Past TCN Papers

From RedwoodCenter

Syllabus (Topics and Readings)

Spring 2011

  • [Feb 10] Anastassiou et al. Ephaptic coupling of cortical neurons [1]
  • [Feb 10] Jin et al. Population receptive fields of ON and OFF thalamic inputs to an orientation column in visual cortex [2]
  • [Jan 20] A review of NIPS 2010 papers. [3]

Fall 2010

  • [Dec 9] Welling. Herding algorithms. [4]
  • [Dec 2] Neal. MCMC using Hamiltonian dynamics. [5]
  • [Nov 18] Mairal et al. Task-driven dictionary learning. [6]
  • [Oct 21] Hamed. Self-referential dynamical systems for the self-organization of behavior in robotic systems. Ch 2-3 of [7]
  • [Oct 14] Hammond, Vandergheynst, and Gribonval. Wavelets on graphs via spectral graph theory. [8]
  • [Oct 7] Neal. Annealed importance sampling. [9]
  • [Sep 30] Martius, Herrmann. Taming the beast: Guided self-organization of behavior in autonomous robots. [10]
  • [Sep 23] Bullier, Jean. "What is Fed Back?" in 23 Problems in Systems Neuroscience. [11]

Summer 2010

  • [June 10]
    • Jarzynski, Nonequilibrium work relations: foundations and applications. [12]
    • Crooks, Nonequilibrium Measurements of Free Energy Differences for Microscopically Reversible Markovian Systems. [13]
    • Crooks, Beyond Boltzmann-Gibbs statistics: Maximum entropy hyperensembles out of equilibrium [14]
  • [May 20] Truccolo et al., Collective dynamics in human and monkey sensorimotor cortex: predicting single neuron spikes [15]

Spring 2010

  • [May 13] A review of active learning (no paper).
  • [Apr 29] Ranzato and Hinton, Modeling Pixel Means and Covariances Using Factorized Third-Order Boltzmann Machines [16]
  • [Apr 22] Boureau et al., Learning Mid-Level Features For Recognition [17]
  • [Apr 15] Neghaban et al., A unified framework for the analysis of regularized $M$-estimators.[18]
  • [Apr 6] Lucke et al., Occlusive components analysis. [19]
  • [Mar 25] Bießmann et al., Decision-related activity in sensory neurons reflects more than a neuron's causal effect.[20]
  • [Mar 18] Itskov and Abbott, Pattern Capacity of a Perceptron for Sparse Discrimination. [21]
  • [Mar 11] Nienborg and Cumming, Decision-related activity in sensory neurons reflects more than a neuron's causal effect.[22]
  • [Feb 18] Masse et al., Olfactory Information Processing in Drosophila. [23]
  • [Feb 11] Yaghoobi et al., Dictionary Learning for Sparse Approximations with the Majorization Method. [24]
  • [Feb 4] Ecker et al., Decorrelated Neuronal Firing in Cortical Microcircuits. [25]
  • [Feb 4] Renart et al., The Asynchronous State in Cortical Circuits. [26]
  • [Jan 28] Recht et al., Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization. [27]

Fall 2009

  • [Dec 3] Kolgin et al., Frequency of gamma oscillations routes flow of information in the hippocampus. [28]
  • [Nov 17] Graham, Chandler, Field. Can the theory of ‘‘whitening’’ explain the center-surround properties of retinal ganglion cell receptive fields? [29]
  • [Nov 12] Lighthill and AI community debate, 1973. [30]
  • [Oct 29, Nov 5] George, Hawkins, Towards a Mathematical Theory of Cortical Micro-circuits. [31]
  • [Oct 22]: Berkes et al., A Structured Model of Video Reproduces Primary Visual Cortical Organisation.[32]
  • [Oct 15]: Petreanu et al., The subcellular organization of neocortical excitatory connections. [33]
  • [Oct 15]: Arenz et al. The contribution of single synapses to sensory representation in vivo. [34]
  • [Oct 1,8]: Kobilarov et al., Lie Group Integrators for Animation and Control of Vehicles.[35]

Last papers covered

indicates papers we've read. The others are suggestions for future readings.

