Publications of Sebastian Seung V. Jain, H. S. Seung, and S. C. Turaga. Machines that learn to segment images: a crucial technology for connectomics. (pdf) Curr. Opin. Neurobiol (2010). V. Jain, B. Bollmann, M. Richardson, D. Berger et al. Boundary learning by optimization with topological constraints. (pdf supplementary info) Proceedings of the IEEE 23rd Conference on Computer Vision and Pattern Recognition (2010). I. R. Wickersham, H. A. Sullivan, and H. S. Seung. Production of glycoprotein-deleted rabies viruses for monosynaptic tracing and high-level gene expression in neurons. (pdf) Nature Protocols. 5, 596-606 (2010). S. C. Turaga, J. F. Murray, V. Jain, F. Roth, M. Helmstaedter, K. Briggman, W. Denk, and H. S. Seung. Convolutional networks can learn to generate affinity graphs for image segmentation. (pdf) Neural Computation 22, 511-538 (2010). S. C. Turaga, K. L. Briggman, M. Helmstaedter, W. Denk, and H. S. Seung. Maximin affinity learning of image segmentation. (pdf) Adv. Neural Info. Proc. Syst. 22 (Proceedings of NIPS '09) (2010). J. Wang, M. T. Hasan, and H. S. Seung. Laser-evoked synaptic transmission in cultured hippocampal neurons expressing Channelrhodopsin-2 delivered by adeno-associated virus.(pdf) J. Neurosci. Methods 183, 165-175 (2009). Y. Loewenstein, D. Prelec, and H. S. Seung. Operant matching as a Nash equilibrium of an intertemporal game. (pdf) Neural Computation 21, 2755-2773 (2009). H. S. Seung. Reading the Book of Memory: Sparse Sampling versus Dense Mapping of Connectomes. (pdf) Neuron 62, 17-29 (2009). V. Jain and H. S. Seung. Natural Image Denoising with Convolutional Networks (pdf) Adv. Neural Info. Proc. Syst. 21 (Proceedings of NIPS '08) 769-776 (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.(pdf) 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.(pdf) 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.(pdf) J. Neurophysiol. 98, 2038-57 (2007). 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.(pdf) 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.(pdf) J. Comput. Neurosci. 23, 283-299 (2007; Epub 2007 Apr 18). Y. Loewenstein and H. S. Seung. Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity. (pdf) Proc. Natl. Acad. Sci. USA 103, 15224-15229 (2006). I. R. Fiete and H. S. Seung. Gradient learning in spiking neural networks by dynamic perturbation of conductances. (pdf) Phys. Rev. Lett. 97, 048104 (2006). V. Jain, V. Zhigulin, and H. S. Seung. Representing part-whole relationships in recurrent neural networks. (pdf) Adv. Neural Info. Proc. Syst. 18, 563--70 (2006). G. S. Corrado, L. P. Sugrue, H. S. Seung, and W. T. Newsome. Linear-nonlinear-Poisson models of primate choice dynamics. (pdf) J. Exp. Anal. Behav. 84, 581-617 (2005). D. Z. Jin, V. Dragoi, M. Sur, and H. S. Seung. Tilt aftereffect and adaptation-induced changes in orientation tuning in visual cortex. (pdf) J. Neurophysiol. 94, 4038-4050 (2005). R. Tedrake, T. W. Zhang, and H. S. Seung. Learning to Walk in 20 Minutes. (pdf) In Proceedings of the Fourteenth Yale Workshop on Adaptive and Learning Systems, Yale University, New Haven, CT, 2005. J. Werfel, X. Xie, and H. S. Seung. Learning curves for stochastic gradient descent in linear feedforward networks. (pdf) Neural Comput. 17, 2699-2718 (2005). Earlier version: J. Werfel, X. Xie, and H. S. Seung. Learning curves for stochastic gradient descent in linear feedforward networks. (pdf) Adv. Neural Info. Proc. Syst. 16 (2004). A. Starovoytov, J. Choi, and H. S. Seung. Light-directed electrical stimulation of neurons cultured on silicon wafers. (pdf) J. Neurophysiol. 93, 1090-1098 (2005; Epub 2004 Sep 22). C. Fang-Yen, M. C. Chu, H. S. Seung, R. R. Dasari, and M. S. Feld. Noncontact measurement of nerve displacement during action potential with a dual-beam low-coherence interferometer. (pdf) Opt. Lett. 29, 2028-2030 (2004). B. D. Mensh, J. Werfel, and H. S. Seung. BCI Competition 2003 - Data set Ia: combining gamma- band power with slow cortical potentials to improve single-trial classification of electroencephalographic signals. (pdf) IEEE Trans. Biomed. Eng. 51, 1052-1056 (2004). I. R. Fiete, R. H. R. Hahnloser, M. S. Fee, and H. S. Seung. Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. (pdf) J. Neurophysiol. 