VS265: Reading Fall2010: Difference between revisions

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* Smith, Lewicki. [http://redwood.berkeley.edu/vs265/smith-lewicki-nature06.pdf Efficient auditory coding], Nature Vol 439 (2006).
* Smith, Lewicki. [http://redwood.berkeley.edu/vs265/smith-lewicki-nature06.pdf Efficient auditory coding], Nature Vol 439 (2006).


<!--A handout on sparse coding and on 'ICA', something we haven't yet discussed:
==== 5 Oct ====
* [http://redwood.berkeley.edu/vs265/sparse-coding-handout.pdf Sparse coding and 'ICA' ]-->


<!--Dayan and Abbott has a nice section on sparse coding in Chapter 10. This is on the syllabus for unsupervised learning already, but you may want to focus on section 10.3 and 10.4.-->
* [http://redwood.berkeley.edu/vs265/miller89.pdf Ocular dominance column development: Analysis and simulation] by Miller, Keller and Stryker.
* [http://redwood.berkeley.edu/vs265/durbin-mitchison.pdf A dimension reduction framework for understanding cortical maps] by R. Durbin and G. Mitchison.
* [http://redwood.berkeley.edu/vs265/horton05.pdf The cortical column: a structure without a function] by Jonathan C. Horton and Daniel L. Adams


<!--Here is a link to [http://www.dsp.ece.rice.edu/cs/ Compressive Sensive Resources] at Rice. It has an enormous number of recent papers related to compressed sensing and sparse coding.-->
Here are some additional links to papers mentioned in lecture. Optional reading:
 
- Gary Blasdel, [http://redwood.berkeley.edu/vs265/blasdel1992.pdf Orientation selectivity, preference, and continuity in monkey striate cortex.], J Neurosci, 1992.  Another source of many of nice images are in the galleries on Amiram Grinvald's site: [http://www.weizmann.ac.il/brain/grinvald/]
 
- From Clay Reid's lab, [http://www.nature.com/nature/journal/v433/n7026/abs/nature03274.html Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex]. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [http://reid.med.harvard.edu/movies.html].
 
==== 7 Oct ====
 
* [http://redwood.berkeley.edu/vs265/tenenbaum-manifold.pdf A Global Geometric Framework for Nonlinear Dimensionality Reduction ], Tenenbaum et al., Science 2000.
* [http://redwood.berkeley.edu/vs265/roweis-saul-manifold.pdf Nonlinear Dimensionality Reduction by Locally Linear Embedding], Roweis and Saul, Science 2000.
* [http://redwood.berkeley.edu/vs265/carlsson-ijcv08.pdf On the Local Behavior of Spaces of Natural Images], Carlsson et al., Int J Comput Vis (2008) 76: 1–12.
 
Additional reading:
 
* [http://redwood.berkeley.edu/vs265/webster-face-adaptation.pdf Adaptation to natural facial categories], Michael A. Webster, Daniel Kaping, Yoko Mizokami & Paul Duhamel, Nature, 2004.
* [http://redwood.berkeley.edu/vs265/leopold.pdf Prototype-referenced shape encoding revealed by high-level aftereffects], David A. Leopold, Alice J. O’Toole, Thomas Vetter and Volker Blanz, Nature, 2001.
 
==== 12/14 Oct ====
 
* [http://redwood.berkeley.edu/vs265/attractor-networks.pdf Handout] on attractor neural networks
* [http://redwood.berkeley.edu/vs265/hopfield82.pdf original Hopfield (1982) paper]
* [http://redwood.berkeley.edu/vs265/hopfield84.pdf Hopfield (1984) paper]
* [http://redwood.berkeley.edu/vs265/marr-poggio-science76.pdf Marr-Poggio stereo algorithm paper]
* [http://redwood.berkeley.edu/vs265/zhang96.pdf Kechen Zhang paper on bump circuits]
* [http://redwood.berkeley.edu/vs265/olshausen-etal93.pdf Olshausen, Anderson & Van Essen, dynamic routing circuit model]
* HKP Chapters 2 and 3
 
==== 19 Oct (David Zipser guest lecture) ====
 
* [http://redwood.berkeley.edu/vs265/zipser-manual.pdf manual] for David Zipser's BPTT simulator
 
==== 26 Oct ====
 
* [http://redwood.berkeley.edu/vs265/probability.pdf A probability primer]
* [http://redwood.berkeley.edu/vs265/bayes-prob.pdf Bayesian probability theory and generative models]
* [http://redwood.berkeley.edu/vs265/mog.pdf Mixture of Gaussians model ]
 
==== 2/4 Nov ====
 
* HKP Chapter 7, section 7.1
 
Application to neural data analysis:
* E. Schneidman, M.J. Berry, R. Segev and W. Bialek,[http://www.nature.com/nature/journal/v440/n7087/full/nature04701.html Weak pairwise correlations imply strongly correlated network states in a neural population], Nature 4400 (7087) (2006), pp. 1007-1012.
* J. Shlens, G.D. Field, J.L. Gauthier, M.I. Grivich, D. Petrusca, A. Sher, A.M. Litke and E.J. Chichilnisky, [http://www.jneurosci.org/cgi/content/abstract/26/32/8254 The structure of multi-neuron firing patterns in primate retina], J Neurosci 260 (32) (2006), pp. 8254-8266.
 