  • Tutorial on Conjugate Gradient - no paper but An Introduction to the Conjugate Gradient Method Without the Agonizing Pain by Jonathan Richard Shewchuk might be useful: link - Presenter: Chris Hillar
  • Tutorial on Natural Gradient - no paper but Amari. Natural gradient works efficiently in learning. Neural Computation, Amari 1998 might be useful: link - Presenter: Jascha
  • Distilling Free-Form Natural Laws from Experimental Data, Michael Schmidt1 and Hod Lipson 2009. Science 324(59233): link - Presenter: Daniel
  • Learning Optical Flow, Deqing Sun, Stefan Roth, J. P. Lewis, and Michael Black. EECV 2008: link - Presenter: Jack
  • Decision-theoretic saliency: computational principles, biological plausibility, and implications for neurophysiology and psychophysics, Gao D, Vasconcelos N. Neural Comput. 2009 Jan;21(1):239-71.: link - Presenter: Daniel
  • Temporal interactions between cortical rhythms, Roopun AK, Kramer MA, Carracedo LM, Kaiser M, Davies CH, Traub RD, Kopell NJ and Whittington MA. (2008) Front. Neurosci. 2,2:145-154. doi:10.3389/neuro.01.034.2008: link - Presenter: Kilian
  • Recognition of natural scenes from global properties: seeing the forest without representing the trees, Greene, M.R. & Oliva, A. 2009 Cognitive Psychology Vol. 58(2), pp. 137-76 link - Presenter: Paul Ivanov
  • Cogito componentiter ergo sum, Lars Kai Hansen and Ling Feng. Lecture Notes in Computer Science, 2006: link - Presenter: ?
  • Tutorial on representation theory and invariance - no paper but A novel set of rotationally and translationally invariant features for images based on the non-commutative bispectrum by Risi Kondor might be useful: link - Presenter: Chris Hillar
  • If I Were You: Perceptual Illusion of Body Swapping, Petkova VI, Ehrsson HH 2008. PLoS ONE 3(12): e3832 doi:10.1371/journal.pone.0003832 link - Presenter: Jascha
  • Multisensory integration in macaque visual cortex depends on cue reliability, Morgan ML, Deangelis GC, Angelaki DE., Neuron. 2008 Aug 28;59(4):662-73. link - Presenter: Rama Natarajan
  • Design of Linear Equalizers Optimized for the Structural Similarity Index, S. Channappayya, Alan Bovik, C. Caramanis, R. Heath Jr; IEEE Transactions on Image Processing, Vol 17 NO 6 June 2008 link - Presenter: Jimmy
  • Kalman filtered compressed sensing, Namrata Vaswani, ICIP 2008 link - Presenter: Jack
  • Transient Induced Gamma-Band Response in EEG as a Manifestation of Miniature Saccades, Shlomit Yuval-Greenberg, Orr Tomer, Alon S. Keren, Israel Nelken and Leon Y. Deouell, Neuron, 58, pp. 429–441, 2008. link - Presenter: Paul and Tim
  • Internally Generated Reactivation of Single Neurons in Human Hippocampus During Free Recall, Hagar Gelbard-Sagiv, Roy Mukamel, Michal Harel, Rafael Malach, Itzhak Fried, Science, Published Online September 4, 2008. link - Presenter: Will
  • Saliency Detection: A Spectral Residual Approach, Xiaodi Hou and Liqing Zhang, in Proc. of CVPR '07, pp. 1-8, 2007. link - Presenter: Chetan
  • The information bottleneck method, N. Tishby, F.C. Pereira and W. Bialek, in Proceedings of the 37th Annual Allerton Conference on Communication, Control and Computing, B. Hajek and R.S. Sreenivas eds, pp. 368-377 (University of Illinois, 1999). link - Presenter: Pierre
  • Evolutionary expansion and anatomical specialization of synapse proteome complexity, R. D. Emes et al., Nature Neuroscience, vol. 11, no. 7, pp. 799-806, June 2008. link - Presenter: Jeff
  • Stability of the fittest: organizing learning through retroaxonal signals, Ken Harris, Trends Neurosci, 31(3), pp. 130-136, 2008. link - Presenter: Will
  • Object recognition with cortex-like mechanisms, T. Serre, L. Wolf, S. Bileschi, M. Riesenhuber and T. Poggio, IEEE Transactions on Pattern Analysis and Machine Intelligence, 29 (3), pp. 411-426, 2007. link- Presenter: Jack
  • Nonlinear extraction of 'Independent Components' of elliptically symmetric densities using radial Gaussianization, S. Lyu and E. P. Simoncelli, Computer Science Technical Report TR2008-911, Apr 2008. link - Presenter: Bruno
