Ashok Litwin-Kumar

Assistant Professor, Department of Neuroscience, Columbia University
Jerome L. Greene Science Center, rm. L6-077
ude [tod] aibmuloc [ta] 5263ka

I am an assistant professor in the Department of Neuroscience and a member of the Center for Theoretical Neuroscience and the Zuckerman Institute. Previously, I was a postdoc with Larry Abbott and a grad student with Brent Doiron.

I am looking for talented graduate students and postdocs. Information about applying to the Center for Theoretical Neuroscience can be found here.


T. H. Moskovitz, A. Litwin-Kumar & L. F. Abbott (2018). Feedback alignment in deep convolutional networks. arXiv: 1812.06488 [cs.NE]. bib | eprint ]

S. R. Bittner, R. C. Williamson, A. C. Snyder, A. Litwin-Kumar, B. Doiron, S. M. Chase, M. A. Smith & B. M. Yu (2017). Population activity structure of excitatory and inhibitory neurons. PLOS ONE 12(8), e0181773. bib | journal | pdf ]

K. Eichler*, F. Li*, A. Litwin-Kumar*, Y. Park, I. Andrade, C. M. Schneider-Mizell, T. Saumweber, A. Huser, C. Eschbach, B. Gerber, R. D. Fetter, J. W. Truman, C. E. Priebe, L. F. Abbott, A. S. Thum, M. Zlatic & A. Cardona (2017). The complete connectome of a learning and memory centre in an insect brain. Nature 548(7666), 175–182. bib | journal | pdf ]
News Feature on circuit mapping.

A. Litwin-Kumar, K. D. Harris, R. Axel, H. Sompolinsky & L. F. Abbott (2017). Optimal degrees of synaptic connectivity. Neuron 93(5), 1153–1164. bib | journal | pdf ]

R. C. Williamson, B. R. Cowley, A. Litwin-Kumar, B. Doiron, A. Kohn, M. A. Smith & B. M. Yu (2016). Scaling properties of dimensionality reduction for neural populations and network models. PLOS Computational Biology 12(12), e1005141. bib | journal | pdf ]

A. Litwin-Kumar, R. Rosenbaum & B. Doiron (2016). Inhibitory stabilization and visual coding in cortical circuits with multiple interneuron subtypes. Journal of Neurophysiology 115(3), 1399–1409. bib | journal | pdf ]

B. Doiron, A. Litwin-Kumar, R. Rosenbaum, G. Ocker & K. Josić (2016). The mechanics of state dependent neural correlations [review]. Nature Neuroscience 19(3), 383–393. bib | journal | pdf ]

G. Ocker, A. Litwin-Kumar & B. Doiron (2015). Self-organization of microcircuit structure in networks of spiking neurons with plastic synapses. PLOS Computational Biology 11(8), e1004458. bib | journal | pdf ]

A. Litwin-Kumar & B. Doiron (2014). Formation and maintenance of neuronal assemblies through synaptic plasticity. Nature Communications 5(5319). bib | journal | pdf ]

B. Doiron & A. Litwin-Kumar (2014). Balanced neural architecture and the idling brain. Frontiers in Computational Neuroscience 8(56). bib | journal | pdf ]

A. Litwin-Kumar (2013). Relationship between neuronal architecture and variability in cortical circuits. Ph.D. thesis, Carnegie Mellon University. bib | link ]

A. Litwin-Kumar & B. Doiron (2012). Slow dynamics and high variability in balanced cortical networks with clustered connections. Nature Neuroscience 15(11), 1498–1505. bib | journal | pdf ]
News & Views by M. M. Churchland & L. F. Abbott.

A. Litwin-Kumar, M. J. Chacron & B. Doiron (2012). The spatial structure of stimuli shapes the timescale of correlations in population spiking activity. PLOS Computational Biology 8(9), e1002667. bib | journal | pdf ]

A. Polk, A. Litwin-Kumar & B. Doiron (2012). Correlated neural variability in persistent state networks. PNAS 109(16), 6295–6300. bib | journal | pdf ]

A. Litwin-Kumar, A. M. Oswald, N. N. Urban & B. Doiron (2011). Balanced synaptic input shapes the correlation between neural spike trains. PLOS Computational Biology 7(12), e1002305. bib | journal | pdf ]

Publications also on Google scholar. *equal contribution


2017: Algorithms for computation of dimension and error rate from Litwin-Kumar, Harris, Axel, Sompolinsky & Abbott. [ download ]

2016: Spiking network with multiple inhibitory interneuron subtypes from Litwin-Kumar, Rosenbaum & Doiron. [ download ]

2014: Balanced spiking network with synaptic plasticity from Litwin-Kumar & Doiron. [ download ]

2012: Balanced spiking network with clustered connections from Litwin-Kumar & Doiron. [ download ]

Code is written in Julia and Python.


Math 0290: Applied Differential Equations (University of Pittsburgh, Spring 2014)

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