==== 16 Nov ====
 
* [http://redwood.berkeley.edu/vs265/info-theory.pdf Information theory primer]
* [http://redwood.berkeley.edu/vs265/handout-sparse-08.pdf Sparse coding and ICA handout]
* Bell and Sejnowski, [http://redwood.berkeley.edu/vs265/tony-ica.pdf An Information-Maximization Approach to Blind Separation and Blind Deconvolution], Neural Comp, 1995.
* Hyvarinen, Hoyer, Inki, [http://redwood.berkeley.edu/vs265/TICA.pdf Topographic Independent Component Analysis], Neural Comp, 2001.
* Karklin & Lewicki paper on  [http://redwood.berkeley.edu/vs265/karklin-lewicki2003.pdf Learning Higher-Order Structure in Natural Images], Network 2003.
* Shao & Cottrell paper on [http://redwood.berkeley.edu/vs265/hshan-nips06.pdf Recursive ICA], NIPS 2006.
 
==== 18 Nov ====
 
* Robbie Jacobs' [http://www.bcs.rochester.edu/people/robbie/jacobslab/cheat_sheet/sensoryIntegration.pdf notes on Kalman filter]
* [http://redwood.berkeley.edu/vs265/kalman.m kalman.m] demo script
* Greg Welch's [http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html  tutorial on Kalman filter]
* [http://vision.ucla.edu/~doretto/research.html Dynamic texture models]
* Kevin Murphy's [http://redwood.berkeley.edu/vs265/murphy-hmm.pdf  HMM tutorial]
 
==== 23 Nov ====
 
* Chris Eliasmith, Charlie Anderson, [http://books.google.com/books?id=J6jz9s4kbfIC Neural Engineering:  Computation, Representation, and Dynamics in Neurobiological Systems], MIT Press, 2004.
 
Chapter 4 will be emailed to the class.
 
* Softky and Koch, [http://redwood.berkeley.edu/vs265/softky-koch-jn93.pdf The Highly Irregular Firing of Cortical Cells Is Inconsistent with Temporal Integration of Random EPSPs], J Neuroscience, January 1993, 13(1):334-350.
* Mainen and Sejnowski, [http://redwood.berkeley.edu/vs265/mainen-sejnowski.pdf Reliability of Spike Timing in Neocortical Neurons], Science, Vol 268, 6 June 1995.
* Shadlen and Newsome, [http://redwood.berkeley.edu/vs265/shadlen-newsome1.pdf Noise, neural codes and cortical organization], Curr Opin in Neur, 1994, 4:569-579.
* Shadlen and Newsom, [http://redwood.berkeley.edu/vs265/shadlen-newsome1.pdf Is there a signal in the noise?], Current Opin in Neur, 1995, 5:248-250.
* Softky, [http://redwood.berkeley.edu/vs265/softky-commentary.pdf Simple codes versus efficient codes], Current Opin in Neuro, 1995, 5:239-247.
* Izhikevich, [http://redwood.berkeley.edu/vs265/izhikevich-nn03.pdf Simple model of spiking neurons], IEEE Trans Neur Networks, 14(6):2003.
* Izhikevich, [http://redwood.berkeley.edu/vs265/izhikevich-which-nn04.pdf Which Model to Use for Cortical Spiking Neurons?], IEEE Trans Neur Networks, 15(5):2004.
 
==== 2 Dec (Jeff Hawkins guest lecture) ====
 
* Numenta document on [http://redwood.berkeley.edu/vs265/HTM_CorticalLearningAlgorithms.pdf Hierarchical Temporal Memory]
 
==== 7 Dec (Paul Rhodes guest lecture) ====
 
* Niell, Meyer, & Smith, [http://redwood.berkeley.edu/vs265/niell-smith-nn04.pdf In vivo imaging of synapse formation on a growing dendritic arbor], Nature Neuroscience, 7, 254-260.
 
* Meyer, & Smith, [http://redwood.berkeley.edu/vs265/meyer-smith-jn06.pdf Evidence from In Vivo Imaging That Synaptogenesis Guides the Growth and Branching of Axonal Arbors by Two Distinct Mechanisms], Journal of Neuroscience, 26, 3604-3614.
 
==== 9 Dec (Pentti Kanerva guest lecture) ====
 
* Kanerva, P [http://www.amazon.com/Sparse-Distributed-Memory-Bradford-Books/dp/0262111322 Sparse Distributed Memory]

Latest revision as of 02:55, 28 August 2012

26 Aug

Optional:

31 Aug

02 Sep

07 Sep

  • Handout on supervised learning in single-stage feedforward networks
  • Handout on supervised learning in multi-layer feedforward networks - "backpropagation"
  • Y. LeCun, L. Bottou, G. Orr, and K. Muller (1998) "Efficient BackProp," in Neural Networks: Tricks of the trade, (G. Orr and Muller K., eds.).
  • NetTalk demo

21 Sep

Optional:

28 Sep

Optional readings:

5 Oct

Here are some additional links to papers mentioned in lecture. Optional reading:

- Gary Blasdel, Orientation selectivity, preference, and continuity in monkey striate cortex., J Neurosci, 1992. Another source of many of nice images are in the galleries on Amiram Grinvald's site: [1]

- From Clay Reid's lab, Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Make sure you look at the supplementary material and videos on their web site (seems partly broken) [2].

7 Oct

Additional reading:

12/14 Oct

19 Oct (David Zipser guest lecture)

  • manual for David Zipser's BPTT simulator

26 Oct

2/4 Nov

  • HKP Chapter 7, section 7.1

Application to neural data analysis:

16 Nov

18 Nov

23 Nov

Chapter 4 will be emailed to the class.

2 Dec (Jeff Hawkins guest lecture)

7 Dec (Paul Rhodes guest lecture)

9 Dec (Pentti Kanerva guest lecture)