  • Relating neural dynamics to neural coding, G. Bard Ermentrout, Roberto F. Galàn and Nathaniel N. Urban, Physical Review Letters, vol. 99, no. 24, December 2007. link - Presenter: Ariel
  • Spatio-temporal correlations and visual signaling in a complete neuronal population, Jonathan W. Pillow, Jonathon Shlens, Liam Paninski, Alexander Sher, Alan M. Litke, E. J. Chichilnisky, Eero P. Simoncelli, Nature (to appear), 2008. - Presenter: Jonathon Shlens
  • Learning Compressed Sensing, Yair Weiss and Hyun Sung Chang and William T. Freeman, Allerton 2007. link - Presenter: Pierre
  • Sparse and shift-invariant feature extraction from non-negative data, P. Smaragdis, B. Raj, and M.V. Shashanka, In proceedings IEEE International Conference on Audio and Speech Signal Processing, April 2008. link - Presenter: Vivienne
  • Context and hierarchy in a probabilistic image model, Y. Jin and S. Geman, CVPR (2) 2006, pp. 2145-2152. link - Presenter: Amir
  • Entrainment of neuronal oscillations as a mechanism of attentional selection, Peter Lakatos, George Karmos, Ashesh D. Mehta, Istvan Ulbert, Charles E. Schroeder, Science, vol. 320, no. 5872, pp. 110-113, April 2008. link - Presenter: Gianluca
  • The missing memristor found, Dmitri B. Strukov, Gregory S. Snider, Duncan R. Stewart, R. Stanley Williams, Nature, vol. 453, pp. 80-83, May 2008. - Presenter: Chris
  • 80 million tiny images: a large dataset for non-parametric object and scene recognition, A. Torralba, R. Fergus, W. T. Freeman, submitted to IEEE PAMI, October 2007. link - Presenter: Jascha
  • Decoupling through Synchrony in Neuronal Circuits with Propagation Delays, E. V. Lubenov and A. G. Siapas. Neuron, vol. 58, 2008, pp. 118-131. link - Presenter: Amir
  • The role of learning in 3-D form perception, P. Sinha and T. Poggio. Nature, vol. 384, no 6608, 1996, pp. 460-463. link - Presenter: Charles
  • Sparse Feature Learning for Deep Belief Networks, M. Ranzato, Y. Boureau, Y. LeCun. Advances in Neural Information Processing Systems 20 (NIPS 2007). link - Presenter: Jimmy
  • Phase-of-Firing Coding of Natural Visual Stimuli in Primary Visual Cortex, Marcelo A. Montemurro, Malte J. Rasch, Yusuke Murayama, Nikos K. Logothetis, and Stefano Panzeri. Current Biology, vol. 18, no. 5, Mar 2008, pp. 375-380. link - Presenter: Kilian
  • Multisensory auditory–visual interactions during early sensory processing in humans: a high-density electrical mapping study, Sophie Molholm, Walter Ritter, Micah M. Murray, Daniel C.Javitt, Charles E. Schroeder and John J. Foxe. Cognitive Brain Research, vol. 14, no. 1, Jun 2002, pp. 115-128. link - Presenter: Gianluca
  • The sleep switch: hypothalamic control of sleep and wakefulness, Clifford B. Saper, Thomas C. Chou and Thomas E. Scammell, Trends in Neurosciences, Vol. 24, No. 12, Dec 2001. link - Presenter: Will
  • Sparse time-frequency representations, T. J. Gardner and M. O. Magnasco, PNAS, vol. 103, no. 16, pp. 6094-6099, 2006. link - Presenter: Marcelo Magnasco
  • Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication, H. Jaeger and H. Haas, Science, Vol. 304, Issue 5667, pp. 78-80, 2004. link - Presenter: Jascha
  • Does spatial invariance result from insensitivity to change?, F. A. A. Kingdom, D. J. Field and A. Olmos, Journal of Vision, 7(14):11, 1-13, Dec. 2007. link - Presenter: Bruno Olshausen
  • How Behavioral Constraints May Determine Optimal Sensory Representations, Emilio Salinas, PLoS Biology, 6:12, Dec. 2006. link - Presenter: Lavi Secundo
  • Convexity, disparity, and depth perception: internalization of natural scene statistics. Johannes Burge, Charless C. Fowlkes, Martin S. Banks. DRAFT. Presenter: Johannes Burge
  • The K-SVD: An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation. IEEE Trans. On Signal Processing, Vol. 54, no. 11, pp. 4311-4322, November 2006. link Presenter: Gianluca Monaci
  • Image Denoising with Nonparametric Hidden Markov Trees. J. Kivinen, E. Sudderth, and M. Jordan. ICIP 2007. link Presenter: Jack Culpepper