92, 2274-2282 (2004). G. Major, R. Baker, E. Aksay, H. S. Seung, and D. W. Tank. Plasticity and tuning of the time course of analog persistent firing in a neural integrator. (pdf) Proc. Natl. Acad. Sci. USA 101, 7745-7750 (2004). G. Major, R. Baker, E. Aksay, B. Mensh, H. S. Seung, and D. W. Tank. Plasticity and tuning by visual feedback of the stability of a neural integrator. (pdf) Proc. Natl. Acad. Sci. 101, 7739-7744 (2004). X. Xie and H. S. Seung. Learning in neural networks by reinforcement of irregular spiking. (pdf) Phys. Rev. E69, 041909 (2004). B. D. Mensh, E. Aksay, D. D. Lee, H. S. Seung, and D. W. Tank. Spontaneous eye movements in goldfish: Oculomotor integrator performance, plasticity, and dependence on visual feedback. (pdf) Vision Res. 44, 711-726 (2004). R. Tedrake, T. W. Zhang, and H. S. Seung. Stochastic Policy Gradient Reinforcement Learning on a Simple 3D Biped. (pdf) In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), pages 2849-2854, Sendai, Japan, September 2004. R. Tedrake, T. W. Zhang, M.-F. Fong, and H. S. Seung. Actuating a Simple 3D Passive Dynamic Walker. (pdf) In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), volume 5, pages 4656-4661, New Orleans, LA, April 2004. H. S. Seung. Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. (pdf) Neuron 40, 1063-1073 (2003). E. Aksay, R. Baker, H. S. Seung, and D. W. Tank. Correlated discharge among cell pairs within the oculomotor horizontal velocity-to-position integrator. (pdf) J. Neuroscience 23, 10852-10858 (2003). M. S. Goldman, J. H. Levine, G. Major, D. W. Tank, and H. S. Seung. Robust Persistent Neural Activity in a Model Integrator with Multiple Hysteretic Dendrites per Neuron. (pdf) Cerebral Cortex 13, 1185-1195 (2003). E. Aksay, G. Major, M. S. Goldman, R. Baker, H. S. Seung, and D. W. Tank. History dependence of rate covariation between neurons during persistent activity in an oculomotor integrator. (pdf) Cerebral Cortex 13, 1173-1184 (2003). H. S. Seung. Amplification, Attenuation, and Integration (pdf) in The Handbook of Brain Theory and Neural Networks: Second Edition (M. A. Arbib, Editor) Cambridge, MA: MIT Press, pp. 94-97 (2003). R. H. R. Hahnloser, H. S. Seung, and J. J. Slotine. Permitted and forbidden sets in symmetric threshold-linear networks. (pdf) Neural Comput. 15, 621-38 (2003). Earlier version: R. H. R. Hahnloser, H. S. Seung. Permitted and Forbidden Sets in Symmetric Threshold Linear Networks. (pdf) Adv. Neural Info. Proc. Syst. 13, 217-223 (2001). X. Xie and H. S. Seung. Equivalence of backpropagation and contrastive Hebbian learning in a layered network. (pdf) Neural Comput. 15, 441-54 (2003). X. Xie, R. H. R. Hahnloser, and H. S. Seung. Double-ring network modeling of the head-direction system (pdf) Phys. Rev. E66, 041902 (2002). X. Xie, R. H. R. Hahnloser, and H. S. Seung. Selectively grouping neurons in recurrent networks of lateral inhibition. (pdf) Neural Comput. 14, 2627-46 (2002). Earlier version: X.-H. Xie, R. Hahnloser and H. S. Seung. Learning winner-take-all competition between groups of neurons in lateral inhibitory networks (pdf) Adv. Neural Info. Proc. Syst. 13, 350-356 (2001). M. S. Goldman, C. R. Kaneko, G. Major, E. Aksay, D. W. Tank, and H. S. Seung. Linear regression of eye velocity on eye position and head velocity suggests a common oculomotor neural integrator. (pdf) J. Neurophysiol. 88, 659-65 (2002). D. Z. Jin and H. S. Seung. Fast computation with spikes in a recurrent neural network. (pdf) Phys. Rev. E65, 051922 (2002). R. Tedrake and H. S. Seung. Improved Dynamic Stability using Reinforcement Learning. (pdf) In 5th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR), pages 341-348, Paris, France, September 2002. E. Aksay, G. Gamkrelidze, H. S. Seung, R. Baker, and D. W. Tank. In vivo intracellular recording and perturbation of persistent activity in a neural integrator (pdf) Nature Neurosci. 4, 184- 93 (2001). D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. (pdf) Adv. Neural Info. Proc. Syst. 13, 556-562 (2001). H. S. Seung and D.D. Lee. The Manifold ways of perception. (pdf) Science 290, 2268-69 (2000). H. S. Seung. Half a century of Hebb. (pdf) Nature Neurosci. 3, 1166-67 (2000). R. H. R. Hahnloser, R. Sarpeshkar, M. A. Mahowald, R. J. Douglas, and H. S. Seung. Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit.