Theoretical Neuroscience Journal Club
Spring 2015 - APPL 595B
Organizers: Jean-Marc Fellous, Ozan Koyluoglu and Kevin Lin

• 1: Tu Jan 20th: Organizational meeting. No readings. Flyer can be found here.
• 2: Tu Jan 27th: Introduction to Computational Neuroscience.
  • Main Papers: T. J. Sejnowski , C. Koch , P. S. Churchland, "Computational Neuroscience", Science, 1988. <PUBMED> <PDF>
    L. F. Abbott, "Theoretical Neuroscience Rising," Neuron, 2008. <PUBMED> <PDF>.
  • Optional papers: T. J. Sejnowski, "Open questions about computation in Cerebral Cortex," 1986. <PDF>
    Wulfram Gerstner, Henning Sprekeler, and Gustavo Deco, "Theory and Simulation in Neuroscience," Science, 2012. <PUBMED> <PDF>
• 3: Tu Feb 3rd: Theme1 - Memory: Review of the main memory systems (Tatiana)
  • Main Paper: Computational models of working memory: putting long-term memory into context. Burgess and Hitch. 2005. <PUBMED> <PDF>
  • Optional Paper: Some targets for memory models. Lewandowsky and Heit, 2006. <PDF>
• 4: Tu Feb 10th: Theme1 - Memory: David presenting
  • Main Paper: P. Wilken and W. J. Ma, "A detection theory account of change detection", Journal of Vision, 2004. <PUBMED>, <PDF>
  • Optional Paper: G. A. Alvarez and P. Cavanagh, "The capacity of visual short-term memory is set both by visual information load and by number of objects", Psychological science, 2004. <PUBMED> <PDF>
• 5: Tu Feb 17th: Theme1 - Memory: Nirmal presenting
  • Main Paper: C. D. Brody, R. Romoz, and A. Kepecs, "Basic mechanisms for graded persistent activity: discrete attractors, continuous attractors, and dynamic representations", Current Opinion in Neurobiology, vol. 13, no. 2, pp. 204-211, 2003. <PUBMED> <PDF>.
  • Optional: A. K. Jain, M. Jianchang, and K. M. Mohiuddin, "Artificial neural networks: a tutorial", Computer, vol. 29, no. 3, pp. 31-44, 1996. <PDF>
• 6: Tu Feb 24th: Theme1 - Memory: Irmak presenting
  • T. Toyoizumi, M. Kaneko, M. P. Stryker, and K. D. Miller, "Modeling the dynamic interaction of Hebbian and homeostatic plasticity", Neuron, vol. 84, no. 2, pp. 497-510, 2014.<PUBMED> <PDF>
  • L. F. Abbott and S. B. Nelson, "Synaptic plasticity: Taming the beast", Nature Neuroscience, pp. 1178-1183, 2000.<PUBMED> <PDF>
• 7: Tu March 3rd: Theme1 - Memory: Sam presenting
  • Main paper: A. Compte, N. Brunel, P. S. Goldman-Rakic, X. J. Wang, "Synaptic mechanisms and network dynamics underlying spatial working memory in a cortical network model", Cereb Cortex, vol. 10, no. 9, pp. 910-23, Sep. 2000. <PUBMED> <PDF>
  • Optional: P. S. Goldman-Rakic, "Cellular basis of working memory", Neuron, vol. 14, no. 3, pp. 477-85, Mar. 1995. <PUBMED> <PDF>
• 8: Tu March 24th: Theme2 - Spatial Navigation: Patrick presenting
  • Main paper: S. Grossberg and P. K. Pilly, "How entorhinal grid cells may learn multiple spatial scales from a dorsoventral gradient of cell response rates in a self-organizing map," PLoS Comput Biol. vol. 8, no. 10, 2012. <PUBMED> <PDF>
  • Optional: E. Moser, E. Kropff, and M. B. Moser, "Place cells, grid cells, and the brain's spatial representation system," Annual Review of Neuroscience, vol. 31, pp. 69-89, 2008. <PUBMED> <PDF>
• 9: Tu March 31st: Theme2 - Spatial Navigation: Irmak presenting
  • Main Paper: Bush D and Burgess N. A hybrid oscillatory interference/continuous attractor network model of grid cell firing. J neuroscience, 14:5065-79, 2014. <PUBMED> <PDF>
  • Optional Paper: N. Burgess, C. Barry, and J. O'Keefe, "An oscillatory interference model of grid cell firing," Hippocampus, vol. 17, no. 9, pp. 801-812, Sep. 2007.
• 10: Tu April 7th:Theme2 - Spatial Navigation: Nirmal presenting
  • K. Yoon, M. A. Buice, C. Barry, R. Hayman, N. Burgess, and I. R. Fiete, "Specific evidence of low-dimensional continuous attractor dynamics in grid cells," Nature Neuroscience, pp. 1077-1084, Jul. 2013. <PUBMED> <PDF>
• 11: Tu April 14th: Theme3 - Bayesian Modeling: Tatiana Presenting
  • Main paper: M. Colombo and Series P."Bayes in the Brain—On Bayesian Modelling in Neuroscience", Br J Philos Sci., vol. 63, no. 3, pp. 697-723, 2012. <REF> <PDF>
  • Optional paper:
    • J. X. O'Reilly and R. B. Mars, "Bayesian models in cognitive neuroscience: A tutorial", An introduction to model-based cognitive neuroscience (Forstmann BU, Wagenmakers EJ, Eds.) Springer. <PDF>
    • Hahn U. The Bayesian boom: good thing or bad? Front. Hum. Neurosci., 04 August 2014 | doi: 10.3389/fnhum.2014.00571 <PUBMED>
• 12: Tu April 21st: Theme3 - Bayesian Modeling: Sam Presenting
  • Main paper: W.-J. Ma, J. M. Beck, P. E. Latham, and A. Pouget, "Bayesian inference with probabilistic population codes," Nature Neuroscience, No. 11, Vol. 9, Nov. 2006. <PUBMED> <PDF>
  • Optional: Alexandre Pouget, Jeffrey M Beck, Wei Ji Ma & Peter E Latham. Probabilistic brains: knowns and unknowns. Nature Neuroscience, 16(9)1170-1177, 2013. <PDF>
• 13: Tu April 28th: Theme3 - Bayesian Modeling: David Presenting
  • Main Paper: R. Moreno-Botea, D. C. Knill, and A. Pouget, "Bayesian sampling in visual perception," PNAS, vol. 108, no. 3, Jul. 2011. <PUBMED> <PDF>
  • Optional paper: A. Pouget, J. M. Beck, W. J. Ma, P. E. Latham, "Probabilistic brains: knowns and unknowns," Nature Neuroscience, vol. 16, no. 9, pp. 1170-1178, 2013.
• 14: Tu May 5th: Theme3 - Bayesian Modeling: Invited talk - prof Bob Wilson
  • Talk Title: The Explore-Exploit Dilemma in Human Reinforcement Learning

 

Useful links

Previous Journal Club Pages can be found here