  • Coupling between neuronal firing, field potentials, and FMRI in human auditory cortex. Mukamel R, Gelbard H, Arieli A, Hasson U, Fried I, Malach R. Science. 2005 Aug 5;309(5736):951-4. link Presenter: Tim Blanche
  • The design and use of steerable filters. W. T. Freeman and E. H. Adelson, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 13, no. 9, pp. 891 - 906, September, 1991. linkPresenter: Jimmy Wang
  • Problem reduction, renormalization, and memory. Commun. Appl. Math. Comput. Sci. 1 1-27. Chorin, Alexandre J. and Stinis, Panagiotis (2006). Presenter: Amir and Fritz
  • Learning Lie Groups of Visual Invariance. Xu Miao and Rajesh P.N. Rao. Neural Computation 19,2665-2693 (2007). Presenter: Pierre Garrigues
  • Correlation between neural spike trains increases with firing rate. Jaime de la Rocha, Brent Doiron, Eric Shea-Brown, Kresimir Josic & Alex Reyes. Nature 448, 802-806 (16 August 2007) link. Presenter: Chris Rozell
  • Adaptation to Stimulus Contrast and Correlations during Natural Visual Stimulation. Nicholas A Lesica, Jianzhong Jin, Chong Weng, Chun-I Yeh, Daniel A Butts, Garrett B Stanley, Jose-Manuel Alonso. Neuron 2007 vol. 55 pp. 479-91. Presenter: Tim Blanche
  • Quest for a Stochastic Grammar of Images. Song-Chun Zhu and David Mumford. To appear in Foundations and Trends in Computer Graphics and Vision, 2007. link. Presenter: Amir
  • Slow feature analysis yields a rich repertoire of complex cell properties. Berkes, P. and Wiskott, L. (2005). Journal of Vision, 5(6), 579-602. link. Presenter: Charles Cadieu
  • Unsupervised learning of image transformations. Memisevic, R. and Hinton, G. E. Computer Vision and Pattern Recognition 2007 link. Presenter: Jack Culpepper
  • The thalamus as a monitor of motor outputs. R. W. Guillery and S. M. Sherman. Phil. Trans. R. Soc. Lond. B (2002) 357, 1809-1821. Presenter: Jascha Sohl-Dickstein
  • Recovering Intrinsic Images from a Single Image. Tappen, M. F., Freeman, W. T., and Adelson, E. H.. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(9): 1459 - 1472, (2005). link Presenter: Chetan Nandakumar
  • N. Ay, D. Polani. Information Flows in Causal Networks. Advances in Complex Systems, submitted. Santa Fe Institute Working Paper 06-05-014. link Presenter: Joe Makin
  • Der R., Hesse F., Liebscher R.: Contingent robot behavior from self-referential dynamical systems. Autonomous robots submitted. link Presenter: Fritz Sommer
  • Z Wang, A C Bovik and E P Simoncelli. Structural approaches to image quality assessment. Chapter 8.3 in Handbook of Image and Video Processing, 2nd Edition, ed. Alan Bovik, Academic Press, 2005. link Presenter: Jimmy Wang
  • O. Ben-Shahar and S.W. Zucker. Geometrical Computations Explain Projection Patterns of Long Range Horizontal Connections in Visual Cortex, in Neural Computation, 16(3): 445-476, 2004. link Presenter: Pierre Garrigues
  • Zhaoping L. (2005) Border Ownership from Intracortical Interaction in Visual Area V2 , in NEURON, Vol. 47, 143-153 link Presenter: Paul King
  • Nakayama, K. , He, Z.J. and Shimojo, S. Visual surface representation: a critical link between lower-level and higher level vision. In Kosslyn, S.M. and Osherson, D.N. Vision. In Invitation to Cognitive Science. M.I.T. Press, p. 1-70, 1995 link Presenter: Jascha Sohl-Dickstein
  • Sinha, P., Balas, B.J., Ostrovsky, Y., & Russell, R."Face Recognition by Humans: 19 results all computer vision researchers should know about." Proceedings of the IEEE. Vol. 94, No. 11, 1948-1962 (2006) [web.mit.edu/bcs/sinha/papers/20Results_2005.pdf link] Presenter: Chetan Nandakumar
  • Chandler DM, and Field DJ. "Estimates of the Information Content and Dimensionality of Natural Scenes from Proximity Distributions." Journal of the Optical Society of America, 2006 (in press) link Presenter: Paul Ivanov
  • Z. Tu, X. Chen, A.L. Yuille, and S.C. Zhu. "Image Parsing: Unifying Segmentation, Detection, and Recognition". Proceedings of ICCV 2003. link Presenter: Jimmy Wang
  • E. Schneidman, M. Berry, R. Segev and W. Bialek. "Weak pairwise correlations imply strongly correlated network states in a neural population". Nature 440, 1007-1012 (20 April 2006) link Presenter: Pierre Garrigues
