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Introduction to Computational Neuroscience >> Content Detail



Study Materials



Readings

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Many of the readings are from the required course text:

Amazon logo Dayan, Peter, and L. F. Abbott.Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA: MIT Press, 2001. ISBN: 9780262041997.


Lec #TOPICSREADINGS
1Introduction

Examples of Neural Coding, Simple Linear Regression
Dayan and Abbott, section 1.1.

Wessel, R., C. Koch, and F. Gabbiani. "Coding of time-varying electric field amplitude modulations in a wave-type electric fish." J of Neurophysiology 75, no. 6 (1996): 2280-93.

Amazon logo Press, William H., Brian P. Flannery, Saul A. Teukolsky, and William T. Vetterling. "Fitting Data to a Straight Line." In Numerical Recipes in C: The Art of Scientific Computing. New York, NY: Cambridge University Press, 1992. ISBN: 9780521431088.
2Convolution and Correlation 1

Firing Rate
Dayan and Abbot, section 1.2-1.3.

Amazon logo Press, William H., Brian P. Flannery, Saul A. Teukolsky, and William T. Vetterling. "Convolution and Deconvolution Using the FFT." In Numerical Recipes in C: The Art of Scientific Computing. New York, NY: Cambridge University Press, 1992. ISBN: 9780521431088.
Optional Lecture 1

Initializing and Using Vectors and Matrices in MATLAB®, Matrix Shortcuts, Plots in MATLAB®, Useful Commands

Simple Statistics and Linear Regression
3Convolution and Correlation 2

Spike-triggered Average

Wiener-Hopf Equations and White Noise Analysis
Dayan and Abbot, sections 2.1-2.2.

Amazon logo Press, William H., Brian P. Flannery, Saul A. Teukolsky, and William T. Vetterling. "Correlation and Autocorrelation Using the FFT." In Numerical Recipes in C: The Art of Scientific Computing. New York, NY: Cambridge University Press, 1992. ISBN: 9780521431088.
4Visual Receptive Fields 1

Basics of the Visual System, Center-surround Receptive Fields, Simple and Complex Cortical Cells
Amazon logo Palmer, Stephen E. Vision Science - Photons to Phenomenology. Cambridge, MA: MIT Press, 1999, pp. 146-154. ISBN: 9780262161831.

Dayan and Abbot, sections 2.3-2.6.

Web site: Space-Time Receptive Fields of Visual Neurons.
Optional Lecture 2

Probability Theory
5Visual Receptive Fields 2
Optional Lecture 3

Markov Processes
6Operant Matching 1Gallistel, C., T. Mark, A. King, and P. Latham. "The Rat Approximates an Ideal Detector of Changes in Rates of Reward." Journal of Experimental Psychology: Animal Behavior Processes 27 (2001): 354-372.

Herrnstein, R. "On the Law of Effect." Journal of the Experimental Analysis of Behavior 13, no. 2 (March 1970): 243-266.
7Operant Matching 2Seung, H. S. "Matching and maximizing are two ends of a spectrum of policy search algorithms." Manuscript (January 2, 2004.) (PDF)

Herrnstein, R., and D. Prelec. Melioration: A Theory of Distributed Choice. The Journal of Economic Perspectives 5, no. 3 (Summer, 1991): 137-156.
8Games 1Amazon logo Camerer, Colin F. Behavioral Game Theory. Princeton, NJ: Princeton University Press, 2003. ISBN: 9780691090399.
Optional Lecture 4

Linear Stability Analysis
9Games 2Sanfey, A., J. Rilling, J. Aronson, L. Nystrom, and J. Cohen. "The Neural Basis of Economic Decision-Making in the Ultimatum Game." Science 300, no. 5626 (June 13, 2003): 1755-8.

Camerer, C. "Strategizing in the Brain." Science 300, no. 5626 (June 13, 2003): 1673-5.
10Project Meeting 1

Discussion of Topics, Choice of Projects, Work Begins
11Project Meeting 2
12Project Meeting 3
13Project Meeting 4
14Project Presentations 1
15Project Presentations 2
16Ion Channels, Nernst Equation, Passive Electrical Properties of NeuronsDayan and Abbott, section 5.2.

Amazon logo Johnston, Daniel, and Samuel Miao-Sin Wu. Foundations of Cellular Neurophysiology. Cambridge, MA: MIT Press, 1994, chapter 2. ISBN: 9780262161831.
17The Action Potential, Hodgkin-Huxley Model 1Dayan and Abbot, sections 5.3, 5.5, and 5.6.

Amazon logo Koch, Christof. Biophysics of Computation, Information Processing in Single Neurons. New York, NY: Oxford University Press, 2004, chapter 6. ISBN: 9780195181999.
18Hodgkin-Huxley Model 2
19A-type Potassium Channels, Calcium-Dependent Potassium ChannelsDayan, and Abbott. Section 6.2.
20SynapsesDayan, and Abbott. Section 5.8.
Optional Lecture 5

Numerical Methods for Differential Equations
Dayan, and Abbott. Section 5.11. (Appendices A and B)

Sherman, A. "Lecture Notes and Lab Problems on Numerical Methods." (PDF) (Courtesy of Dr. Arthur Sherman, NIDDK, National Institutes of Health. This work is in the public domain.)

Arthur Sherman's Web page on Numerical Methods in Neuronal Modeling.
21Associative Memory 1Professor Seung's notes on the Hopfield Model (PDF)

Hopfield, J. J. "Neural networks and physical systems with emergent collective computational abilities." Proc Natl Acad Sci U.S.A. 79: 2554-58.
22Associative Memory 2More of Professor Seung's notes on Associative Memory (PDF)

Miyashita, Y. "Neuronal correlate of visual associative long-term memory in the primate temporal cortex." Nature 335 (1988): 817-20.

Griniasty, M., M. V. Tsodyks, and D. J. Amit. "Conversion of temporal correlations between stimuli to spatial correlations between attractors." Neural Comput 5 (1993): 1-17.

Amit, D. J. "The Hebbian paradigm reintegrated: local reverberations as internal representations." Behav Brain Sci 18 (1995): 617-26.

Nakazawa, K., M. C. Quirk, R. A. Chitwood, et al. "Requirement for Hippocampal CA3 NMDA Receptors in Associative Memory Recall." Science 297 (2002): 211-218.
23Decisionmaking
24Projects
25
Projects (cont.)
26Review
Final Exam

 








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