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Link to Mainpage: [[TCN]]
Link to Mainpage: [[TCN]]


== Post Your Suggested Topics or Paper (click on Edit)==
===Charles===
* Kovesi, Image Features from Phase Congruency. [http://mitpress.mit.edu/e-journals/Videre/001/articles/v1n3001.pdf]
* Friewald et al., A face feature space in the macaque temporal lobe. [http://www.nature.com/neuro/journal/v12/n9/abs/nn.2363.html]


===Sleep===
===Nicol===
* Crick, Francis, and Graeme Mitchison. "The Function of Dream Sleep." Nature 304, (14 July 1983): 111-114.
* Labat, Idier, Sparse blind deconvolution accounting for time-shift ambiguity. [http://www.irccyn.ec-nantes.fr/~idier/pub/pubC/Labat06bC.pdf]


* 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) [http://www.nature.com/nature/journal/v440/n7084/pdf/nature04587.pdf link]
===Jack===
* Kobilarov et al., Lie Group Integrators for Animation and Control of Vehicles.[http://www.geometry.caltech.edu/pubs/KCD09.pdf]


===Other topics===
===Jimmy===
* Heitz, Koller. Learning Spatial Context: Using Stuff to Find Things. [http://robotics.stanford.edu/~koller/Papers/Heitz+Koller:ECCV08.pdf]


*Karklin, Lewicki. A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals. Neural Computation. 2005;17:397-423. [http://video.google.com/videoplay?docid=-5115453018099427284&q=msri MSRI talk]
===Amir===
* Wierzynski et al., Hippocampal-prefontal spike timing during sleep. [http://dx.doi.org/10.1016/j.neuron.2009.01.011]
* Petreanu et al., The subcellular organization of neocortical excitatory connections. [http://www.nature.com/nature/journal/v457/n7233/pdf/nature07709.pdf]
<!--* Huys, Paninski, Smoothing of and Parameter Estimation from Noisy Biophysical Recordings. [http://dx.doi.org/10.1371%2Fjournal.pcbi.1000379]-->
<!-- * Ballard et al., Minimizing communication in linear algebra. [http://arxiv.org/pdf/0905.2485]-->


*Guetig, Sompolinsky. The Tempotron: a neuron that learns spike timing-based decisions. Nature Neuroscience 2006; 9:420-428. [http://www.nature.com/neuro/journal/v9/n3/pdf/nn1643.pdf]
===Guy===
* Sharpee et al., Analyzing neural responses to natural signals: Maximally informative dimensions [http://www.princeton.edu/~wbialek/our_papers/sharpee+al_04.pdf]


*Hinton, Dayan, Frey, Neal. The wake-sleep algorithm for unsupervised Neural Networks. Science, 268, 1158-1161.
===Bruno===
* Zoran & Weiss, Scale Invariance and Noise in Natural Images. [http://www.cs.huji.ac.il/~yweiss/zoranweiss09.pdf]
* Anderson & Martin, The Synaptic Connections between Cortical Areas V1 and V2 in Macaque Monkey.  [http://www.jneurosci.org/cgi/reprint/29/36/11283]
* Ozden et al. Reliable Coding Emerges from Coactivation of Climbing Fibers in Microbands of Cerebellar Purkinje Neurons  [http://www.jneurosci.org/cgi/reprint/29/34/10463]
* Learning to Traverse Image Manifolds


*Nakayama, He, Shimojo. Visual Surface Representation: A critical link between Lower-level and Higher-level vision. Visual Congnition, 1995. [http://redwood.berkeley.edu/~amir/pdf/nakayama-1995.pdf]


* Zhu, Wu, Mumford. Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling. International Journal of Computer Vision 27(2), 107-126 (1998). [http://www.stat.ucla.edu/~sczhu/papers/FRAME.pdf]
[[Old Suggestion Board]]
 
* George, Hawkins. A Hierarchical Bayesian Model of Invariant Pattern Recognition in the Visual Cortex. [http://www.stanford.edu/~dil/invariance/Download/GeorgeHawkinsIJCNN05.pdf link]
 
* D.P. Wipf and B.D. Rao, "Sparse Bayesian Learning for Basis Selection," IEEE Transactions on Signal Processing, vol. 52, no. 8, August 2004. [http://ieeexplore.ieee.org/xpl/tocresult.jsp?isNumber=29166&puNumber=78 link]
 
* Alan A Stocker & Eero P Simoncelli. Noise characteristics and prior expectations in human visual speed perception. Nature Neuroscience 9, 578 - 585 (2006) [http://www.nature.com/neuro/journal/v9/n4/abs/nn1669.html]
 
* Wilson RI, Turner GC, and Laurent G. Transformation of olfactory representations in the Drosophila antennal lobe Science 303: 366-370 (2004) [http://marvin.caltech.edu/PDF/WilsonetalScience2004.pdf]
 
===Computational Biology===
* Paul W. K. Rothemund. Folding DNA to create nanoscale shapes and patterns. Nature 440, 297-302 (16 March 2006). [http://www.nature.com/nature/journal/v440/n7082/abs/nature04586.html link]
 
===Birdsong===
 
* Anthony Leonardo & Michale S. Fee.  Ensemble Coding of Vocal Control in Birdsong.  The Journal of Neuroscience, January 19, 2005, 25(3):652-661.  [http://www.jneurosci.org/cgi/reprint/25/3/652 link (Warning: 27.7 MB .pdf)]
 
Here's an example for formating:
 
===Topic===
* E. Smith and M. S. Lewicki, Efficient Auditory Coding, Nature, 439 (7079), 2006. [http://www.nature.com/nature/journal/v439/n7079/abs/nature04485.html link]
 
: News and Views: DeWeese and Zador, "Neurobiology: Efficiency measures". [http://www.nature.com/nature/journal/v439/n7079/full/439920a.html link]

Revision as of 06:40, 24 September 2009

Link to Mainpage: TCN

Charles

  • Kovesi, Image Features from Phase Congruency. [1]
  • Friewald et al., A face feature space in the macaque temporal lobe. [2]

Nicol

  • Labat, Idier, Sparse blind deconvolution accounting for time-shift ambiguity. [3]

Jack

  • Kobilarov et al., Lie Group Integrators for Animation and Control of Vehicles.[4]

Jimmy

  • Heitz, Koller. Learning Spatial Context: Using Stuff to Find Things. [5]

Amir

  • Wierzynski et al., Hippocampal-prefontal spike timing during sleep. [6]
  • Petreanu et al., The subcellular organization of neocortical excitatory connections. [7]

Guy

  • Sharpee et al., Analyzing neural responses to natural signals: Maximally informative dimensions [8]

Bruno

  • Zoran & Weiss, Scale Invariance and Noise in Natural Images. [9]
  • Anderson & Martin, The Synaptic Connections between Cortical Areas V1 and V2 in Macaque Monkey. [10]
  • Ozden et al. Reliable Coding Emerges from Coactivation of Climbing Fibers in Microbands of Cerebellar Purkinje Neurons [11]
  • Learning to Traverse Image Manifolds


Old Suggestion Board

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