  • S. Ullman, S. Soloviev. "Computation of Pattern Invariance in Brain-like Structures". Neural Networks 1999. link Presenter: Charles Cadieu
  • P. Bak, C. Tang, and K. Wiesenfeld. "Self-Organized Critically: An Explanation of 1/f Noise". Physical Review Letters, July 1987. Presenter: Kilian Koepsell
  • A. Hyvarinen. "Estimation of Non-Normalized Statistical Models by Score Matching". Journal of Machine Learning Research 6 (2005) 695-709. Presenter: Jascha Sohl-Dickstein
  • M. Ranzato, C.S. Poultney, S. Chopra and Y. LeCun. "Efficient Learning of Sparse Overcomplete Representations with an Energy-Based Model". Advances in Neural Information Processing Systems 19, in Scholkopf et al. (eds), MIT Press, Cambridge, MA, 2007. Presenter: Pierre Garrigues
  • Liam Paninski, Jonathan Pillow and Eero Simoncelli. Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model. Neural Computation, 2004. Presenter: Amir
  • Randall C. O'Reilly. Biologically Based Computational Models of High-Level Cognition. Science Oct. 2006. Presenter: Charles Cadieu
  • Todorov, E. and Jordan, M. I. Optimal feedback control as a theory of motor coordination. Nature Neuroscience 5, 1226-1235, 2002.
  • Asari, H., Pearlmutter, B. A. and Zador, A. M. Sparse Representations for the Cocktail Party Problem. The Journal of Neuroscience, July 12, 2006.
  • Hinton, G. E. and Salakhutdinov, R. R. Reducing the dimensionality of data with neural networks. Science, Vol. 313. no. 5786, pp. 504 - 507, 28 July 2006.
  • P. Dayan, Image, Frames, and Connectionist Hierarchies. Neural Computation 18, 2293-2319 (2006)
  • T. Blaschke, P. Berkes and L. Wiskott, What Is the Relation Between Slow Feature Analysis and Independent Component Analysis? Neural Computation 18, 2495-2508 (2006)
  • T.J. Gardner, and M.O. Magnasco, Sparse time-frequency representations PNAS 103: 6094-6099, April 18, 2006 paper
  • B.L. McNaughton, F.P. Battaglia, O. Jensen, E.I. Moser and M.B. Moser, Path integration and the neural basis of the 'cognitive map'. Nature Reviews Neuroscience 7, 663-678 (August 2006) paper
  • Karklin, Lewicki. A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals. Neural Computation. 2005;17:397-423. paper MSRI talk
  • Perspectives: Jose-Manuel Alonso, Neurons Find Strength Through Synchrony in the Brain, Science, 16 June 2006, Vol. 312. no. 5780, pp. 1604 - 1605 link
  • Randy M. Bruno and Bert Sakmann, Cortex Is Driven by Weak but Synchronously Active Thalamocortical Synapses, Science, 16 June 2006, Vol. 312. no. 5780, pp. 1622 - 1627 link
  • David J. Foster and Matthew A. Wilson, Reverse replay of behavioural sequences in hippocampal place cells during the awake state, Nature 440, 680-683 (30 March 2006) link
  • Guetig, Sompolinsky. The Tempotron: a neuron that learns spike timing-based decisions. Nature Neuroscience 2006; 9:420-428. link
  • E. Smith and M. S. Lewicki, Efficient Auditory Coding, Nature, 439 (7079), 2006. link
News and Views: DeWeese and Zador, "Neurobiology: Efficiency measures". link
  • D. Y. Tsao, W. A. Freiwald, R. B. H. Tootell, M. S. Livingstone, A Cortical Region Consisting Entirely of Face-Selective Cells, Science 3 February 2006; Vol. 311. no. 5761, pp. 670 - 674. link
Perspectives: Kanwisher, "What's in a Face?". link
  • Harris Nover, Charles H. Anderson, and Gregory C. DeAngelis. A Logarithmic, Scale-Invariant Representation of Speed in Macaque Middle Temporal Area Accounts for Speed Discrimination Performance. J. Neurosci., Oct 2005; 25: 10049 - 10060 link
  • Randy M. Bruno and Bert Sakmann, Cortex Is Driven by Weak but Synchronously Active Thalamocortical Synapses, Science, 16 June 2006, Vol. 312. no. 5780, pp. 1622 - 1627 link
Perspectives: Jose-Manuel Alonso, Neurons Find Strength Through Synchrony in the Brain, Science, 16 June 2006, Vol. 312. no. 5780, pp. 1604 - 1605 link
  • C Whitney & P Cornelissen (2005). Letter-position encoding and dyslexia. Journal of Research in Reading 28, 274-301. paper

