access publication (postprint: Open Access publication).

Kao, J. C., Nuyujukian, P., Ryu, S. I., Churchland, M. M., Cunningham, J. P., and Shenoy, K. V. (2015). Single-trial dynamics of motor cortex and their applications to brain-machine interfaces. Nature communications 6(1): 1-12. doi: 10.1038/ncomms8759 Open Access publication.

Kao, J. C., Nuyujukian, P., Ryu, S. I., and Shenoy, K. V. (2016). A high-performance neural prosthesis incorporating discrete state selection with hidden Markov models. IEEE Transactions on Biomedical Engineering: 64(4) 935-945. doi: 10.1109/TBME.2016.2582691 Closed Access publication.

Nuyujukian, P., Kao, J. C., Ryu, S. I., and Shenoy, K. V. (2016). A nonhuman primate brain–computer typing interface. Proceedings of the IEEE 105(1): 66-72. doi: 10.1109/JPROC.2016.2586967 Closed Access publication (postprint: Open Access publication).

Nuyujukian, P., Albites Sanabria, J., Saab, J., Pandarinath, C., Jarosiewicz, B., Blabe, C. H., … and Henderson, J. M. (2018). Cortical control of a tablet computer by people with paralysis. PloS one 13(11): e0204566. doi: 10.1371/journal.pone.0204566 Open Access publication.

Pandarinath, C., O’Shea, D. J., Collins, J., Jozefowicz, R., Stavisky, S. D., Kao, J. C., … and Sussillo, D. (2018). Inferring single-trial neural population dynamics using sequential auto-encoders. Nature methods: 15(10) 805-815. doi: 10.1038/s41592-018-0109-9 Closed Access publication (postprint: Open Access publication).

Pandarinath, C., Nuyujukian, P., Blabe, C. H., Sorice, B. L., Saab, J., Willett, F. R., … and Henderson, J. M. (2017). High performance communication by people with paralysis using an intracortical brain-computer interface. Elife 6: e18554. doi: 10.7554/eLife.18554 Open Access publication.

Santhanam, G., Yu, B. M., Gilja, V., Ryu, S. I., Afshar, A., Sahani, M., and Shenoy, K. V. (2009). Factor-analysis methods for higher-performance neural prostheses. Journal of neurophysiology 102(2): 1315-1330. doi: 10.1152/jn.00097.2009 Open Access publication.

Shenoy, K. V., Sahani, M., and Churchland, M. M. (2013). Cortical control of arm movements: a dynamical systems perspective. Annual review of neuroscience 36: 337-359. doi: 10.1146/annurev-neuro-062111-150509 Closed Access publication.

Stavisky, S. D., Kao, J. C., Ryu, S. I., and Shenoy, K. V. (2017). Motor cortical visuomotor feedback activity is initially isolated from downstream targets in output-null neural state space dimensions. Neuron 95(1): 195-208. doi: 10.1016/j.neuron.2017.05.023 Open Access publication.

Stavisky, S. D., Willett, F. R., Wilson, G. H., Murphy, B. A., Rezaii, P., Avansino, D. T., … and Henderson, J. M. (2019). Neural ensemble dynamics in dorsal motor cortex during speech in people with paralysis. Elife 8: e46015. doi: 10.7554/eLife.46015 Open Access publication.

Trautmann, E. M., Stavisky, S. D., Lahiri, S., Ames, K. C., Kaufman, M. T., O’Shea, D. J., … and Shenoy, K. V. (2019). Accurate estimation of neural population dynamics without spike sorting. Neuron 103(2): 292-308. doi: 10.1016/j.neuron.2019.05.003 Open Access publication.

Vyas, S., Even-Chen, N., Stavisky, S. D., Ryu, S. I., Nuyujukian, P., and Shenoy, K. V. (2018). Neural population dynamics underlying motor learning transfer. Neuron 97(5): 1177-1186. doi: 10.1016/j.neuron.2018.01.040 Open Access publication.

Vyas, S., Golub, M. D., Sussillo, D., and Shenoy, K. V. (2020). Computation through neural population dynamics. Annual Review of Neuroscience 43: 249-275. doi: 10.1146/annurev-neuro-092619-094115 Closed Access publication (postprint: Open Access publication).

Vyas, S., O’Shea, D. J., Ryu, S. I., and Shenoy, K. V. (2020). Causal role of motor preparation during error-driven learning. Neuron 106(2): 329-339. doi: 10.1016/j.neuron.2020.01.019 Open Access publication.

Willett, F. R., Deo, D. R., Avansino, D. T., Rezaii, P., Hochberg, L. R., Henderson, J. M., and Shenoy, K. V. (2020). Hand knob area of premotor cortex represents the whole body in a compositional way. Cell 181(2): 396-409. doi: 10.1016/j.cell.2020.02.043 Open Access publication.

Williams, A. H., Kim, T. H., Wang, F., Vyas, S., Ryu, S. I., Shenoy, K. V., … and Ganguli, S. (2018). Unsupervised discovery of demixed, low-dimensional neural dynamics across multiple timescales through tensor component analysis. Neuron 98(6): 1099-1115. doi: 10.1016/j.neuron.2018.05.015 Open Access publication.

Yu, B. M., Cunningham, J. P., Santhanam, G., Ryu, S., Shenoy, K. V., and Sahani, M. (2008). Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity. Advances in neural information processing systems, 21. url: NIPS2008.