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Difference between revisions of "VS265: Reading"

From RedwoodCenter

(2 Dec)
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* Crick and Mitchison theory on 'unlearning' during sleep - [http://redwood.berkeley.edu/vs265/crick-mitchison-sleep.pdf paper]
 
* Crick and Mitchison theory on 'unlearning' during sleep - [http://redwood.berkeley.edu/vs265/crick-mitchison-sleep.pdf paper]
 
* Application of Boltzmann machines to neural data analysis:<br>
 
* Application of Boltzmann machines to neural data analysis:<br>
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.<br>
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** 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.<br>
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.<br>
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** 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.<br>
Urs paper
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** U. Koster, J. Sohl-Dickstein, C.M. Gray, B.A. Olshausen, [http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1003684#pcbi-1003684-g007 Modeling higher-order correlations within Cortical Microcolumns], PLOS Computational Biology, July 2014.
 
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* Kalman filter
* Robbie Jacobs' [http://www.bcs.rochester.edu/people/robbie/jacobslab/cheat_sheet/sensoryIntegration.pdf notes on Kalman filter]
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** 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
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** [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]
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** Greg Welch's [http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html  tutorial on Kalman filter]
* [http://vision.ucla.edu/~doretto/projects/dynamic-textures.html Dynamic texture models]
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** [http://vision.ucla.edu/~doretto/projects/dynamic-textures.html Dynamic texture models]
* Kevin Murphy's [http://redwood.berkeley.edu/vs265/murphy-hmm.pdf  HMM tutorial]
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** Kevin Murphy's [http://redwood.berkeley.edu/vs265/murphy-hmm.pdf  HMM tutorial]
 
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==== 21 Nov ====
 
==== 21 Nov ====

Revision as of 17:49, 2 December 2014

Aug 28: Introduction

Optional:

Sept 2: Neuron models

Background reading on dynamics, linear time-invariant systems and convolution, and differential equations:

Sept 4: Linear neuron, Perceptron

Background on linear algebra:

Sept 11: Multicompartment models, dendritic integration (Rhodes guest lecture)

Sept. 16, 18: Supervised learning

  • HKP Chapters 5, 6
  • Handout on supervised learning in single-stage feedforward networks
  • Handout on supervised learning in multi-layer feedforward networks - "back propagation"

Further reading:

Sept. 23, 24: Unsupervised learning

  • HKP Chapters 8 and 9, DJCM chapter 36, DA chapter 8, 10
  • Handout: Hebbian learning and PCA
  • PDP Chapter 9 (full text of Michael Jordan's tutorial on linear algebra, including section on eigenvectors)

Optional:

Sept 30, Oct 2: Attractor Networks and Associative Memories (Sommer guest lectures)

  • "HKP" Chapter 2 and 3 (sec. 3.3-3.5), 7 (sec. 7.2-7.3), DJCM chapter 42, DA chapter 7
  • Handout on attractor networks - their learning, dynamics and how they differ from feed-forward networks
  • Hopfield82
  • Hopfield84
  • Willshaw69

Oct 7: Ecological utility and the mythical neural code (Feldman guest lecture)

  • Feldman10 Ecological utility and the mythical neural code

Oct 9: Hyperdimensional computing (Kanerva guest lecture)

Oct 16: Structural and Functional Connectomics (Tom Dean guest lecture)

21,23,28 Oct

Additional readings:

30 Oct, 4 Nov

Optional:

Re-organization in response to cortical lesions:

6 Nov

Additional reading:

6, 13 Nov

13,18 Nov

20,25 Nov

2 Dec

21 Nov


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