Early Work

  • K. A. C. Martin, The Pope and grandmother−a frog's-eye view of theory, Nature Neuroscience 3, 1169 (2000) link
  • Lettvin, Maturana, McCulloch, Pitts, "What the Frog's Eye Tells the Frog's Brian" link
  • Barlow HB (1972) Single Neurons and Sensation: A neuron doctrine for perceptual psychology. Perception 1, 371-394. link
  • Marvin Minsky, Steps Toward Artificial Intelligence link
  • McCulloch and Pitts, “A logical calculus of the ideas immanent in nervous activity” (1943) link
  • Marr, selection from Vision; Artificial Intelligence—a personal view, by David Marr link
  • Readings from Dartmouth Conf. 1956 proceedings
  • Rosenblatt, Frank (1962). Principles of neurodynamics. New York: Spartan. Cf. Rumelhart, D.E., J. L. McClelland and the PDP Research Group (1986). Parallel Distributed Processing vol. 1&2. Cambridge: MIT. link
  • "Making a Mind Versus Modeling the Brain: Artificial Intelligence Back at a Branchpoint" (with H. Dreyfus),Daedulus, Winter 1988 link


  • Kreiman, G. Neural Coding: Computational and Biophysical Perspectives, Physics of Life Reviews, 2, 71-102, 2004. link
  • Pouget, A, Dayan, P & Zemel, RS (2000). Information processing with population codes. Nature Reviews Neuroscience, 1 , 125-132. link
  • E. Smith and M. S. Lewicki, Efficient Auditory Coding, Nature, 439 (7079), 2006. link
News and Views: DeWeese and Zador, "Neurobiology: Efficiency measures" link
  • Olshausen BA, Field DJ. Sparse Coding of Sensory Inputs. Curr Op in Neurobiology, 14: 481-487 (2004). link
  • Coding and computation with neural spike trains. W Bialek & A Zee, J. Stat. Phys. 59, 103–115 (1990). link
  • Selection from: Spikes: Exploring the Neural Code. F Rieke, D Warland, R de Ruyter van Steveninck & W Bialek (MIT Press, Cambridge, 1997). link
  • H. Nover, C. H. Anderson, and G. C. DeAngelis, A Logarithmic, Scale-Invariant Representation of Speed in Macaque Middle Temporal Area Accounts for Speed Discrimination Performance, J. Neurosci., Oct 2005; 25: 10049 - 10060 link
  • Ray Singh and Chris Eliasmith, Higher-Dimensional Neurons Explain the Tuning and Dynamics of Working Memory Cells, J. Neurosci. 2006;26 3667-3678 link

Cortical Microcircuit/Universal Cortical Algorithm

  • Vernon Mountcastle (1978), "An Organizing Principle for Cerebral Function: The Unit Model and the Distributed System", The Mindful Brain (Gerald M. Edelman and Vernon B. Mountcastle, eds.) Cambridge, MA: MIT Press link
  • Rodney J. Douglas, Kevan A.C. Martin, Neural Circuits of the Neocortex, Annual Review of Neuroscience 2004 27, 419-451 link
  • Selection from: Hawkins, J., On Intelligence (Chapter 6) link
  • Henry Markram, The Blue Brain Project, Nature Neuroscience, 7:153-160, 2006. link
  • Douglas RJ, Martin KAC Whitteridge D. (1989) A canonical microcircuit for neocortex. Neural Computation 1: 480-488. link (the related talk at the Redwood symposium)
  • Cross-modal plasticity in cortical development: differentiation and specification sensory cortex, by Mriganka Sur, Sarah L. Pallas and Anna W. Roe. link
  • Poggio, T. and E. Bizzi. Generalization in Vision and Motor Control, Nature, Vol. 431, 768-774, 2004. link
  • Marr D, "A Theory for Cerebral Neocortex", Proc Roy Soc London(B), 176, 161-234, 1970. link

