Hyunjune Sebastian Seung
Systems and Circuits ; Theory and Computation
Systems and Circuits ; Theory and Computation

Evnin Professor in Neuroscience. Professor of Computer Science and the Princeton Neuroscience Institute. Co-Director, Program in Neuroscience.

Ph.D., Harvard University, 1990
Faculty

Research: Combines methods from biology and computer science to investigate the connectivity of neurons in biological tissue.

sseung@princeton.edu
Research Lab
609-258-7713
153 PNI


Research Focus

Sebastian Seung uses techniques from machine learning and social computing to extract brain structure from light and electron microscopic images. EyeWire showcases his approach by mobilizing gamers from around the world to create 3D reconstructions of neurons by interacting with a deep convolutional network. After reconstructing neural circuits, Seung applies computational methods to explain how they function. Current areas of interest include retinal, oculomotor, and cortical circuits.
 

Selected Publications

  • Vishwanathan A, Daie K, Ramirez AD, Lichtman JW, Aksay ERF, Seung HS. Electron Microscopic Reconstruction of Functionally Identified Cells in a Neural Integrator. Curr Biol. 2017 Jul 24;27(14):2137-2147.
  • Aleksandar Zlateski and H Sebastian Seung. 2017. Compile-time optimized and statically scheduled N-D convnet primitives for multi-core and many-core (Xeon Phi) CPUs. In Proceedings of the International Conference on Supercomputing (ICS ’17). ACM, New York, NY, USA, Article 8, 10 pages.
  • Prelec D, Seung HS, McCoy J. A solution to the single-question crowd wisdom problem. Nature. 2017 Jan 25;541(7638):532-535.
  • Ignacio Arganda-Carreras, Verena Kaynig, Curtis Rueden, Kevin W. Eliceiri, Johannes Schindelin, Albert Cardona, H. Sebastian Seung; Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification, Bioinformatics, Volume 33, Issue 15, 1 August 2017, Pages 2424
  • D Prelec, HS Seung, J McCoy, A solution to the single-question crowd wisdom problem. Nature 541 (7638), 532-535
  • M.J. Greene, J.S. Kim, H.S. Seung, the EyeWirers. Analogous convergence of sustained and transient inputs in parallel on and off pathways for retinal motion computation. Cell Reports 14, 1-9 (2016). 
  • Ragan, T, Kadiri LR, Sutin J, Taranda J, Arganda-Carreras I, Kim Y, Kim Y, Seung SH, Osten P. 2012. Serial two-photon tomography for automated ex vivo mouse brain imaging. Nature Methods.
  • Wickersham, IR, Sullivan HA, Seung HS. 2010. Production of glycoprotein-deleted rabies viruses for monosynaptic tracing and high-level gene expression in neurons. Nature Protocols. 5(3):595-606.
  • Wang, J, Hasan MT, Seung SH. 2009. Laser-evoked synaptic transmission in cultured hippocampal neurons expressing channelrhodopsin-2 delivered by adeno-associated virus. J Neurosci Methods. 183:165–75.
  • Turaga, SC, Briggman KL, Helmstaedter M, Denk W, Seung SH. 2009. Maximin affinity learning of image segmentation. CoRR. abs/0911.5372.
  • S. C. Turaga, J. F. Murray, V. Jain, F. Roth, M. Helmstaedter, K. Briggman, W. Denk, and H. S. Seung. Co
  • Y. Loewenstein, D. Prelec, and H. S. Seung. Operant matching as a Nash equilibrium of an intertemporal game. Neural Computation 21, 2755-2773 (2009).
  • H. S. Seung. Reading the Book of Memory: Sparse Sampling versus Dense Mapping of Connectomes. Neuron 62, 17-29 (2009).
  • V. Jain and H. S. Seung. Natural Image Denoising with Convolutional Networks. Advances in Neural Info. Proc. Systems 21 (Proceedings of NIPS '08), pp. 769-776. Cambridge, MA: MIT Press, 2009.
  • V. Jain, J. F. Murray, F. Roth, S. Turaga, V. Zhigulin, K. L. Briggman, M. N. Helmstaedter, W. Denk, and H. S. Seung. Supervised Learning of Image Restoration with Convolutional Networks. Proceedings: IEEE 11th International Conference on Computer Vision (ICCV) (2007).
  • C. Fang-Yen, M. C. Chu, H. S. Seung, R. R. Dasari, and M. S. Feld. Phase-referenced probe interferometer for biological surface profiling and displacement measurements. Rev. Sci. Instrum. 78, 123703 (2007).
  • I. R. Fiete, M. S. Fee, and H. S. Seung. Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. J. Neurophysiol. 98, 2038-57 (2007; Epub 2007 Jul 25).
  • C. Fang-Yen, S. Oh, Y. Park, W. Choi, S. Song, H. S. Seung, R. R. Dasari, and M. S. Feld. Imaging voltage-dependent cell motions with heterodyne Mach-Zehnder phase microscopy. Opt. Lett. 32, 1572-4 (2007).
  • U. Rokni, A. G. Richardson, E. Bizzi, and H. S. Seung. Motor learning with unstable neural representations. Neuron 54, 65366 (2007).
  • D. Z. Jin, F. M. Ramazanoglu, and H. S. Seung. Intrinsic bursting enhances the robustness of a neural network model of sequence generation by avian brain area HVC. J. Comput. Neurosci. 23, 283-299 (2007; Epub 2007 Apr 18).