TCN: Difference between revisions
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* [Jan 30] Zipser et al. 1996 - Contextual Modulation in Primary Visual Cortex [http://www.jneurosci.org/content/16/22/7376.full.pdf+html] | * [Jan 30] Zipser et al. 1996 - Contextual Modulation in Primary Visual Cortex [http://www.jneurosci.org/content/16/22/7376.full.pdf+html] | ||
Ayzenshtat et al. 2012 - Population Response to Natural Images in the Primary Visual Cortex Encodes Local Stimulus Attributes and Perceptual Processing [http://www.jneurosci.org/content/32/40/13971.full.pdf+html] | |||
* [Jan 08] Cathart-Harris et al. 2012 - Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin [http://www.pnas.org/content/109/6/2138.long] | * [Jan 08] Cathart-Harris et al. 2012 - Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin [http://www.pnas.org/content/109/6/2138.long] |
Revision as of 17:39, 1 February 2013
Topics in Computational Neuroscience
Spring 2013
- [Feb 06] Girosi 1998 - An Equivalence Between Sparse Approximation and Support Vector Machines [1][2]
- [Jan 30] Zipser et al. 1996 - Contextual Modulation in Primary Visual Cortex [3]
Ayzenshtat et al. 2012 - Population Response to Natural Images in the Primary Visual Cortex Encodes Local Stimulus Attributes and Perceptual Processing [4]
- [Jan 08] Cathart-Harris et al. 2012 - Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin [5]
Fall 2012
- [Aug 29] Salakhutdinov & Hinton 2012 - An Efficient Learning Procedure for Deep Boltzmann Machines [8]
- [Sep 05] Coates & Ng 2011 - An Analysis of Single-Layer Networks in Unsupervised Feature Learning [9]
- [Sep 12] Quiroga 2012 - Concept Cells: The Building Blocks of Declarative Memory Functions [10]
- [Oct 10] Moira & Bialek 2011 - Are Biological Systems Poised at Critcality? [11]
- [Oct 17] Newman 2005 -Power laws, Pareto distributions and Zipfʼs law. [12]
- [Nov 28] Todorov 2004 -Optimality Principles in Sensorimotor Control. [13]
Spring 2011
- [Feb 10] Anastassiou et al. Ephaptic coupling of cortical neurons [14]
- [Feb 10] Jin et al. Population receptive fields of ON and OFF thalamic inputs to an orientation column in visual cortex [15]
- [Jan 20] A review of NIPS 2010 papers. [16]
Fall 2010
- [Dec 9] Welling. Herding algorithms. [17]
- [Dec 2] Neal. MCMC using Hamiltonian dynamics. [18]
- [Nov 18] Mairal et al. Task-driven dictionary learning. [19]
- [Oct 21] Hamed. Self-referential dynamical systems for the self-organization of behavior in robotic systems. Ch 2-3 of [20]
- [Oct 14] Hammond, Vandergheynst, and Gribonval. Wavelets on graphs via spectral graph theory. [21]
- [Oct 7] Neal. Annealed importance sampling. [22]
- [Sep 30] Martius, Herrmann. Taming the beast: Guided self-organization of behavior in autonomous robots. [23]
- [Sep 23] Bullier, Jean. "What is Fed Back?" in 23 Problems in Systems Neuroscience. [24]
Past TCN Papers
Time and Location
1:00-2:00pm usually every Thursday in the Redwood Center (508-20 Evans). For the Spring term, we are meeting sporadically based on interest. Please sign up to the email list (below) for announcements on meeting dates.
Overview
This journal club is aimed at graduate students from the neuroscience program, neuroscience related life sciences, as well as students from engineering, physics, and math programs with an interest in a computational approach to studying the brain. It provides a broad survey of literature from theoretical and computational neuroscience. Readings will combine both seminal works and recent theories. We meet for one session each week.
It is possible to take this seminar for credit. If you would like to do so, please mention during journal club.
If you have questions, please email the club organizer Mayur Mudigonda.
E-mail List
To subscribe to the journal club email list, visit link. You will receive emails twice a week about papers that will be covered in the next meeting.
Guidelines for Presenting Papers
Each person that selects a paper should present, in about 15-30 minutes:
- an executive summary
- an outline of the key points, ideas, or contributions
- relevant background information
- a description of the key figures
- what you took away from the paper
- some potential questions for discussion
- you are encouraged to use whatever method to present (slides, puppets, etc.)