Feedback, Hierarchical Organization, Generative Models

  • David Mumford, Neuronal Architectures for Pattern-theoretic Problems, in "Large-Scale Neuronal Theories of the Brain", C.Koch & J.Davis, editors, MIT Press, 1994, pp.125-152. link
  • RPN Rao. Bayesian inference and attention in the visual cortex. Neuroreport 16(16), 1843-1848, 2005. link
  • TS Lee, D Mumford Hierarchical Bayesian inference in the visual cortex, Journal of the Optical Society of America A, 2003 link
  • Felleman, DJ and Van Essen, DC (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1, 1-47. link

Manifold Learning

  • Richard Durbin & Graeme Mitchison, A dimension reduction framework for understanding cortical maps, Nature 343, 644 - 647 (15 February 1990) link
  • Tal Kenet, Dmitri Bibitchkov, Misha Tsodyks, Amiram Grinvald and Amos Arieli, Spontaneously emerging cortical representations of visual attributes, Nature 425, 954-956 (30 October 2003) link
  • Selection from: Self-Organizing and Associative Memory, T Kohonen - Japanese translation 2nd Edition, Splinger-Verlag Tokyo, 1994 link
  • JB Tenenbaum, V de Silva, JC Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, 2000 link
  • ST Roweis, LK Saul, Nonlinear Dimensionality Reduction by Locally Linear Embedding, Science, 2000 link
  • Nicholas V. Swindale, Doron Shoham, Amiram Grinvald, Tobias Bonhoeffer & Mark Hübener, Visual cortex maps are optimized for uniform coverage, Nature Neuroscience 3, 822 - 826 (2000) link

Background reading on SOMs

  • Neural Computation and Self-Organizing Maps - An Introduction, by Helge Ritter, Thomas Martinetz, and Klaus Schulten, Addison-Wesley, New York, 1992, Kohonen's Network Model Contents

Plasticity, Hebbian Learning

  • Dan, Y. and Poo, M.-m. (2004). Spike timing-dependent plasticity of neural circuits. Neuron 44, 23-30 link
  • Abbott LF, Nelson SB. (2000) Synaptic plasticity: taming the beast. Nat Neurosci. 3 Suppl:1178-83. link
  • P. Foldiak, Forming sparse representations by local anti-Hebbian learning, Biological Cybernetics, vol. 64, pp. 165-170, 1990. link
  • M. Tsodyks, Spike-timing-dependent synaptic plasticity–The long road towards understanding neuronal mechanisms Trends in Neuroscience, 2002. link
  • Saudargienne A, Porr B, and Worgotter F. How the shape of pre- and postsynaptic signals can influence STDP: a biophysical model. Neural Comp 16: 595–625, 2004. link
  • Seung, HS (2000) Half a century of Hebb. Nat. Neurosc. Suppl: 1166. link
  • H. S. Seung. Learning in spiking neural networks by reinforcement of stochastic synaptic transmission. Neuron 40, 1063-1073 (2003). link
  • Hinton, G. E. and Sejnowski, T. J. (1986), Learning and relearning in Boltzmann machines. In Rumelhart, D. E. and McClelland, J. L., editors, Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Volume 1: Foundations, MIT Press, Cambridge, MA. link


  • Gray, CM (1999) The temporal correlation hypothesis of visual feature integration: still alive and well. Neuron. 1999, 24(1):31-47, 111-25. Review. link
  • Neuron Special Issue on Oscillations, 1999, 24(1) link

Associative Memory

  • J Hopfield. Neural Networks and Physical Systems with Emergent Collective Computational Abilities. PNAS, 79:2554-2558 (1982) link
  • S. Fusi, P.J. Drew, and L.F. Abbott, Cascade Models of Synaptically Stored Memories, Neuron 2005 45: 599-611. link
  • G. Palm. On the storage capacity of an associative memory with randomly distributed storage elements. Biol. Cybernetics. 36:19-31 (1980). link
  • Selection from: Self-Organizing and Associative Memory, T Kohonen - Japanese translation 2nd Edition, Splinger-Verlag Tokyo, 1994

Models of Invariance

  • Olshausen BA, Anderson CH, Van Essen DC (1993). A Neurobiological Model of Visual Attention and Invariant Pattern Recognition Based on Dynamic Routing of Information, The Journal of Neuroscience, 13(11), 4700-4719. link
  • K Fukushima, Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position, Biological Cybernetics (Historical Archive), Volume 36, Issue 4, Apr 1980, Pages 193 - 202 link
  • P. Foldiak, Learning invariance from transformation sequences, Neural Computation, vol. 3, pp. 194-200, 1991. link
  • L Wiskott. Slow Feature Analysis: Unsupervised Learning of Invariances. Neural Computation. 2002;14:715-770. link

Active Perception-sensorimotor loops

  • D. Philipona, J.K.O'Regan & J.-P. Nadal. Is there something out there? Inferring space from sensorimotor dependencies. Neural Computation, 2003, 15, 9, 2029-2050. link
  • Philipona, D., O Regan, J.K., Nadal, J.-P. and Coenen, O. J.-M. D. Perception of the structure of the physical world using multimodal unknown sensors and effectors. Advances in Neural Information Processing Systems, 16, 2004. link
  • Churchland P, Ramachandran VS, Sejnowski TJ. Large-Scale Neuronal Theories of the Brain: Chapter 2, Critique of Pure Vision, 1994. link
  • Oregan JK, Noe A. A sensorimotor account of vision and visual consciousness, BBS (2001) 24:939-1031. link


  • Anthony Leonardo & Michale S. Fee. Ensemble Coding of Vocal Control in Birdsong. The Journal of Neuroscience, January 19, 2005, 25(3):652-661. link (Warning: 27.7 MB .pdf)
  • Troyer TW, Bottjer SW. Birdsong: models and mechanisms. Curr Opin Neurobiol. 2001 Dec;11(6):721-6. link

Theories of the Ventral Stream

  • Ullman, S. (1995). Sequence-seeking and counter streams: A computational model for bi-directional information flow in the visual cortex. Cerebral Cortex, 5(1) 1-11. link
  • Riesenhuber, M., and T. Poggio. Models of Object Recognition, Nature Neuroscience, 3 Supp., 1199-1204, 2000. link
  • Riesenhuber, M. and T. Poggio. How Visual Cortex Recognizes Objects: The Tale of the Standard Model. In: The Visual Neurosciences, (Eds. L.M. Chalupa and J.S. Werner), MIT Press, Cambridge, MA, Vol. 2, 1640-1653, 2003. link
  • Rolls,E.T. (1997) A neurophysiological and computational approach to the functions of the temporal lobe cortical visual areas in invariant object recognition. Chapter 9, pp. 184-220 in Computational and Psychophysical Mechanisms of Visual Coding, eds. M.Jenkin and L.Harris. Cambridge University Press: Cambridge. link


  • Crick, Francis, and Graeme Mitchison. "The Function of Dream Sleep." Nature 304, (14 July 1983): 111-114. link
  • Sutherland GR, McNaughton B., Memory trace reactivation in hippocampal and neocortical neuronal ensembles., Curr Opin Neurobiol. 2000 Apr;10(2):180-6 link

Theories of Hippocampus

  • Becker, S. (2005) "A computational principle for hippocampal learning and neurogenesis". Hippocampus 15(6):722-738. link
  • Leutgeb, S., Leutgeb, J.K., Moser, M.-B., and Moser, E.I. (2005). Place cells, spatial maps and the population code for memory. Current Opinion in Neurobiology, 15, 738-746. link
  • Hasselmo, M.E. and McClelland, J.L. (1999) Neural models of memory. Curr. Opinion Neurobiol. 9: 184-188. link

Motor System

  • Körding, KP. and Wolpert, D. (2004) Bayesian Integration in Sensorimotor Learning, Nature 427:244-247. link
  • Georgopoulos AP. Neuron. 1994 Aug;13(2):257-68. New concepts in generation of movement. link
  • Todorov E Direct cortical control of muscle activation in voluntary arm movements: a model. (2000) Nature Neuroscience 3(4): 391-398 link
  • Todorov E. On the role of primary motor cortex in arm movement control (2003) In Progress in Motor Control III, ch 6, pp 125-166, Latash and Levin (eds), Human Kinetics link
  • Scott, S.H. (2004) Optimal feedback control and the neural basis of volitional motor control. Nature Reviews Neuroscience 5:532-546. link


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